Professor Yaochu Jin
About
Biography
I am a Distinguished Chair and Professor in Computational Intelligence, Co-Coordinator of the Centre for Mathematical and Computational Biology (CMCB), Department of Computer Science, University of Surrey. I was a Finland Distinguished Professor (2015-17) with the Multi-objective Optimization Group, Faculty of Information Technology, University of Jyvaskyla, Finland, and a Changjiang Distinguished Visiting Professor (2015-17), State Key Laboratory of Synthetical Automation of Process Industry, Northeastern University, China.
I am the Editor-in-Chief of the IEEE Transactions on Cognitive and Developmental Systems and Co-Editor-in-Chief of Complex & Intelligent Systems (Springer). I was an elected AdCom member (2012-2013), Vice President for Technical Activities (2014-2015), and an IEEE Distinguished Lecturer (2013-2015, 2017-2019) of the IEEE Computational Intelligence Society. I was elevated to an IEEE Fellow for contributions to evolutionary optimization.
I obtained the BSc, MSc and PhD degrees from Zhejiang University, Hangzhou, China and the Dr.-Ing. from Ruhr-University Bochum, Germany. Before joining Surrey in 2010, I was a Principal Scientist with Honda Research Institute Europe, Germany. I did postdoctoral research with the Industrial Engineering Department, Rutgers, the State University of New Jersey, USA from 1998 to 1999. I was an Assistant and Associate Professor with the Electrical Engineering Department, Zhejiang University, Hangzhou, China from 1992 to 1996.
I am an Associate Editor of the IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Transactions on Nanobioscience, Soft Computing (Springer), and BioSystems (Elsevier). I am also an Editorial Board Member of the Evolutionary Computation Journal (MIT Press) and Natural Computing (Springer). I am a past Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, and the IEEE Transactions on Control Systems Technology, IEEE Transactions on Autonomous Mental Development, and IEEE Computational Intelligence Magazine.
I am a Member of EPSRC Peer Review College and EPSRC ICT Responsive Mode Panel, a Panel Member of EC FP7 FET/HBP grants, a Panel Review Member of Academy of Finland and a Reviewer of VQR (Research Assessment), Italy.
I am the General Co-Chair of the 2016 IEEE Symposium Series on Computational Intelligence (SSCI 2016), Founding General Co-Chair of the IEEE Symposium on Computational Intelligence in Big Data, IEEE Symposium on Computational Intelligence in Multi-Criterion Decision-Making (IEEE MCDM), IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (IEEE CIDUE). I was General Chair of 2012IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2012) and Program Chair of 2013 IEEE Congress on Evolutionary Computation.
Previous roles
Affiliations and memberships
External PhD examiner
- PhD thesis, National University of Singapore, 2016
- PhD thesis, Multimedia University, Malaysia, 2016
- PhD thesis, IIT Delhi, India, 2015
- PhD thesis, NTU, 2014
- PhD thesis, CCU, Taiwan, ROC, 2014
- PhD thesis, Nanyang Technological University, 2014
- PhD thesis, University of Birmingham, 2014
- PhD thesis, Robert Gordon University, 2014
- PhD thesis, Bielefeld University, 2014
- PhD thesis, University of Sheffield, 2013 (Student: Rui Wang, Supervisor: Prof Peter Fleming, Dr Robin Purshouse)
- PhD thesis, SYSU, China, 2013
- PhD thesis, University of Bradford, 2013
- PhD thesis, University of Oxford, 2013 (Student: Zhenyu Wang, Supervisor: Dr V. Palade)
- PhD thesis, Hong Kong Polytechnic University, 2013 (Student: Yihong Zhang, Supervisor: Prof C.W. Yuen)
- PhD thesis, Universite Paris Sud, 2012 (Student: Ilya Loshchilov, Supervisor: Prof Marc Schoenauer)
- PhD thesis, RMIT University, Australia, 2012 (Student: Robert Carrese, Supervisor: Dr Jon Watmuff)
- PhD thesis, Brunel University, 2012 (Student: Sameera Alshayji, Supervisor: Prof Zidong Wang)
- PhD thesis, Universidad de Málaga, Spain, 2012 (Student: Jose D. Fernandez Rodriguez, Supervisor: Prof Francisco J. Vico)
- PhD thesis, University of Exeter, 2012 (Student: Andrew Clark, Supervisor: Prof Richard Everson)
- PhD thesis, Nanyang Technological University, 2012 (Student: Xianshun Chen, Supervisor: Prof Yew Soon Ong)
- PhD thesis, University of Manchester, 2012 (Student: Richard Allmendinger, Supervisor: Dr Joshua Knowles)
- PhD thesis, Birkbeck, University of London, 2011 (Student: Tony Lewis, Supervisor: Prof George Magoulas)
- PhD thesis, La Trobe University, Australia, 2011 (Student: Xi Li, Supervisor: Prof Dianhui Wang)
- PhD thesis, University of Leicester, 2011 (Student: Imtiaz Korejo, Supervisor: Dr Shengxiang Yang)
- PhD thesis, Gwangju Institute of Science and Technology, Korea, 2011 (Student: Sanghoun Oh, Supervisor: Prof. Moongu Jeon)
- PhD thesis, University of Dortmund, Germany, 2011 (Student: Boris Naujoks, Supervisor: Prof. Guenther Rudolph)
- PhD thesis, Department of Management Engineering, Technical University of Denmark, 2011 (Student: J.-F. Dupuis, Supervisor: Prof. Zhun Fan)
- PhD thesis, School of Computer Science, University of Birmingham, UK, 2011 (Student: Trung Thanh Nguyen, Supervisor: Prof. Xin Yao)
- PhD thesis, Department of Computer Science, University of Leicester, UK, 2011 (Student: Changhe Li, Supervisor: Dr Shengxiang Yang)
- PhD thesis, School of Computer Science and Information Technology, RMIT University, Australia, 2010 (Student: W.R.M.U.K. Wickramasinghe, Supervisor: Dr. Xiaodong Li)
- PhD thesis, Department of Electronics, The University of York, UK, 2010 (Student: Tuze Kuyucu, Supervisor: Prof. Andy Tyrrell)
- PhD thesis, Department of Computer Science and Engineering, Annamalai University, India, 2010 (Studenrt: M. Govindarajan, Supervisor: Prof. R.M. Chandrasekaran)
- PhD thesis, Section Computational Science, University of Amsterdam, The Netherlands, 2009 (Student: Yves Fomkong-Nanfack, Supervisor: Prof. Jaap Kaandorp)
- PhD thesis, School of Computer Science and Information Technology, RMIT University, Australia, 2008 (Student: Antony Iorio, Supervisor: Dr Xiaodong Li)
- PhD thesis, Department of Informatics and Systems, Universidad de las Palmas de Grand Canaria, Spain, 2008 (Student: Daniel E. Salazar Aponte, Supervisor: Prof. Blas Galván)
- PhD thesis, School of Computer Science, University of Essex, UK, 2007 (Student: Hui Li, Supervisor: Prof. Qingfu Zhang)
- PhD thesis, School of Computer Science, Nanyang Technological University, Singapore, 2006 (Student: Zongzhao Zhou, Prof. Yew Soon Ong)
- PhD thesis, Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 2005 (Student: Pawan K. S. Nain, Prof. Kalyanmoy Deb).
Grant reviewer/panel member
- Review Panel, EC HBP, 2014
- Review Panel, EPSRC ICT, 2014
- Review Panel, Academy of Finland, 2013,2014
- Review Panel, EU FP7 FET, 2013
- Royal Academy of Engineer, 2012
- DAAD, Germany, 2012
- Marsden Fund, New Zealand, 2012
- Italy VQR 2012
- Killam Research Fellowship, Canada Council , 2012
- Netherlands Organization for Scientific Research, 2011
- EPSRC, UK, 2011
- Research Promotion Foundation, Cyprus, 2011
- The EUROCORES Programme "EuroBioSAS", European Science Foundation, 2010
- Visiting Professorship Application, the Leverhulme Trust, 2010
- Netherlands Organization for Scientific Research, 2003.
Referee
- Promotion to Full Professorship, University of Notre Dame, USA, 2014
- Promotion to Full Professorship, Lancaster University, UK, 2014
- Promotion to Full Professorship, University of Exeter, UK, 2014
- Promotion to Full Professorship, University of Kansas, 2011
- Promotion to Full Professorship, Zhejiang University, 2010
- Young Scientist Award, Singapore National Academy of Science (SNAS)
- Research Award of ASEA Brown Boveri (ABB), 2003.
ResearchResearch interests
- Evolutionary optimisation
- Data driven evolutionary optimization
- Surrogate-assisted evolutionary optimization and Bayesian optimization, transfer optimization
- Robust and dynamic optimization, robustness over time, optimization in the presence of uncertainty
- Multi-objective and many-objective optimization
- Large-scale optimization, federated optimization
- Machine learning
- Deep learning, automated machine learning, neural architecture search
- Secure and trustworthy machine learning, adversarial machine learning, privacy-preserving federated learning, learning over encrypted data
- Evolutionary machine learning, multi-objective learning
- Real world applications include:
- Design optimization and control of complex systems, e.g., high-lift wing systems, fuselage of aircraft, turbine engines and vehicles, hybrid and electrical vehicles;
- Process optimization and control, including steel-making and continuous casting, and control of multi-level carbon fibre stretching processes; electric power transmission systems
- Image identification, face recognition and human behaviour detection
- Healthcare, bioinformatics and fintech
My science-driven research interests lie in interdisciplinary areas that bridge the gap between computational intelligence and machine learning, computational neuroscience, and computational biology. My current main topics include
- Evolutionary developmental systems (neural and morphological development, gene regulatory networks, brain-body co-evolution)
- Computational modelling of neural plasticity (computational modelling of plasticity, gene regulated plasticity in reservoir computing such as echo-state networks and liquid state machines)
- Morphogenetic robotics, including morphogenetic swarm and reconfigurable modular robotics.
Research projects
"Evolutionary Multi-objective Federated Learning" funded by industry (PI)The objective of this collaboration is to apply evolutionary optimization strategies to the multi-objective optimization of federated recommendation system with minimal effect on the user’s experience of the mobile device.
"Surrogate based runtime difference mitigation in asynchronous multi-disciplinary search tasks" funded by Honda Research Institute Europe (PI)Bayesian approaches to the optimization of complex systems have attracted much research in recent years and have achieved encouraging success. The project has mainly two aims: 1) Develop new training algorithms and new optimization methods that can deal with very low amount of training data for surrogate models and optimization evaluations. 2) Develop new infill criteria for Bayesian approaches to optimisation which integrate multiple models for estimating different criteria of a multi-objective problem or constraints.
"Multi-source side information fusion assisted Bayesian optimization" funded by Royal Society (PI)In this project, we study multi-source side information fusion assisted Bayesian optimization models and algorithms. The aim of this study is to fully exploit the side information to reduce the number of computational times of expensive fitness functions, and, meanwhile, to accurately construct response surface in the parameter space for effectively searching and recognizing the global optimum.
"Many-objective Bayesian optimization for vehicle dynamics" funded by Honda R&D Europe (PI)The project aims to improve digital development process for vehicle dynamics in the light of efficient many-objective optimization and smart visualization.
"Multi-objective evolutionary methods for hierarchical and multi-label classification" funded by FAPESP SPRINT, Brazil (PI: Ricardo Cerri, Co-I: Yaochu Jin)FAPESP SPRINT, Surrey-PI, PI: Dr Ricardo Cerri, UFSCar, Brazil
"Deep learning in mass spectrometry imaging" funded by EPSRC iCASE (PI)This project aims to develop new and innovative machine learning algorithms to analyse the data from the new 3D OrbiSIMS instrument (mass spectrometry) in a time and memory efficient manner. Current techniques limit the volume of data that can be analysed, and currently there are no methods to integrate the different modalities produced by the instrument. The 3D OrbiSIMS is the first of its kind and is involved in a large number of projects relating to antimicrobial resistance, cancer research, and material characterisation. The project offers a unique opportunity for candidates to contribute to a wide range of disciplines and impact a broad scientific base.
"Preference learning in multi-objective decision making" funded by Honda (PI)This project investigates the current state of the art methods and algorithms relevant for decision making support systems. Focus points of the investigation are multi- and many-objective evolutionary optimization methods as well as non-evolutionary MCDM methods and methods from portfolio management in relation to decision making support systems in which user of a system are supported in the task of selecting solutions from a numerically identified Pareto front.
"Data-driven surrogate-assisted evolutionary fluid dynamic optimization" funded by EPSRC (PI)This research proposal aims to permit the application of evolutionary algorithms, a class of global search metaheuristics, to fluid dynamic optimisation of highly complex industrial systems by exploiting surrogate models and modern machine learning techniques.
"Decision support for complex multiobjective optimization problems (DeCoMo)" funded by Tekes (PI: Kaisa Miettinen, Finland Distinguished Professor: Yaochu Jin)Finland Distinguished Professor
"A theoretical framework for swarms of GRN-controlled agents which display adaptive tissue-like organization - SWARM-ORGAN" funded by European Commission FP7 (PI)This project aims to use gene regulatory networks and morphogen gradients governing the biological development process for self-organizing large-scale swarm robots that can autonomously generating patterns for following and surrounding moving targets.
"Surrogate-assisted evolutionary many-objective optimization" funded by Honda Research Institute Europe (PI)This project aims to address the main challenges in evolutionary many-objective optimisation using model-based techniques and surrogate-assisted evolutionary optimisation.
"Optimisation of CFRP Stiffened Panels of Aircraft" funded by EPSRC KTA (PI)This project takes a detailed look at the design and use of materials in the aerospace industry, and will deliver a fully designed structure for use in aircraft design, and joins up a number of key themes in weight reduction, namely a reduction of fuel consumption and the knock-on environmental effects of this. It has been estimated that reduction in 1 Kg mass of the panel can lead to a saving of 1.5 to 2.million Euros based on today’s fuel prices. The project also pin-points the safety implications which must be taken into account when superseding already advanced aerospace composite materials.
"Evolutionary methods for generating hierarchical and multi-label classifiers" funded by Santander (PI)Santander Doctoral Student Award
"Copyright protection and forensics bootleg museum images" funded by EPSRC CASE (PI)Machine learning or pattern matching problem consists of two parts. Firstly, a set of features or statistics must be extracted from the object. The aim is to select features which include as much information relevant to the problem as possible, by avoiding unnecessary features. The second part is the classifier, like a support vector machine or artificial neural network. We will invest most of the time on feature extraction, because the features must be tailored to our particular problem of recognition. If the features are well-chosen, any classifier should be able to demonstrate some positive effect. Further work on the classifier design may improve results if the features are well-chosen, but may have no effect if they are properly not.
AI-assisted Automatic Dental Disease Detection with Radiography funded by EPSRC Impact Acceleration Account (IAA) Projects Fund (PI:Yunpeng Li, Co-I: Yaochu Jin)The purpose aims to build a mobile phone app that empowers smartphones with Artificial Intelligence (AI) capability in firstly, correcting dental radiographic images to reduce errors for the viewer or prescriber, and secondly recognising normal anatomical structures and differentiate from subtle abnormalities. This project will provide a proof-of-concept study to incorporate AI into mobile devices to serve as a complementary method to help identify and classify dental diseases from digital radiographic images by improving the accuracy and diagnostic outcome
"Efficient Evolutionary Neural Architecture Search for Human Face and Shape Recognition" funded by industry (PI)This project aims to develop computationally efficient, scalable, and powerful neural architecture search methods that are able to automatically generate deep neural network models best suited for a given problem at hand, in particular for human face and shape recognition.
"Bayesian evolutionary optimization for electric drive" funded by Bosch (PI)This project aims to investigate the application of Bayesian optimization techniques to electric drive optimization with many objectives having various computational complexities.
Research collaborations
Academic collaborators:
- Dr Spencer Thomas, NPL, UK
- Prof Tianyou Chai, Northeastern University, China
- Prof Kaisa Miettinen, University of Jyvaskyla, Finland
- Dr Mana Mahapatra, The Pirbright Institute
- Prof. Colin A. Smith and Dr Emma Laing, Department of Biological Sciences
- Prof. Matthew Leach, CES
- Prof. Soon-Thiam Khu, CES
- John Doherty, MES.
Industrial collaborators:
- Huawei Research Institute, Finland
- Bosch, Germany
- Honda R&D Europe, Germany
- The National Physical Laboratory, UK
- The Pirbright Institute, UK
- Honda Research Institute Europe, Germany
- Valtra, Finland
- Fingrid, Finland
- HR Wallingford, UK
- Bosch Thermotechnology Ltd, UK
- Airbus
- QinetiQ
- Intellas UK Ltd
- Aero Optimal
- Santander.
Indicators of esteem
Best Student Paper Award, IEEE Congress on Evolutionary Computation, June 5-8, 2017, San Sebastian, Spain
Runner-up, Best Student Paper Award, IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
Best Paper Award, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 2-5, 2010, Montreal, Canada
Best Student Paper Award (Student: I. Paenke, Supervisors: J. Branke, Y. Jin), IEEE Symposium on Foundations of Computational Intelligence, April 2007, Hawaii, USA
Main conference activities
- Special Session Chair, 2014 IEEE World Congress on Computational Intelligence, July 6-11, 2014, Beijing, China
- Program Chair, 2013 IEEE Congress on Evolutionary Computation, June 20-23, 2013, Cancu, Mexico
- General Chair, 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 9-12, 2012, San Diego, USA
- Area Co-Chair, FUZZ-IEEE 2011, Taipei, Taiwan, June 27-30, 2011
- Program Co-Chair of International Workshop on Advanced Computational Intelligence, Oct. 19-21, 2011, Wuhan, China
- Industry Liaison, IJCNN 2011, San Jose, California, July 31 - August 5, 2011
- Co-Chair, IEEE Symposium on Computational Intelligence in Multi-Criterion Decision Making (MCDM 2011), part of IEEE Symposium Series on Computational Intelligence, April 11-15, 2011, Paris
- Co-Chair, IEEE Symposium on Computational Intelligence in Industry (CII 2011), part of IEEE Symposium Series on Computational Intelligence, April 11-15, 2011, Paris
- Co-Chair, IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE 2011), part of IEEE Symposium Series on Computational Intelligence, April 11-15, 2011, Paris
- Tutorials and Workshops Co-Chair, CEC 2010, Barcelona, Spain, July 18-23, 2010
- Program Chair-Industry, 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS'09), September, 2009, Istanbul, Turkey
- Program Co-Chair, IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (IEEE MCDM 2009), Part of SSCI 2009, March 30 - April 2, 2009, Nashville, TN, USA
- Tutorial Chair, 2007 IEEE Congress on Evolutionary Computation, Singapore, Sept. 25-28, 2007
- Co-Chair, 2007 IEEE Symposium on Multi-Criteria Decision-Making (IEEE MCDM 2007), Part of SSCI 2007, April 1-5, Honolulu, Hawaii, USA
- Program Chair, The Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'05). Hunan, China, 27-29 August 2005
- Publicity Co-Chair, The Sixth International Conference on Intelligent Systems Design and Applications (ISDA2006), Jinan, China, Oct. 16-18, 2006.
Main professional services
- AdCom Member, IEEE Computational Intelligence Society. Term 2012-2014
- Chair, Intelligent Systems Applications Technical Committee (ISATC), IEEE Computational Intelligence Society (2011 -)
- Management Committee Member, European Cooperation in Science and Technology (COST), Action IC0806: Intelligent Monitoring, Control, and Security of Critical Infrastructure Systems (2010)
- Chair, Industrial Liaison Subcommittee, IEEE Computational Intelligence Society (2010)
- Chair, Continuing Education Sub-Committee, IEEE Computational Intelligence Society (2009-2010)
- Member, Award Sub-Committee for Outstanding PhD Dissertation Award, IEEE Computational Intelligence Society (2009)
- Member, Evolutionary Computation Technical Committee, IEEE Computational Intelligence Society (2007 - )
- Member, Emergent Technologies Technical Committee, IEEE Computational Intelligence Society (2007 - 2010)
- Founding Chair, Task Force on Evolutionary Computation in Dynamic and Uncertain Environments, Evolutionary Computation Technical Committee, IEEE Computational Intelligence Society (2004 - 2010).
Keynotes and invited talks
Invited plenary / keynote talks and invited tutorials
- Invited Keynote, “Scalable Model based Evolutionary Multi-objective Optimization”, 7th Joint International Conference on Computational Intelligence, Lisbon, Portugal, 12-14 November, 2015
- Invited Keynote, “Evolutionary optimization of complex systems in uncertain environments”, The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT) , June 30 - July 3 2015, Gijón, Asturias, Spain
- Invited Keynote, "Towards large-scale bio-inspired robot swarms", The 5th Joint International Conference on Swarm, Evolutionary and Memetic Computing", December 18-20, 2014, Bhubaneswar, Odisha, India
- Invited Keynote, "Social and cellular swarm intelligence for scalable optimisation and swarm robot pattern formation", The 5th International Conference on Swarm Intelligence, October 17-19, 2014, Hefei, China
- Invited Keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", 20th International Conference on Soft Computing (MENDEL'14), June 25-27, Brno, Czech Republic
- Invited Keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", The 19th International Conference on Automation and Computing, September 13-14, 2013, Uxbridge, UK
- Invited Keynote, "Evolutionary dynamic optimization: To track or not to track, and how to track?" IEEE Symposium Series on Computational Intelligence, April 16-19 2013, Singapore
- Invited summer school course, "Evolutionary optimisation of expensive problems." 22nd Jyvaskyla Summer School, University of Jyvaskyla, Finland, 13-17 August 2012
- Invited Keynote, 10th Workshop on Bioinformatics and 5th Symposium of the Polish Bioinformatics Society, 25 - 27 May 2012, Gdańsk, Poland
- Invited keynote, "Surrogate-assisted evolutionary optimization: Past, present and future", Learning and Intelligent Optimization Conference (LION 6), January 16-20, 2011, Paris, France
- Invited keynote, "Morphogenetic self-organization of swarm robotic systems for robust boundary coverage and target tracking", The 7th International Conference on Computational Intelligence and Security, December 3-4, 2011, Sanya, Hainan, China
- Invited keynote, "Self-organisation of neural systems - An evolutionary and developmental perspective", DeveLeaNN Workshop, October 27-28, 2011, Paris, France
- Invited Keynote, "Computational modelling, analysis and synthesis of gene regulatory networks", Workshop on Computational Methods in Bioinformatics, October 19, 2011, Salerno, Italy
- Invited keynote, "Morphogenetic self-organization of collective systems. Organic Computing Workshop, The 8th International Conference on Autonomic Computing, Karlsruhe, Germany, June 14-18, 2011
- Invited tutorial, "A systems approach to aerodynamic design optimization", Learning and Intelligent OptimizatioN (LION 5), Jan. 17-21, 2011, Rome, Italy
- Plenary talk, "Morphogenetic robotics", World Congress on Nature and Biologically Inspired Computing, Kitakyushu, Japan, December 15-17, 2010
- Plenary talk, "Analysis and Synthesis of Gene Regulatory Networks and Their Application to Morphogenetic Robotics", International Conference on Computational Systems Biology and Bioinformatics, Bangkok, Thailand, November 4-5, 2010
- Plenary talk, "Multi-objective machine learning", The 2010 International Workshop on Nature Inspired Computation and Application , October 23-27, 2010, Hefei, China
- Keynote talk, "A fitness-independent evolvability measure for evolutionary developmental systems", 7th International Symposium on Networks in Bioinformatics, Amsterdam, the Netherlands, April 22-23, 2010
- Semi-plenary talk, "Computational modelling of gene regulatory networks: Analysis, synthesis and applications", 15th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP 2008), November 25-28, 2008, Auckland, New Zealand
- Keynote talk, "Efficient evolutionary algorithms for complex engineering design", Adaptive Computing in Design and Manufacturing, April 29th-30th 2008, Bristol, UK
- Keynote talk, "Pareto-optimality is everywhere: From engineering design, machine learning to biological systems", Genetic and Evolving Fuzzy Systems, 4 - 7 March, 2008, Witten-Bommerholz, Germany
- Plenary talk, "Pareto-based multi-objective machine learning", Hybrid Intelligent Systems, Sept. 17-19, 2007, Kaiserslautern, Germany.
Other selected invited talks
- Invited Seminar, "Evolution of gene regulated cellular growth models for morphological development", Department of Computer Science, University of Oxford, January 31, 2014
- Invited Seminar, "A systems approach to evolutionary optimisation of complex engineering problems.", Department of Mathematical Information technology , University of Jyvaskyla, Finland, 16.08.2012
- Invited talk, "Morphogenetic self-organisation of robotic systems." Social Robotics lab, National University of Singapore, 05.06.2012
- Invited talk, "Modeling activity-dependent neural plasticity in liquid state machines for spatiotemporal pattern recognition." School of Computer Engineering, Nanyang Technological University, Singapore, 03.06.2012
- Invited speech, Biology + Computing = ?? A Joint Meeting of the CSE:SEABIS Group and the ModAbs Group, Sponsored by SICSA, University of Stirling, UK, 21st May 2012
- Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", School of Computing, Robert Gordon University, 24 February, 2012
- Invited seminar, Department of Information Systems and Computing, Brunel University, 22 February, 2012
- Invited talk, "Morphogenetic robotics", Robot Intelligence Technology Lab, KAIST, Republic of Korea, December 16, 2011
- Invitd talk, "Morphogenetic robotics", College of Engineering, Seoul National University, Republic of Korea, December 15, 2011
- Invited talk, "Modeling neural plasticity for human behaviour recognition", School of Computer Science, Nanjing University, April 26, 2011
- Invited talk, "Dynamicalization - Manipulated Changes of Constraints for Efficient Optimization of Constrained Problems", Bridging The Gap: Workshop 7, Dynamic Optimisation in an Uncertain World: Challenges and State-of-the-Art , University of Birmingham, 24th February, 2011
- Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", The Centre for Computational Statistics and Machine Learning, University College London, January 27, 2011
- Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", Department of Control Science and Engineering, Huazhong University of Science and Technology, 31st December, 2010
- Invited talk, "A systems approach to multi-objective optimization of complex systems", Department of Automation, Tsinghua University, 29th December, 2010
- Invited talk, "Analysis, synthesis and applications of gene regulatory networks models", School of Engineering, Mathematics and Physical Sciences, University of Exeter, 10th November, 2010
- Invited talk, International Workshop on Nature Inspired Computation and Applications, Oct. 23-27, 2010, Hefei, China
- Invited speaker, EU ICT FET Action Workshop on EVOBODY: new Principles of Unbound Embodied Evolution. Sept. 23, 2010, Malta
- Invited talk, "Morphogenetic self-organization of collective systems", COST Action IC0806: Intelligent Monitoring, Control and Security of Critical Infrastructure Systems, Second Action Workshop, May 17-18, 2010, Budapest, Hungary
- Invited talk, "Analysis and synthesis of gene regulatory networks and their application to morphogenetic robotics", Laboratory for Systems Theory and Automatic Control, Otto-von-Guericke University of Magdeburg, January 26, 2010
- Invited talk, "Evolutionary multi-objective optimization of expensive problems using surrogate ensembles", Special Session on "Evolutionary Multi-Objective Optimization" organized by J. Branke, the 23rd European Conference on Operational Research, July 6-8 2009, Bonn, Germany
- Invited talk, "Analysis, synthesis and applications of gene regulatory network", Colloquium, Faculty of Science, University of Amsterdam, February 13, 2009
- Invited talk, "Brain-body co-evolution toward understanding major transitions in evolution of primitive nervous systems", INNS-NNN Symposia (New directions in Neural Networks) on Modelling the Brain and Nervous Systems, 24-25 November 2008, Auckland, NZ
- Invited talk, "Pareto analysis of evolutionary and learning systems", The 2008 International Workshop on Nature Inspired Computation and Applications, May 27-29,2008, Hefei, China
- Invited talk (together with B. Sendhoff), "Towards multi-objective system optimization", EMO 2007, March 8, Matsushima, Japan
- Invited talk, "Scalable model-based multi-objective optimization", Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Dec. 13-17, 2006, Schloss Dagstuhl, Wadern, Germany
- Invited talk, "Modeling regularity in multi-objective optimization", PPSN Workshop on Multi-Objective problem Solving from Nature, Sep. 9, 2006, Reykjavik
- Invited talk, "Multi-objective machine learning", School of Computer Science, University of Birmingham, February 18, 2006
- Invited talk, "Research on evolution and learning at HRI-EU", Kanpur Genetic Algorithm Lab , Indian Institute of Technology, Kanpur, India, July 6, 2005
- Invited talk on "Hybrid representations for evolutionary multi-objective optimization", Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Schloss Dagstuhl, Germany, Nov. 8-12, 2004
- Invited talk, "Aerodynamic optimization using evolutionary algorithms", Track on EC in Industry, GECCO'04, Seattle, July 2004
- Invited talk on "Ein auf evolutionaerer Mehrzieloptimierung basierender Ansatz zur Regularisierung neuronaler Netze" (A method for neural network regularization based on evolutionary multi-objective optimization), Fachbereich Informatik, Lehrstuhl Systemanalyse (Prof. Dr. Hans-Paul Schwefel), University of Dortmund, Germany, March 1, 2004
- Invited talk on "Rethinking multi-objective evolutionary algorithms", Dagstuhl Seminar on Theory of Evolutionary Algorithms, Schloss Dagstuhl, Germany, Feb. 15-20, 2004
- Invited talk on "Dynamic weighted aggregation: from multi-objective optimization to dynamic optimum tracking". AIFB, University of Karlsruhe, Karlsruhe, Germany, Nov. 28, 2003
- Invited talk on "Evolutionary multi-objective optimization: Methods, analysis and applications". The Industrial Engineering and Management Department, Yuan-Ze University, Chung-Li, Taiwan, ROC, Nov. 4-10, 2002.
Research interests
- Evolutionary optimisation
- Data driven evolutionary optimization
- Surrogate-assisted evolutionary optimization and Bayesian optimization, transfer optimization
- Robust and dynamic optimization, robustness over time, optimization in the presence of uncertainty
- Multi-objective and many-objective optimization
- Large-scale optimization, federated optimization
- Machine learning
- Deep learning, automated machine learning, neural architecture search
- Secure and trustworthy machine learning, adversarial machine learning, privacy-preserving federated learning, learning over encrypted data
- Evolutionary machine learning, multi-objective learning
- Real world applications include:
- Design optimization and control of complex systems, e.g., high-lift wing systems, fuselage of aircraft, turbine engines and vehicles, hybrid and electrical vehicles;
- Process optimization and control, including steel-making and continuous casting, and control of multi-level carbon fibre stretching processes; electric power transmission systems
- Image identification, face recognition and human behaviour detection
- Healthcare, bioinformatics and fintech
My science-driven research interests lie in interdisciplinary areas that bridge the gap between computational intelligence and machine learning, computational neuroscience, and computational biology. My current main topics include
- Evolutionary developmental systems (neural and morphological development, gene regulatory networks, brain-body co-evolution)
- Computational modelling of neural plasticity (computational modelling of plasticity, gene regulated plasticity in reservoir computing such as echo-state networks and liquid state machines)
- Morphogenetic robotics, including morphogenetic swarm and reconfigurable modular robotics.
Research projects
The objective of this collaboration is to apply evolutionary optimization strategies to the multi-objective optimization of federated recommendation system with minimal effect on the user’s experience of the mobile device.
Bayesian approaches to the optimization of complex systems have attracted much research in recent years and have achieved encouraging success. The project has mainly two aims: 1) Develop new training algorithms and new optimization methods that can deal with very low amount of training data for surrogate models and optimization evaluations. 2) Develop new infill criteria for Bayesian approaches to optimisation which integrate multiple models for estimating different criteria of a multi-objective problem or constraints.
In this project, we study multi-source side information fusion assisted Bayesian optimization models and algorithms. The aim of this study is to fully exploit the side information to reduce the number of computational times of expensive fitness functions, and, meanwhile, to accurately construct response surface in the parameter space for effectively searching and recognizing the global optimum.
The project aims to improve digital development process for vehicle dynamics in the light of efficient many-objective optimization and smart visualization.
FAPESP SPRINT, Surrey-PI, PI: Dr Ricardo Cerri, UFSCar, Brazil
This project aims to develop new and innovative machine learning algorithms to analyse the data from the new 3D OrbiSIMS instrument (mass spectrometry) in a time and memory efficient manner. Current techniques limit the volume of data that can be analysed, and currently there are no methods to integrate the different modalities produced by the instrument. The 3D OrbiSIMS is the first of its kind and is involved in a large number of projects relating to antimicrobial resistance, cancer research, and material characterisation. The project offers a unique opportunity for candidates to contribute to a wide range of disciplines and impact a broad scientific base.
This project investigates the current state of the art methods and algorithms relevant for decision making support systems. Focus points of the investigation are multi- and many-objective evolutionary optimization methods as well as non-evolutionary MCDM methods and methods from portfolio management in relation to decision making support systems in which user of a system are supported in the task of selecting solutions from a numerically identified Pareto front.
This research proposal aims to permit the application of evolutionary algorithms, a class of global search metaheuristics, to fluid dynamic optimisation of highly complex industrial systems by exploiting surrogate models and modern machine learning techniques.
Finland Distinguished Professor
This project aims to use gene regulatory networks and morphogen gradients governing the biological development process for self-organizing large-scale swarm robots that can autonomously generating patterns for following and surrounding moving targets.
This project aims to address the main challenges in evolutionary many-objective optimisation using model-based techniques and surrogate-assisted evolutionary optimisation.
This project takes a detailed look at the design and use of materials in the aerospace industry, and will deliver a fully designed structure for use in aircraft design, and joins up a number of key themes in weight reduction, namely a reduction of fuel consumption and the knock-on environmental effects of this. It has been estimated that reduction in 1 Kg mass of the panel can lead to a saving of 1.5 to 2.million Euros based on today’s fuel prices. The project also pin-points the safety implications which must be taken into account when superseding already advanced aerospace composite materials.
Santander Doctoral Student Award
Machine learning or pattern matching problem consists of two parts. Firstly, a set of features or statistics must be extracted from the object. The aim is to select features which include as much information relevant to the problem as possible, by avoiding unnecessary features. The second part is the classifier, like a support vector machine or artificial neural network. We will invest most of the time on feature extraction, because the features must be tailored to our particular problem of recognition. If the features are well-chosen, any classifier should be able to demonstrate some positive effect. Further work on the classifier design may improve results if the features are well-chosen, but may have no effect if they are properly not.
The purpose aims to build a mobile phone app that empowers smartphones with Artificial Intelligence (AI) capability in firstly, correcting dental radiographic images to reduce errors for the viewer or prescriber, and secondly recognising normal anatomical structures and differentiate from subtle abnormalities. This project will provide a proof-of-concept study to incorporate AI into mobile devices to serve as a complementary method to help identify and classify dental diseases from digital radiographic images by improving the accuracy and diagnostic outcome
This project aims to develop computationally efficient, scalable, and powerful neural architecture search methods that are able to automatically generate deep neural network models best suited for a given problem at hand, in particular for human face and shape recognition.
This project aims to investigate the application of Bayesian optimization techniques to electric drive optimization with many objectives having various computational complexities.
Research collaborations
Academic collaborators:
- Dr Spencer Thomas, NPL, UK
- Prof Tianyou Chai, Northeastern University, China
- Prof Kaisa Miettinen, University of Jyvaskyla, Finland
- Dr Mana Mahapatra, The Pirbright Institute
- Prof. Colin A. Smith and Dr Emma Laing, Department of Biological Sciences
- Prof. Matthew Leach, CES
- Prof. Soon-Thiam Khu, CES
- John Doherty, MES.
Industrial collaborators:
- Huawei Research Institute, Finland
- Bosch, Germany
- Honda R&D Europe, Germany
- The National Physical Laboratory, UK
- The Pirbright Institute, UK
- Honda Research Institute Europe, Germany
- Valtra, Finland
- Fingrid, Finland
- HR Wallingford, UK
- Bosch Thermotechnology Ltd, UK
- Airbus
- QinetiQ
- Intellas UK Ltd
- Aero Optimal
- Santander.
Indicators of esteem
Best Student Paper Award, IEEE Congress on Evolutionary Computation, June 5-8, 2017, San Sebastian, Spain
Runner-up, Best Student Paper Award, IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
Best Paper Award, 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 2-5, 2010, Montreal, Canada
Best Student Paper Award (Student: I. Paenke, Supervisors: J. Branke, Y. Jin), IEEE Symposium on Foundations of Computational Intelligence, April 2007, Hawaii, USA
Main conference activities
- Special Session Chair, 2014 IEEE World Congress on Computational Intelligence, July 6-11, 2014, Beijing, China
- Program Chair, 2013 IEEE Congress on Evolutionary Computation, June 20-23, 2013, Cancu, Mexico
- General Chair, 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, May 9-12, 2012, San Diego, USA
- Area Co-Chair, FUZZ-IEEE 2011, Taipei, Taiwan, June 27-30, 2011
- Program Co-Chair of International Workshop on Advanced Computational Intelligence, Oct. 19-21, 2011, Wuhan, China
- Industry Liaison, IJCNN 2011, San Jose, California, July 31 - August 5, 2011
- Co-Chair, IEEE Symposium on Computational Intelligence in Multi-Criterion Decision Making (MCDM 2011), part of IEEE Symposium Series on Computational Intelligence, April 11-15, 2011, Paris
- Co-Chair, IEEE Symposium on Computational Intelligence in Industry (CII 2011), part of IEEE Symposium Series on Computational Intelligence, April 11-15, 2011, Paris
- Co-Chair, IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE 2011), part of IEEE Symposium Series on Computational Intelligence, April 11-15, 2011, Paris
- Tutorials and Workshops Co-Chair, CEC 2010, Barcelona, Spain, July 18-23, 2010
- Program Chair-Industry, 2nd IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS'09), September, 2009, Istanbul, Turkey
- Program Co-Chair, IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (IEEE MCDM 2009), Part of SSCI 2009, March 30 - April 2, 2009, Nashville, TN, USA
- Tutorial Chair, 2007 IEEE Congress on Evolutionary Computation, Singapore, Sept. 25-28, 2007
- Co-Chair, 2007 IEEE Symposium on Multi-Criteria Decision-Making (IEEE MCDM 2007), Part of SSCI 2007, April 1-5, Honolulu, Hawaii, USA
- Program Chair, The Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'05). Hunan, China, 27-29 August 2005
- Publicity Co-Chair, The Sixth International Conference on Intelligent Systems Design and Applications (ISDA2006), Jinan, China, Oct. 16-18, 2006.
Main professional services
- AdCom Member, IEEE Computational Intelligence Society. Term 2012-2014
- Chair, Intelligent Systems Applications Technical Committee (ISATC), IEEE Computational Intelligence Society (2011 -)
- Management Committee Member, European Cooperation in Science and Technology (COST), Action IC0806: Intelligent Monitoring, Control, and Security of Critical Infrastructure Systems (2010)
- Chair, Industrial Liaison Subcommittee, IEEE Computational Intelligence Society (2010)
- Chair, Continuing Education Sub-Committee, IEEE Computational Intelligence Society (2009-2010)
- Member, Award Sub-Committee for Outstanding PhD Dissertation Award, IEEE Computational Intelligence Society (2009)
- Member, Evolutionary Computation Technical Committee, IEEE Computational Intelligence Society (2007 - )
- Member, Emergent Technologies Technical Committee, IEEE Computational Intelligence Society (2007 - 2010)
- Founding Chair, Task Force on Evolutionary Computation in Dynamic and Uncertain Environments, Evolutionary Computation Technical Committee, IEEE Computational Intelligence Society (2004 - 2010).
Keynotes and invited talks
Invited plenary / keynote talks and invited tutorials
- Invited Keynote, “Scalable Model based Evolutionary Multi-objective Optimization”, 7th Joint International Conference on Computational Intelligence, Lisbon, Portugal, 12-14 November, 2015
- Invited Keynote, “Evolutionary optimization of complex systems in uncertain environments”, The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT) , June 30 - July 3 2015, Gijón, Asturias, Spain
- Invited Keynote, "Towards large-scale bio-inspired robot swarms", The 5th Joint International Conference on Swarm, Evolutionary and Memetic Computing", December 18-20, 2014, Bhubaneswar, Odisha, India
- Invited Keynote, "Social and cellular swarm intelligence for scalable optimisation and swarm robot pattern formation", The 5th International Conference on Swarm Intelligence, October 17-19, 2014, Hefei, China
- Invited Keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", 20th International Conference on Soft Computing (MENDEL'14), June 25-27, Brno, Czech Republic
- Invited Keynote, "Morphogenetic self-organisation of swarm robots for adaptive pattern formation", The 19th International Conference on Automation and Computing, September 13-14, 2013, Uxbridge, UK
- Invited Keynote, "Evolutionary dynamic optimization: To track or not to track, and how to track?" IEEE Symposium Series on Computational Intelligence, April 16-19 2013, Singapore
- Invited summer school course, "Evolutionary optimisation of expensive problems." 22nd Jyvaskyla Summer School, University of Jyvaskyla, Finland, 13-17 August 2012
- Invited Keynote, 10th Workshop on Bioinformatics and 5th Symposium of the Polish Bioinformatics Society, 25 - 27 May 2012, Gdańsk, Poland
- Invited keynote, "Surrogate-assisted evolutionary optimization: Past, present and future", Learning and Intelligent Optimization Conference (LION 6), January 16-20, 2011, Paris, France
- Invited keynote, "Morphogenetic self-organization of swarm robotic systems for robust boundary coverage and target tracking", The 7th International Conference on Computational Intelligence and Security, December 3-4, 2011, Sanya, Hainan, China
- Invited keynote, "Self-organisation of neural systems - An evolutionary and developmental perspective", DeveLeaNN Workshop, October 27-28, 2011, Paris, France
- Invited Keynote, "Computational modelling, analysis and synthesis of gene regulatory networks", Workshop on Computational Methods in Bioinformatics, October 19, 2011, Salerno, Italy
- Invited keynote, "Morphogenetic self-organization of collective systems. Organic Computing Workshop, The 8th International Conference on Autonomic Computing, Karlsruhe, Germany, June 14-18, 2011
- Invited tutorial, "A systems approach to aerodynamic design optimization", Learning and Intelligent OptimizatioN (LION 5), Jan. 17-21, 2011, Rome, Italy
- Plenary talk, "Morphogenetic robotics", World Congress on Nature and Biologically Inspired Computing, Kitakyushu, Japan, December 15-17, 2010
- Plenary talk, "Analysis and Synthesis of Gene Regulatory Networks and Their Application to Morphogenetic Robotics", International Conference on Computational Systems Biology and Bioinformatics, Bangkok, Thailand, November 4-5, 2010
- Plenary talk, "Multi-objective machine learning", The 2010 International Workshop on Nature Inspired Computation and Application , October 23-27, 2010, Hefei, China
- Keynote talk, "A fitness-independent evolvability measure for evolutionary developmental systems", 7th International Symposium on Networks in Bioinformatics, Amsterdam, the Netherlands, April 22-23, 2010
- Semi-plenary talk, "Computational modelling of gene regulatory networks: Analysis, synthesis and applications", 15th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP 2008), November 25-28, 2008, Auckland, New Zealand
- Keynote talk, "Efficient evolutionary algorithms for complex engineering design", Adaptive Computing in Design and Manufacturing, April 29th-30th 2008, Bristol, UK
- Keynote talk, "Pareto-optimality is everywhere: From engineering design, machine learning to biological systems", Genetic and Evolving Fuzzy Systems, 4 - 7 March, 2008, Witten-Bommerholz, Germany
- Plenary talk, "Pareto-based multi-objective machine learning", Hybrid Intelligent Systems, Sept. 17-19, 2007, Kaiserslautern, Germany.
Other selected invited talks
- Invited Seminar, "Evolution of gene regulated cellular growth models for morphological development", Department of Computer Science, University of Oxford, January 31, 2014
- Invited Seminar, "A systems approach to evolutionary optimisation of complex engineering problems.", Department of Mathematical Information technology , University of Jyvaskyla, Finland, 16.08.2012
- Invited talk, "Morphogenetic self-organisation of robotic systems." Social Robotics lab, National University of Singapore, 05.06.2012
- Invited talk, "Modeling activity-dependent neural plasticity in liquid state machines for spatiotemporal pattern recognition." School of Computer Engineering, Nanyang Technological University, Singapore, 03.06.2012
- Invited speech, Biology + Computing = ?? A Joint Meeting of the CSE:SEABIS Group and the ModAbs Group, Sponsored by SICSA, University of Stirling, UK, 21st May 2012
- Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", School of Computing, Robert Gordon University, 24 February, 2012
- Invited seminar, Department of Information Systems and Computing, Brunel University, 22 February, 2012
- Invited talk, "Morphogenetic robotics", Robot Intelligence Technology Lab, KAIST, Republic of Korea, December 16, 2011
- Invitd talk, "Morphogenetic robotics", College of Engineering, Seoul National University, Republic of Korea, December 15, 2011
- Invited talk, "Modeling neural plasticity for human behaviour recognition", School of Computer Science, Nanjing University, April 26, 2011
- Invited talk, "Dynamicalization - Manipulated Changes of Constraints for Efficient Optimization of Constrained Problems", Bridging The Gap: Workshop 7, Dynamic Optimisation in an Uncertain World: Challenges and State-of-the-Art , University of Birmingham, 24th February, 2011
- Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", The Centre for Computational Statistics and Machine Learning, University College London, January 27, 2011
- Invited talk, "Self-organization of neural systems - An evolutionary and developmental perspective", Department of Control Science and Engineering, Huazhong University of Science and Technology, 31st December, 2010
- Invited talk, "A systems approach to multi-objective optimization of complex systems", Department of Automation, Tsinghua University, 29th December, 2010
- Invited talk, "Analysis, synthesis and applications of gene regulatory networks models", School of Engineering, Mathematics and Physical Sciences, University of Exeter, 10th November, 2010
- Invited talk, International Workshop on Nature Inspired Computation and Applications, Oct. 23-27, 2010, Hefei, China
- Invited speaker, EU ICT FET Action Workshop on EVOBODY: new Principles of Unbound Embodied Evolution. Sept. 23, 2010, Malta
- Invited talk, "Morphogenetic self-organization of collective systems", COST Action IC0806: Intelligent Monitoring, Control and Security of Critical Infrastructure Systems, Second Action Workshop, May 17-18, 2010, Budapest, Hungary
- Invited talk, "Analysis and synthesis of gene regulatory networks and their application to morphogenetic robotics", Laboratory for Systems Theory and Automatic Control, Otto-von-Guericke University of Magdeburg, January 26, 2010
- Invited talk, "Evolutionary multi-objective optimization of expensive problems using surrogate ensembles", Special Session on "Evolutionary Multi-Objective Optimization" organized by J. Branke, the 23rd European Conference on Operational Research, July 6-8 2009, Bonn, Germany
- Invited talk, "Analysis, synthesis and applications of gene regulatory network", Colloquium, Faculty of Science, University of Amsterdam, February 13, 2009
- Invited talk, "Brain-body co-evolution toward understanding major transitions in evolution of primitive nervous systems", INNS-NNN Symposia (New directions in Neural Networks) on Modelling the Brain and Nervous Systems, 24-25 November 2008, Auckland, NZ
- Invited talk, "Pareto analysis of evolutionary and learning systems", The 2008 International Workshop on Nature Inspired Computation and Applications, May 27-29,2008, Hefei, China
- Invited talk (together with B. Sendhoff), "Towards multi-objective system optimization", EMO 2007, March 8, Matsushima, Japan
- Invited talk, "Scalable model-based multi-objective optimization", Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Dec. 13-17, 2006, Schloss Dagstuhl, Wadern, Germany
- Invited talk, "Modeling regularity in multi-objective optimization", PPSN Workshop on Multi-Objective problem Solving from Nature, Sep. 9, 2006, Reykjavik
- Invited talk, "Multi-objective machine learning", School of Computer Science, University of Birmingham, February 18, 2006
- Invited talk, "Research on evolution and learning at HRI-EU", Kanpur Genetic Algorithm Lab , Indian Institute of Technology, Kanpur, India, July 6, 2005
- Invited talk on "Hybrid representations for evolutionary multi-objective optimization", Dagstuhl Seminar on Practical Approaches to Multi-objective Optimization, Schloss Dagstuhl, Germany, Nov. 8-12, 2004
- Invited talk, "Aerodynamic optimization using evolutionary algorithms", Track on EC in Industry, GECCO'04, Seattle, July 2004
- Invited talk on "Ein auf evolutionaerer Mehrzieloptimierung basierender Ansatz zur Regularisierung neuronaler Netze" (A method for neural network regularization based on evolutionary multi-objective optimization), Fachbereich Informatik, Lehrstuhl Systemanalyse (Prof. Dr. Hans-Paul Schwefel), University of Dortmund, Germany, March 1, 2004
- Invited talk on "Rethinking multi-objective evolutionary algorithms", Dagstuhl Seminar on Theory of Evolutionary Algorithms, Schloss Dagstuhl, Germany, Feb. 15-20, 2004
- Invited talk on "Dynamic weighted aggregation: from multi-objective optimization to dynamic optimum tracking". AIFB, University of Karlsruhe, Karlsruhe, Germany, Nov. 28, 2003
- Invited talk on "Evolutionary multi-objective optimization: Methods, analysis and applications". The Industrial Engineering and Management Department, Yuan-Ze University, Chung-Li, Taiwan, ROC, Nov. 4-10, 2002.
Supervision
Postgraduate research supervision
PhD students (principal supervisor)
- Shiqing Liu (01.2020 - ) "Efficient Evolutionary Neural Architecture Search for Human Face and Shape Recognition", funded by Ulucu, China
- Guoyang Xie (10.2019 - ), "Neural Architecture Search for Secure Machine Learning", joint PhD program with SusTec, China
- Xilu Wang (01.2019 - ), Topic: "Evolutionary Bayesian many-objective optimization", funded by Honda Research Institute Europe
- Jia Liu (08.2018 - ), Topic: "Evolutionary optimization for interpretable and robust deep learning", funded by the Department of Computer Science
- Foivos Ntelemis (07.2018 - ), Topic: "Deep learning for mass spectrometry imaging", funded by EPSRC iCASE
- Qiqi Liu (04.2018 - ), Topic: "Evolutionary many-objective optimization of vehicle dynamics", funded by Honda R&D Europe
- Hangyu Zhu (04.2018 - ), Topic: "Evolutionary federated machine learning".
Academic visitors and visiting PhD students
- Zhigang Ren, Xi'an Jiaotong University
- Yi Wang, Northwest University
- Mengxuan Zhang, XiDian University.
Graduated PhD students (since 06/2010)
- Dr Guo Yu (10.2016 - 04.2020)
- Dr Ataollah Ramezan Shirazi (07.2013 - 09.2017), currently a Research Associate at University of Hertfordshire
- Dr Shenkai Gu (10.2011 - 07.2016) , currently a Lecturer at Nanjing University of Science and Technology
- Dr Tameera Rahman (10.2011 - 07.2016)
- Dr Ran Cheng (01.2013 - 04/2016), currently an Assistant Professor at Southern University of Science and Technology, Shenzhen, China
- Dr Joseph Chrol-Cannon (07.2011 - 06.2015)
- Dr Christopher Smith (04.2011 - 03.2015), Principal CAE at McLaren Automotive Ltd
- Dr Wissam Albukhanajer (01.2011 - 03.2015), currently a Consultant Engineer with Roke Manor Research Limited
- Dr Spencer Thomas (04.2011 - 06.2014), currently a Senior Research Scientist National Physical Laboratory, UK.
Supervised postdocs
- Dr Handing Wang (2015 - 2018), currently a Full Professor at XiDian University
- Dr Chaoli Sun (2014 - 2016), currently a Full Professor at Taiyuan University of Science and Technology
- Dr Hyondong Oh (2013 - 2014), currently an Associate Professor at Ulsan National Institute of Science and Technology
- Daniel Bush (2010 - 2011), currently a Research Associate at UCL.
Past members
- Lianbo Ma, Academic visitor, Northeastern University (2020)
- Shuai Wang, Visiting PhD student, XiDian University (2018-19)
- Xinjie Wang, Visiting PhD student, Donghua University (2019)
- Weifeng Zhang, Academic visitor, Huanan Agriculture University (2018-2019)
- Bei Dong, Academic visitor, Shannxi Normal University (2018-2019)
- Dong Han, Visiting PhD student, ECUST (2019)
- Simin Mo, Academic visitor, Taiyuan University of Science and Technology (02.2017 - 01.2018)
- Yuhong Jiang, Visiting PhD student, China University of GeoScience(Wuhan) (10.2017 - 10.2018)
- Yang Chen, Visiting PhD student, China University of Mining Technology (09.2017 - 09.2018)
- Yu Chen, Academic visitor, Wuhan University of Science and Technology, China (08.2017 - 07.2018)
- Handing Wang, Postdoctoral Research Fellow. Funded by EPSRC (07/2015 - 07/2018)
- Yixin Yang, Visiting PhD student, Chinese Academy of Sciences, China (03.2017 - 08.2017)
- Tian Ye, Visiting PhD student, Anhui University, China (10/2016 - 03/2017)
- Cheng He, Visiting PhD stundent, Huazhong University of Technology, China (10/2016 - 03/2017)
- Prof Luochen Liu, Academic visitor, XiDian University China (02/2016 - 02/2017)
- Prof Xiangtao Li, Academic visitor, Northeastern Normal University, China (11/2015 - 11/2016)
- Joseph Chrol-Cannon, Postdoctoral Research Fellow. (07/2015 -07.2016)
- Chaoli Sun, Postdoctoral Research Fellow. (09/2014 -09.2016)
- Jingnan Shen, Visiting PhD student, Tsinghua University, China (10.2016 - 04.2016)
- Prof Ufuk Yolcu, Ankara University, Turkey (09.2015- 08.2016)
- Dr Ran Cheng, PhD student, graduated in March 2016, currently a postdoctoral researcher at University of Birmingham (01.2013 - 03.2016)
- Murillo Carneiro, University of Sao Paulo, Brazil
- Prof Xingguang Peng, Northwestern Polytechnical University, China
- Prof Zhenping Xie, Jiangnan University, China (08.2014-08.2015)
- Prof Songdong Xue, Taiyuan University of Science and Technology, China(10.2014-09/2015)
- Dr Christopher Smith, PhD student, graduated in March 2015 and is now working at McLarens(03/2011 -03/2015)
- Dr Wissam Albukhanajer, PhD student, graduated in March 2015, currently a postdoctoral researcher at Surrey Space Centre, University of Surrey (01/2011 -03/2015)
- Prof Yan Wu, Academic Visitor, Xidian University, China (10/2013 - 10/2014)
- Dr Spencer Thomas, PhD student, graduated in June 2014 and worked at the National Physical Laboratory, UK (03/2011 - 06/2014)
- Amiram Moshainov, Academic Visitor, Tel Aviv University, Israel (09/2013 - 08/2014)
- Mr Kaname Narukawa, Academic Visitor, Honda Research Institite Europe, Germany (during 01/2013 - 08/2014)
- Prof Xingyi Zhang, Academic Visitor, Anhui University, China (08/2013 - 08/2014)
- Dr Hyondong Oh, Research Fellow. Funded by EC FP7 SWARM-ORGAN. Currently an Assistant Professor at UNIST, Korea (04/2013 - 08/2014)
- Ms Xin-Lan Liao, Visiting PD student, National Chung Cheng University, Taiwan, R.O.C. (09/2013 - 02/2014)
- Dr Borys Wrobel, Academic visitor, Polish Academy of Sciences and Adam Mickiewicz University in Poznan, Poland (06/2013-08/2013)
- Prof Chaoli Sun,Visiting Academic Researcher, Taiyuan University of Science and Technology, China (10/2012 - 03/2013)
- Ayang Xiao, Visiting PhD student, Harbin Institute of Technology, China (01/2012 - 04/2013)
- Dr Sohrab Saeb, Postdoc Research Fellow (04/2012 - 04/2013)
- Ricardo Cerri, Santander Visiting PhD student, University of Sao Paulo, Brazil (03/2012 -08/2012)
- Dr Colin Bell, KTA Postdoc Research Fellow (09/2011-09/2012)
- Prof. Xiaoyan Sun, Visiting Academic Researcher, China University of Mining and Technology (09/2011 - 02/2012)
- Dr Daniel Bush, Postdoc Research Fellow (11/2010-10.2011)
- Prof. Chuan-Kang Ting, Visiting Academic Researcher, National Chung-Cheng University, Taiwan (07/2011-08/2011)
- Dr M. Govindarajan, Visiting Academic Researcher, Annamalai University, India (05/2011-06/2011).
Postdocs, PhD and MSc / Diplom students co-supervised at Honda (2001-2010)
- Postdoctoral associate, Tobias Luksch, Robust humanoid robot object grasping and manipulation under uncertainty using evolutionary algorithms, In collaboration with Technical University of Kaiserslauten (02/2010 - 05/2010)
- Ph.D. student, Daniel Botman, Genetic and cellular mechanisms for modelling controlled growth. In collaboration with University of Amsterdam, The Netherlands (03/2010 - 05/2010)
- Visiting Ph.D. student, Sanghoun Oh, Evolutionary optimization of multi-modal constrained optimization problems through dynamicalization, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea (08/2009 - 01/2010)
- Ph.D. student, Hongliang Guo, hierarchical gene regulatory network for generating robust emerging behaviours for interacting collective systems. In collaboration with Stevens Institute of Technology, Hoboken, USA (04/2009 - 05/2010)
- Postdoctoral associate, Benjamin Inden, Co-evolution of neural control and body plan for object grasping. In coo-operation with the CoR-Lab Graduate School, Bielefeld University, Germany (06/2008 - 05/2010)
- Ph.D. student, Andrea Finke, Brain-machine interface for Asimo control. In collaboration with the CoR-Lab Graduate School, Bielefeld University, Germany (02/2008 - 05/2010)
- Ph.D. student, Heiko Lex, Cognitive systems in motor adaptation. In collaboration with the CoR-Lab Graduate School, Bielefeld University, Germany (06/2008 - 06/2010)
- Ph.D. student Le-Minh Nghia, Model-based approaches to large-scale, highly constrained multi-objective design optimization. In collaboration with Nanyang Technological University, Singapore (10/2008 - 05/2010)
- Ph.D. student, Lisa Schramm, Co-evolution of nervous systems and morphology. In collaboration with Fachgebiet Regelungstheorie und Robotik, TU Darmstadt, Germany (09/2007 - 05/2010)
- Ph.D. student, Till Steiner, Evolutionary development for system design. In collaboration with Bielefeld University, Germany (09/2006 - 05/2010)
- Ph.D. student, Ben Jones, Major transitions in evolution of primary nervous systems. In collaboration with School of Computer Science, University of Birmingham, UK (completed in 10/2009)
- Ph.D. student, Neale Samways, Co-evolution of functional and regulatory genes in DNA. In collaboration with School of Computer Science, University of Birmingham, UK (completed in 02/2009 )
- Postdoctoral associate, Breanna Studenka, Cognitive planning in manual action. In collaboration with the CoR-Lab Graduate School, Bielefeld University, Germany (completed in 09/2009)
- Diploma student, Christine Becker, Analysis and Modeling of the glycolysis of Saccharomyces cerevisiae. In collaboration with Fachbereich Biologie, TU Darmstadt (completed in 08/2009)
- Master student, Liuquan Yang, Efficient CFD based design optimization using differential recurrent neural networks. In collaboration with Cranfield University, UK (completed in 06/2009)
- Diplom student, Jens Trommler, Evolvability of evolutionary developmental systems, In collaboration with Fachgebiet Regelungstheorie und Robotik, TU Darmstadt, Germany (completed in 02/2009)
- Ph.D. student Dudy Lim, Evolutionary optimization for computationally expensive problems. In collaboration with Nanyang Technological University, Singapore (completed in 11/2008)
- Ph.D. student, Aimin Zhou, Modeling regularity in estimation of distribution algorithms for multi-objective optimization. In collaboration with Department of Computing and Electronics Systems, University of Essex, UK (completed in 12/2008)
- Ph.D. student, Ingo Paenke, Interactions of evolution and learning. In collaboration with Institut für Angewandte Informatik und Formelle Beschreibung (AIFB), University of Karlsruhe (completed in 02/2008)
- Master student, Rob Veldkamp, Evolution and memory. In collaboration with Vrije University of Amsterdam (completed in 10/2007)
- Master student, Michal Kowalczykiewicz, Recurrent neural networks for approximation of computational fluid dynamics (CFD) simulations. In collaboration with School of Engineering, Cranfield University, UK (completed in 05/2007)
- Diplom student, Robin Gruna, Analysis of redundant genotype-phenotype mapping. In collaboration with Institut für Angewandte Informatik und Formelle Beschreibung (AIFB), University of Karlsruhe (completed in 10/2007
- Diplom student, Lisa Schramm, A model for nervous system development controlled by a gene regulatory networks, In collaboration with Fachgebiet Regelungstheorie und Robotik, TU Darmstadt (completed in 09/2007)
- Diplom student, Lars Gräning, Evolutionary multi-objective approach to analysis of ROC of neural classifiers. In collaboration with FG Neuroinformatik und Kognitive Robotik, TU Ilmenau (completed in 01/2006)
- Ph.D. student, Tatsuya Okabe, Evolutionary multi-objective optimization. In collaboration with Technische Fakultät, Universität Bielefeld (completed in 12/2004)
- Diplom student, Ingo Paenke, Evolutionary search for robust solutions. In collaboration with Institut für Angewandte Informatik und Formelle Beschreibung (AIFB), University of Karlsruhe (completed in 05/2004).
Teaching
Teaching
- COMM054: Data Science (shared, 2019-)
- COM2040: Further Programming Paradigms (shared, 2018-2019)
- COM2038: Object-Oriented Programming and C++ (2016 - 2017)
- COM3001: Professional Projects (UG, 2014 -)
- COMM002: MSc Dissertation Coordination (2014 -)
- COM3013: Computational Intelligence (Undergraduate, Autumn semester, 2010 - )
- COM2016: Professional Studies (Undergraduate, Autumn semester, 2011)
- COM2030: Advanced Algorithms (Undergraduate, Autumn semester, shared, 2011)
Publications
My verified Google Scholar Citation Profile: h-index = 65, sum of citations = 18,115 (as of 10.2019)
According to Thomson Reuters ISI Web of Science: h-index = 40, sum of citations = 7,535 (as of 10.2019)
Computer Scientist National and World Ranking according to Guide2Research.
See also Research Gate, Publications Sorted by Year or DBLP Computer Science Bibliography
Authored Books
- Y. Jin. Advanced Fuzzy Systems Design and Applications. Springer, 2003
- Y. Jin and J. Wang. Intelligent Control: Theory and Applications, Henan Science and Technology Publishing House, Zhengzhou, China, 1997 (in Chinese)
Refereed Journal Papers (in English)
- H. Chen, R. Cheng, W. Pedrycz, and Y. Jin. Solving many-objective optimization problems via multistage evolutionary search. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2019 (accepted)
- C. Yang, J. Ding, Y. Jin, and T. Chai. Off-line data-driven multi-objective optimization: Knowledge transfer between surrogates and generation of final solutions. IEEE Transactions on Evolutionary Computation, 2019 (accepted)
- Y. Sun, H. Wang, B. Xue, Y. Jin, G. G. Yen, and M. Zhang. Surrogate-assisted evolutionary deep learning using an end-to-end random forest-based performance predictor. IEEE Transactions on Evolutionary Computation, 2019 (accepted)
- H. Zhu and Y. Jin. Multi-objective evolutionary federated learning. IEEE Transactions on Neural Networks and Learning Systems, 2019 (accepted)
- X. Wang, Y. Jin and K. Hao. Evolving local plasticity rules for synergistic learning in echo state networks. IEEE Transactions on Neural Networks and Learning Systems, 2019 (accepted)
- Y. Tian, X. Zhang, C. Wang, and Y. Jin. An evolutionary algorithm for large-scale sparse multi-objective optimization problems. IEEE Transactions on Evolutionary Computation, 2019 (accepted)
- S. Wang, J. Liu and Y. Jin. Finding influential nodes in multiplex networks using a memetic algorithm. IEEE Transactions on Cybernetics, 2019 (accepted)
- Y. Tian, X. Zheng, X. Zhang, and Y. Jin. Efficient large-scale multi-objective optimization based on a competitive swarm optimizer. IEEE Transactions on Cybernetics, 2019 (accepted)
- C. He, L. Li, Y. Tian, X. Zhang, R. Cheng, Y. Jin and X. Yao. Accelerating large-scale multi-objective optimization via problem reformulation. IEEE Transactions on Evolutionary Computation, 2019 (accepted)
- G. Yu, Y. Jin, and M. Olhofer. Benchmark problems and performance indicators for search of knee points in multi-objective optimization. IEEE Transactions on Cybernetics, 2019 (accepted)
- Y. Tian, X. Zhang, R. Cheng, C. He, and Y. Jin. Guiding evolutionary multi-objective optimization with generic front modeling. IEEE Transactions on Cybernetics, 2018 (accepted)
- L. Zhang, H. Pan, X. Zhang, X. Zeng and Y. Jin. A network reduction based multi-objective evolutionary algorithm for community detection in large-scale complex networks. IEEE Transactions on Cybernetics, 2018 (accepted)
- H. Wang, and Y. Jin. A random forest assisted evolutionary algorithm for data-driven constrained multi-objective combinatorial optimization of trauma systems. IEEE Transactions on Cybernetics, 2018 (accepted)
- Z. Yang, Y. Jin, and K. Hao. A bio-inspired self-learning coevolutionary dynamic multiobjective optimization algorithm for internet of things services. IEEE Transactions on Evolutionary Computation, 2018 (accepted)
- Y. Tian, X. Zhang, R. Cheng, C. He, and Y. Jin. Guiding evolutionary multi-objective optimization with generic front modeling. IEEE Transactions on Cybernetics, 2018 (accepted)
- Y. Tian, R. Cheng, X. Zhang, Y. Su, and Y. Jin. A strengthened dominance relation considering convergence and diversity for evolutionary many-objective optimization. IEEE Transactions on Evolutionary Computation, 2018 (accepted)
- C. Yang, J. Ding, Y. Jin, C. Wang, T. Chai. Multi-tasking multi-objective evolutionary operational indices optimization of beneficiation processes. IEEE Transactions on Automation Science and Engineering, 2018 (accepted).
- Z. Yang, Y. Ding, Y. Jin, and K. Hao. Immune-endocrine system inspired hierarchical coevolutionary multiobjective optimization algorithm for IoT service. IEEE Transactions on Cybernetics, 2018 (accepted)
- Y. Tian, R. Cheng, X. Zhang, M. Li, and Y. Jin. Diversity assessment of multi-objective evolutionary algorithms: Performance metric and benchmark problems. IEEE Computational Intelligence Magazine, 14(3): 61-74, 2019
- Y. Jin, H. Wang, T. Chugh, D. Guo, and K. Miettinen. Data-driven evolutionary optimization: An overview and case studies. IEEE Transactions on Evolutionary Computation, 23(3): 442-458, 2019
- J. Tian, Y. Tan, J. Zeng, C. Sun, and Y. Jin. Multi-objective infill criterion driven Gaussian process assisted particle swarm optimization of high-dimensional expensive problems. IEEE Transactions on Evolutionary Computation, 23(3):459 -472, 2019
- L. Huang, Y. Ding, M. Zhou, Y. Jin, and K. Hao. Multiple-solution optimization strategy for multirobot task allocation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018 (accepted)
- D. Han, W. Du, W. Du, Y. Jin and C. Wu. An adaptive decomposition-based evolutionary algorithm for many-objective optimization. Information Sciences, 491: 204-222, 2019
- X. Wang, Y. Jin, and K. Hao. Echo state networks regulated by local intrinsic plasticity rules for regression. Neurocomputing, 351: 111-122, 2019
- X. Peng, Y. Jin, and H. Wang. Multi-modal optimization enhanced cooperative coevolution for large-scale optimization. IEEE Transactions on Cybernetics, 49(9): 3507-3520, 2019
- M. Rong, D. Gong, Y. Zhang, Y. Jin, and W. Pedrycz. Multi-directional prediction approach for dynamic multi-objective optimization problems. IEEE Transactions on Cybernetics, 49(9):3362-3374, 2019
- H. Wang, Y. Jin, C. Sun and J. Doherty. Offline data-driven evolutionary optimization using selective surrogate ensembles. IEEE Transactions on Evolutionary Computation, 23(2): 203-216, 2019
- M. G. Carneiroa, R. Cheng, L. Zhao, Y. Jin. Particle swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019
- Y. Hua, Y. Jin and K. Hao. A clustering based adaptive evolutionary algorithm for multi-objective optimization with irregular Pareto fronts. IEEE Transactions on Cybernetics, 49(7): 2758-2770, 2019
- J. Ding, C. Yang, Q. Xiao, T. Chai, and Y. Jin. Dynamic evolutionary multi-objective optimization for raw ore allocation in mineral processing. IEEE Transactions on Emerging Topics in Computational Intelligence, 3(1): 36-48, 2019
- D. Guo, Y. Jin, J. Ding, and T. Chai. Heterogeneous ensemble based infill criterion for evolutionary multi-objective optimization of expensive problems. IEEE Transactions on Cybernetics, 49(3):1012-1025, 2019
- J. Ding, C. Yang, Y. Jin and T. Chai. Generalized multi-tasking for evolutionary optimization of expensive problems. IEEE Transactions on Evolutionary Computation, 23(1): 44-58, 2019
- L. Pan, C. He, Y. Tian, H. Wang, X. Zhang, and Y. Jin. A classification based surrogate-assisted evolutionary algorithm for expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 23(1):74-88, 2019
- Q. Fan, Y. Jin, W. Wang, and X. Yan. A performance-driven multi-algorithm selection strategy for energy consumption optimization of sea-rail intermodal transportation. Swarm and Evolutionary Computation, 44:1-17, 2019
- W. Du, W. Zhong, Y. Tang, W. Du and Y. Jin. High-dimensional robust multi-objective optimization for order scheduling: A decision variable classification approach. IEEE Transactions on Industrial Informatics, 15(1): 293-304, 2019
- Y. Han, D. Gong, Y. Jin, and Q. Pan. Evolutionary multi-objective blocking lot-streaming flow shop scheduling with machine breakdowns. IEEE Transactions on Cybernetics, 49(1): 184-197, 2019
- Y. Wang, D. Wang, X. Ye, Y. Wang, Y. Yin, and Y. Jin. A tree ensemble-based two-stage model for advanced-stage colorectal cancer survival prediction. Information Sciences, 44:106-124, 2019
- R. Jiao, S. Zeng, C. Li, Y. Jiang and Y. Jin. A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization. Information Sciences, 471:80-96, 2019
- H. Wang, Y. Jin and J. Doherty. A generic test suite for evolutionary multi-fidelity optimization. IEEE Transactions on Evolutionary Computation. 22(6): 836 – 850, 2018
- R. Jiao, S. Zeng, C. Li, Y. Jiang and Y. Jin. A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization. Information Sciences, 471, 80-96, 2019
- S. Cui, D. Wang, Y. Wang, P.-W. Yu, Y. Jin. An improved support vector machine-based diabetic readmission prediction. Computer Methods and Programs in Biomedicine, 166: 123-135, 2018
- Z. Xie and Y. Jin. An extended reinforcement learning framework to model cognitive development with enactive pattern representation. IEEE Transactions on Cognitive and Developmental Systems, 10(3): 738-750, 2018
- F. Li, R. Cheng, J. Liu, and Y. Jin. TS-R2EA: A two-stage R2 indicator based evolutionary algorithm for many-objective optimization. Applied Soft Computing, 67: 245-260, 2018
- H. Yu, Y. Tan, J. Zeng, C. Sun and Y. Jin. Surrogate-assisted hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
- Z. Chen, C. K. Yeo, B. S. Lee, C. T. Lau and Y. Jin. Evolutionary multi-objective optimization based ensemble autoencoders for image outlier detection. Neurocomputing, 309: 192-200 2018
- C. Qian, Y. Yang, K. Tang, Y. Jin, X. Yao, and Z.-H. Zhou. On the effectiveness of sampling for evolutionary optimization in noisy environments. Evolutionary Computation, 26(2):237-267, 2018
- C. Sun, J. Ding, J. Zeng and Y. Jin. Fitness approximation assisted competitive swarm optimizer for large scale expensive optimization problems. Memetic Computing, 10(2):123-134 2018.
- H. Oh, A. R. Shiraz, Y. Jin. Morphogen diffusion algorithms for tracking and herding using a swarm of Kilobots. Soft Computing, 22(6): 1833-1844, 2018
- Y. Tian, R. Cheng, X. Zhang, F. Cheng, and Y. Jin. An indicator based multi-objective evolutionary algorithm with reference point adaptation for better versatility. IEEE Transactions on Evolutionary Computation, 22(1):97-112, 2018
- T. Chugh, Y. Jin, K. Miettinen, J. Hakanen, and K. Sindhya. A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 21(1): 129-142, 2018
- S. Gu, R. Cheng, Y. Jin. Feature selection for high dimensional classification using a competitive swarm optimizer. Soft Computing, 22(3): 811–822, 2018
- X. Zhang, Y. Tian, R. Cheng and Y. Jin. A decision variable clustering-based evolutionary algorithm for large-scale many-objective optimization. IEEE Transactions on Evolutionary Computation, 22(1):97 - 112, 2018
- X. Zhang, Xi. Zheng, R. Cheng, J. Qiu, and Y. Jin. A competitive mechanism based multi-objective particle swarm optimizer with fast convergence. Information Sciences, 427:63-76, 2018
- A. Ramezan Shirazi and Y. Jin. A Strategy for Self-Organized Coordinated Motion of a Swarm of Minimalist Robots. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(5): 326 – 338, 2017
- Y. Tian, H. Wang, X. Zhang, and Y. Jin. Effectiveness and efficiency of non-dominated sorting for evolutionary multi- and many-objective optimization. Complex & Intelligent Systems, 3(4): 247–263, 2017
- H. Wang, M. Olhofer and Y. Jin. Mini-review on preference modeling and articulation in multi-objective optimization: Current status and challenges. Complex & Intelligent Systems, 3(4):233-245, 2017
- X. Zhang, F. Duan, L. Zhang, F. Cheng, Y. Jin, K. Tang. Pattern recommendation in task oriented applications: A multi-objective perspective. IEEE Computational Intelligence Magazine, 12(3):43-53, 2017
- X. Ye, S. Liu, Y. Yin and Y. Jin. User-oriented many-objective cloud workflow scheduling based on an improved knee point driven evolutionary algorithm. Knowledge Based Systems, 135: 113-124, 2017
- R. Cheng, Y. Jin, M. Olhofer and B. Sendhoff. Test problems for large-scale multi- and many-objective optimization. IEEE Transactions on Cybernetics, 7(12): 4108-4121, 2017
- Y. Tian, R. Cheng, X. Zhang, and Y. Jin. PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization. IEEE Computational Intelligence Magazine, 12(4):73-87, 2017
- C. He, Y. Tian, Y. Jin, X. Zhang, and L. Pan. A radial space division based evolutionary algorithm for many-objective optimization. Applied Soft Computing, 61:603-621, 2017
- Y. Liu, D. Gong, J. Sun, and Y. Jin. A many-objective evolutionary algorithm using a one-by-one selection strategy. IEEE Transactions on Cybernetics, 47(9): 2689-2702, 2017
- C. Sun, Y. Jin, R. Cheng, J. Ding and J. Zeng. Surrogate-assisted cooperative swarm optimization of high-dimensional expensive problems. IEEE Transactions on Evolutionary Computation, 21(4): 644-660, 2017
- H. Wang, Y. Jin, and J. Doherty. Committee-based active learning for surrogate-assisted particle swarm optimization of expensive problems. IEEE Transactions on Cybernetics, 47(9): 2664-2677, 2017
- S. Gu and Y. Jin. Multi-train: A semi-supervised heterogeneous ensemble classifier. Neurocomputing, 249:202-211, 2017
- G. Yao, Y. Ding, Y. Jin, K. Hao. Endocrine-based coevolutionary multi-swarm for multi-objective workflow scheduling in a cloud system. Soft Computing, 21(15): 4309–4322, 2017
- H. Wang, Y. Jin and X. Yao. Diversity assment in many-objective optimization. IEEE Transactions on Cybernetics, 47(6):1510-1522, 2017 (Highly cited article, as of 28.03.2018)
- J. Liu, Y. Chi, C. Zhu and Y. Jin. A time series driven decomposed evolutionary optimization approach for reconstructing large-scale gene regulatory networks based on fuzzy cognitive maps. BMC Bioinformatics, 18:241, 2017. DOI: 10.1186/s12859-017-1657-1
- R. Cheng, T. Rodemann, M. Fischer, M. Olhofer, and Y. Jin. Evolutionary many-objective optimization of hybrid electric vehicle control: From general optimization to preference articulation. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(2):97-111, 2017
- T. Chugh, N. Chakraborti, K. Sindhya, and Y. Jin. A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem. Materials and Manufacturing Processes, 32(1): 1172-1178, 2017
- R. Allmendinger, M. T. M. Emmerich, J. Hakanen, Y. Jin, and E. Rigoni. Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case. Journal of Multi-Criteria Decision Analysis, 14(1/2):5-25, 2017
- W. A. Albukhanajer, Y. Jin, and J. A. Briffa. Classifier ensembles for image identification using multi-objective Pareto features. Neurocomputing, 238:316-327, 2017
- H. Oh, A. R. Shirazi, C. Sun, and Y. Jin. Bio-inspired self-organising multi-robot pattern formation: A review. Robotics and Autonomous Systems, 91:83-100, 2017
- Y. Huang, Y. Ding, K. Hao, and Y. Jin. A multi-objective approach to robust optimization over time considering switching cost. Information Sciences, Vol. 394-395, 183-197, 2017
- D.-J. Wang, F. Liu and Y. Jin. A multi-objective evolutionary algorithm guided by directed search for dynamic scheduling. Computers & Operations Research, 79: 279-290, 2017
- H. Wang, Y. Jin and J. O. Jansen. Data-driven surrogate-assisted multi-objective evolutionary optimization of a trauma system. IEEE Transactions on Evolutionary Computation, 20(6): 939-952, 2016
- C. Brown, Y. Jin, M. Leach and M. Hodgson. m JADE: Adaptive differential evolution with a small population. Soft Computing, 20(10): 4111-4120, 2016
- X. Peng, K. Liu and Y. Jin. A dynamic optimization approach to the design of cooperative coevolutionary algorithms. Knowledge-Based Systems, 109: 174-186, 2016
- R. Cerri, R. C. Barros, A. C. P. de L. F. Carvalho and Y. Jin. Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinformatics, 17:373, 2016. DOI: 10.1186/s12859-016-1232-1
- X. Zhang, Y. Tian, Y. Jin. Approximate non-dominated sorting for evolutionary many-objective optimization. Information Sciences, 369:14-33, 2016
- R. Cheng, Y. Jin, M. Olhofer and B. Sendhoff. A reference vector guided evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 20(5):773-791, 2016 (Highly cited article, as of 28.03.2018)
- M.-H. Yusoff, J. Chrol-Cannon and Y. Jin. Modeling neural plasticity in echo state networks for classification and regression. Information Sciences, 364–365:184–196, 2016
- R. Cheng, Y. Jin, K. Narukawa and B. Sendhoff. A multiobjective evolutionary algorithm using Gaussian process based inverse modeling. IEEE Transactions on Evolutionary Computation, 19(6):761-856, 2015
- X. Zhang, Y. Tian and Y. Jin. A knee point driven evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 19(6):761-776, 2015 (Highly cited article, as of 28.03.2018)
- D.-J. Wang, F. Liu, Y.-Z. Wang, Y. Jin. A knowledge-based evolutionary proactive scheduling approach in the presence of machine breakdown and deterioration effect. Knowledge-Based Systems. 90:70-80, 2015
- Y. Wu, Y. Jin and X. Liu. A directed search strategy for evolutionary dynamic multiobjective optimization. Soft Computing, 19:3221–3235, 2015
- W. A. Albukhanajer, J. A. Briffa, and Y. Jin. Evolutionary multi-objective image feature extraction in the presence of noise. IEEE Transactions on Cybernetics, 45(9):1757-1768, 2015
- J. Chrol-Cannon and Y. Jin. Learning structure of sensory inputs with synaptic plasticity leads to interference. Frontiers in Computational Neuroscience, 9: 103, 2015. doi: 10.3389/fncom.2015.00103
- S. Gu, R. Cheng and Y. Jin. Multi-objective ensemble generation. WIREs Data Mining and Knowledge Discovery, 5(5): 234-245, 2015
- X. Zhang, Y. Tian, R. Cheng, and Y. Jin. An efficient approach to non-dominated sorting for evolutionary multi-objective optimization. IEEE Transactions on Evolutionary Computation, 19(2): 201-213, 2015 (Highly cited article, as of 28.03.2018)
- T. Rahman, M. Mahapatra, E. Laing and Y. Jin. Evolutionary non-linear modelling for selecting vaccines against antigenically-variable viruses. Bioinformatics, 31(6): 834-840, 2015
- B. Yang, Y. Ding, Y. Jin, and K. Hao. Self-organized swarm robot for target search and trapping inspired by bacterial chemotaxis. Robotics and Autonomous Systems, 72: 83-92, 2015
- R. Cheng and Y. Jin. A competitive swarm optimizer for large scale optimization. IEEE Transactions on Cybernetics, 45(2): 191-204, 2015 (Highly cited article, as of 28.03.2018)
- Y. Jin, Y. Ding, K. Hao, Y. Jin. An endocrine-based intelligent distributed cooperative algorithm for target tracking in wireless sensor networks. Soft Computing, 19(5): 1427-1441, 2015
- C. Sun, Y. Jin, J. Zeng and Y. Yu. A two-layer surrogate-assisted particle swarm optimization algorithm. Soft Computing, 19(6): 1461-1475, 2015
- T. Zhang, Y. Jin, Y. Ding and K. Hao. A cytokine network inspired cooperative control system for multi-stage stretching processes in fiber production. Soft Computing, 19(6): 1523-1540, 2015
- R. Cheng and Y. Jin. A social learning particle swarm optimization algorithm for scalable optimization. Information Sciences, 291:43-60, 2015 (Highly cited article, as of 28.03.2018)
- Z.-H. Zhou, N. V. Chawla, Y. Jin, and G. J. Williams. Big data opportunities and challenges: Discussions from data analytics perspectives. IEEE Computational Intelligence Magazine, 9(4):62-74, 2014
- J. Chrol-Cannon and Y. Jin. On the correlation between reservoir metrics and performance for time series classification under the influence of synaptic plasticity. PLOS ONE, DOI: 10.1371/journal.pone.0101792, July 10, 2014
- S. A. Thomas and Y. Jin. Reconstructing biological gene regulatory networks: Where optimization meets big data. Evolutionary Intelligence, 7(1):29-47, 2014
- C. Smith and Y. Jin. Evolutionary multi-objective generation of recurrent neural network ensembles for time series prediction. Neurocomputing, 143:302-311, 2014
- J. Chrol-Cannon and Y. Jin. Computational modeling of neural plasticity for self-organization of neural networks. BioSystems, 125: 43-54, 2014
- A. Zhou, Y. Jin and Q. Zhang. A population prediction strategy for evolutionary dynamic multiobjective optimization. IEEE Transactions on Cybernetics, 44(1): 40-53, 2014
- X. Sun, S. Chen, Y. Jin and D. Gong. A new surrogate-assisted interactive genetic algorithm with weighted semi-supervised learning. IEEE Transactions on Cybernetics, 43(2): 685-698, 2013
- S. A. Thomas and Y. Jin. Evolving connectivity between genetic oscillators and switches using evolutionary algorithms. Journal of Bioinformatics and Computational Biology, 11(3), 2013
- B. Inden, Y. Jin, R. Haschke, H. Ritter, B. Sendhoff. An examination of different fitness and novelty based selection methods for the evolution of neural networks. Soft Computing. 17(5): 753-767, 2013
- Y. Jin, K. Tang, X. Yu, B. Sendhoff and X. Yao. A framework for finding robust optimal solutions over time. Memetic Computing, 5(1):3-18, 2013
- M.N. Le, Y.S. Ong, S. Menzel, Y. Jin, and B. Sendhoff. Evolution by adapting surrogates. Evolutionary Computation, 21(2):313-340, 2013
- Y. Meng, H. Guo and Y. Jin. A morphogenetic approach to flexible and robust shape formation for swarm robotic systems. Robotics and Autonomous Systems, 61(1):25-38, 2013
- C. Sun, J. Zeng, J. Pan, S. Xue, Y. Jin. A new fitness estimation strategy for particle swarm optimization. Information Sciences: 221: 355-370, 2013
- G. Jia, Y. Wang, Z. Cai, and Y. Jin. An improved (m + l)-constrained differential evolution for constrained optimization. Information Sciences, 222: 302-322, 2013
- L. Schramm, Y. Jin, and B. Sendhoff. Evolution and analysis of genetic networks for stable cellular growth and regeneration. Artificial Life, 18(4): 425-444, 2012
- D. Bush and Y. Jin. Calcium control of hippocampal STDP. Journal of Computational Neuroscience. 33(3):495-514, 2012
- J. Yin, Y. Meng and Y. Jin. A developmental approach to structural self-organization in reservoir computing. IEEE Transactions on Autonomous Mental Development, DOI: 10.1109/TAMD.2012.2182765, 2012
- Y. Jin, H. Guo, and Y. Meng. A hierarchical gene regulatory network for adaptive multi-robot pattern formation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(3):805-816, 2012
- M. N. Le, Y. S. Ong, Y. Jin and B. Sendhoff. A unified framework for symbiosis of evolutionary mechanisms with application to water clusters potential model design. IEEE Computational Intelligence Magazine, 7(1):20-35, 2012
- B. Inden, Y. Jin, R. Haschke, H. Ritter. Evolving neural fields for problems with large input and output spaces. Neural Networks, 28: 24-39, 2012
- H. Guo, Y. Jin, and Y. Meng. A morphogenetic framework for self-organized multi-robot pattern formation and boundary coverage. ACM Transactions on Autonomous and Adaptive Systems, 7(1), Article No. 15, April 2012. Doi:10.1145/2168260.2168275
- E. Gehrmann, C. Glaesser, Y. Jin, B. Sendhoff, B. Drossel, and K. Hamacher. Robustness of glycolysis in yeast to internal and external noise. Physical Review E, E 84, 021913, 2011
- Y. Meng, Y. Jin and J. Yin. Modeling activity-dependent plasticity in BCM spiking neural networks with application to human behavior recognition. IEEE Transactions on Neural Networks, 22(12):1952-1966, 2011
- Y. Zhang, Y. Meng, Y. Jin. Object recognition using a bio-inspired neuron model with bottom-up and top-down pathways. Neurocomputing, 74(17): 3158-3169, 2011
- Y. Jin. Surrogate-assisted evolutionary computation: Recent advances and future challenges. Swarm and Evolutionary Computation, 1(2):61-70, 2011 (Highly cited article, as of 28.03.2018)
- S. Oh, Y. Jin and M. Jeon. Approximate models for constraint functions in evolutionary constrained optimization. International Journal of Innovative Computing, Information and Control. 7(11):6585-6603, 2011
- Y. Jin and Y. Meng. Emergence of robust regulatory motifs from in silico evolution of sustained oscillation. BioSystems, 103(1):38-44, 2011
- Y. Jin and Y. Meng. Morphogenetic robotics: An emerging new field in developmental robotics. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(2):145-160, 2011
- M. Liu, S. Zhang and Y. Jin. Multi-sensor optimal H_¥ fusion filters for delayed nonlinear intelligent systems based on a unified model. Neural Networks, 24(3):280-290, 2011
- Y. Meng, Y. Zheng, and Y. Jin. Autonomous self-reconfiguration of modular robots by evolving a hierarchical mechanochemical model. IEEE Computational Intelligence Magazine, 6(1):43-54, 2011
- Y. Meng and Y. Jin. Distributed multi-agent systems for a collective construction task based on virtual swarm intelligence. International Journal of Swarm Intelligence Research, 1(2), 58-79, 2010
- D. Lim, Y. Jin, Y.-S. Ong, and B. Sendhoff. Generalizing surrogate-assisted evolutionary computation. IEEE Transactions on Evolutionary Computation, 14(3):329-355, 2010
- T. Steiner, Y. Jin, and B. Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177, 2009
- H. Guo, Y. Meng, and Y. Jin. A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network. BioSystems, 98(3):193-203, 2009
- M.N. Le, Y. S. Ong, Y. Jin, and B. Sendhoff. Lamarckian memetic algorithms: Local optimum and connectivity structure analysis. Memetic Computing, 1(3):1795-190, 2009
- A. Zhou, Q. Zhang, Y. Jin. Approximating the set of Pareto-optimal solutions in both decision and objective spaces by an estimation of distribution algorithm. IEEE Transactions on Evolutionary Computation, 13(5): 1167-1189, 2009
- Y. Jin and B. Sendhoff. A systems approach to evolutionary multi-objective structural optimization. IEEE Computational Intelligence Magazine, 4(3):62-76, 2009
- I. Paenke, Y. Jin, J. Branke. Balancing population and individual level of adaptation in changing environments. Adaptive Behavior, 17(2):153-174, 2009
- M. Meeter, R. Veldkamp, Y. Jin. Multiple memory stores and operant conditioning: A rationale for memory's complexity. Brain and Cognition, 69(1):200-208, 2009
- Y. Jin, R. Grunar, and B. Sendhoff. Pareto analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009
- Y. Jin and B. Sendhoff. Pareto-based multi-objective machine learning: An overview and case studies. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 38(3):397-415, 2008
- Q. Zhang, A. Zhou, Y. Jin. RM-MEDA: A regularity model-based multiobjective estimation of distribution algorithm. IEEE Transactions on Evolutionary Computation. 12(1):41-63, 2008 (Highly cited article, as of 28.03.2018)
- D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff, B.-S. Lee. Efficient hierarchical parallel genetic algorithms using grid computing. Future Generation Computer Systems. 23(4):658-670, 2007
- D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff, and B. S. Lee. Adaptive inverse multi-objective robust evolutionary design optimization. Genetic Programming and Evolvable Machines. 7(4), 383-404, 2007
- I. Paenke, J. Branke, and Y. Jin. Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation. IEEE Transactions on Evolutionary Computation, 10(4), 405-420, 2006
- K. Foli, T. Okabe, M. Olhofer, Y. Jin, and B. Sendhoff. Optimization of micro heat exchanger: CFD, analytical approach and multi-objective evolutionary algorithms. International Journal of Heat and Mass Transfer. 49, 1090-1099, 2006
- Y. Jin and J. Branke. Evolutionary optimization in uncertain environments - A survey. IEEE Transactions on Evolutionary Computation, 9(3), 303-317, 2005
- H. Wang, S. Kwong, Y. Jin, W. Wei and K. Man. Agent-based evolutionary approach to interpretable rule-based knowledge extraction. IEEE Transactions Systems, Man, and Cybernetics, Part C, 29(2), 143-155, 2005
- H. Wang, S. Kwong, Y. Jin, W. Wei and K. Man. A multi-objective hierarchical genetic algorithm for interpretable rule-based knowledge extraction. Fuzzy Sets and Systems, 149(1), 149-186, 2005
- Y. Jin. A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing, 9(1), 3-12, 2005
- M. Huesken, Y. Jin and B. Sendhoff. Structure optimization of neural networks for evolutionary design optimization. Soft Computing, 9(1), 21-28, 2005
- Y. Jin and B. Sendhoff, Extracting interpretable fuzzy rules from RBF networks. Neural Processing Letters, 17(2), 149-164, 2003
- Y. Jin, M. Olhofer and B. Sendhoff. A framework for evolutionary optimization with approximate fitness functions. IEEE Transactions on Evolutionary Computation, 6(5), 481-494, 2002
- Y. Jin. Fuzzy modeling of high-dimensional systems: Complexity reduction and interpretability improvement. IEEE Transactions on Fuzzy Systems, 8(2), 212-221, 2000
- Y. Jin and B. Sendhoff. Knowledge incorporation into neural networks from fuzzy rules. Neural Processing Letters, 10(3), 231-242, 1999
- Y. Jin, W. von Seelen and B. Sendhoff. On generating FC3 fuzzy rule systems from data using evolution strategies. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 29(6), 829-845, 1999
- Y. Jin and W. von Seelen. Evaluating flexible fuzzy controllers via evolution strategies. Fuzzy Sets and Systems, 108, 243-252, 1999
- Y. Jin. Decentralized adaptive fuzzy control of robot manipulators. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, 28(1), 47-57, 1998
- Y. Jin, J. Jiang and J. Zhu. Neural network based fuzzy identification and its applications to modeling and control of complex systems. IEEE Transactions on Systems, Man and Cybernetics, 25(6), 990-997, 1995
- Y. Jin, J. Zhu and J. Jiang. Adaptive fuzzy identification with applications. International Journal of Systems Science, 6(2), 197-212, 1995
Peer-Reviewed Conference Papers
- C. Sun, Y. Jin and Y. Tan. Semi-supervised learning assisted particle swarm optimization of computationally expensive problems. Genetic and Evolutionary Computation Conference, Kyoto, Japan, 15-19 July 2018
- G. Yu, Y. Jin and M. Olhofer. Method for a posteriori identification of knee points based on solution density. Congress on Evolutionary Computation, Rio de Janeiro, Brazil, 8-13 July 2018
- H. Wang, J. Doherty and Y. Jin. Hierarchical surrogate-assisted evolutionary multi-scenario airfoil shape optimization. Congress on Evolutionary Computation, Rio de Janeiro, Brazil, 8-13 July 2018
- Y. Tian, X. Xiang, X. Zhang, R. Cheng and Y. Jin. Sampling reference points on the Pareto fronts of multi-objective optimization problems. Congress on Evolutionary Computation, Rio de Janeiro, Brazil, 8-13 July 2018
- M. G. Carneiro, T. H. Cupertino, R. Cheng, Y. Jin and L. Zhao. Nature-inspired graph optimization for dimensionality reduction. The Annual IEEE International Conference on Tools with Artificial Intelligence, November 6-7, 2017, Boston, MA, USA
- S. Thomas, Y. Jin, J. Bunch and I. Gilmore. Enhancing classification of mass spectrometry imaging data with deep neural networks. IEEE Symposium Series on Computational Intelligence, November 27-December 1, 2017, Hawaii, USA
- N. Naik, P. Jenkins, R. Cooke, D. Ball, A. Foster, Y. Jin. Augmented windows fuzzy firewall for preventing denial of service attack. FUZZ-IEEE 2017: 1-6
- T. Jie, T. Ying, S. Chaoli, Z. Jianchao, Y. Haibo and Y. Jin. Comparisons of different kernels in Kriging-assisted evolutionary expensive optimization. IEEE Symposium Series on Computational Intelligence, November 27-December 1, 2017, Hawaii, USA
- C. Yang, J. Ding, K. C. Tan, and Y. Jin. Two-stage assortative mating for multi-objective multifactorial evolutionary optimization. The 56th IEEE Conference on Decision and Control, December 12-15, 2017, Melbourne, Australia
- H. Wang and Y. Jin. Efficient nonlinear correlation detection for decomposed search in evolutionary multi-objective optimization. Congress on Evolutionary Computation, June 2017
- T. Chugh, K. Sindhya, K. Miettinen, Y. Jin, T. Kratky, and P. Makkonen. Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system. Congress on Evolutionary Computation, June 2017 (Best Student Paper Award)
- D. Guo, T. Chai, J. Ding, and Y. Jin. Small data driven evolutionary multi-objective optimization of fused magnesium furnaces. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
- J. Hakanen, T. Chugh, K. Sindhya, Y. Jin, K. Miettinen. Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
- J. Tian, Y. Tan, C. Sun, J. Zeng, and Y. Jin. A self-adaptive similarity-based fitness approximation for evolutionary optimization. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
- U. Yolcu, Y. Jin and E. Egrioglu. An ensemble of single multiplicative neuron models for probabilistic prediction. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
- X. Zhang, Y. Tian, R. Cheng, and Y. Jin. Empirical analysis of a tree-based efficient non-dominated sorting approach for many-objective optimization. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
- H. Yu, C. Sun, J. Zeng, Y. Tan and Y. Jin. An adaptive model selection strategy for surrogate-assisted particle swarm optimization algorithm. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
- S. Cheng, B. Liu, Y. Shi, Y. Jin and B. Li. Evolutionary computation and big data: Key challenges and future directions. DMBD 2016, LNCS 9714, pp. 3–14, 2016
- M. Carneiro, L. Zhao, R. Cheng and Y. Jin. Network structural optimization based on swarm intelligence for high level classification. International Joint Conference on Neural Networks, Vancouver, July 2016
- C. Yang, J. Ding, T. Chai and Y. Jin. Reference point based prediction for evolutionary dynamic multiobjective optimization. Congress on Evolutionary Computation, Vancouver, July 2016
- Y. Tian, X. Zhang, R. Cheng and Y. Jin. A multi-objective evolutionary algorithm based on an enhanced inverted generational distance metric. Congress on Evolutionary Computation, Vancouver, July 2016
- R. Cheng, M. Olhofer and Y. Jin. Reference vector based a posteriori preference articulation for evolutionary multiobjective optimization. Congress on Evolutionary Computation (CEC 2015). May 24-28, 2015, Sendai, Japan
- Y. Huang, Y. Jin and Y. Ding. New performance indicators for robust optimization over time. Congress on Evolutionary Computation (CEC 2015). May 24-28, 2015, Sendai, Japan
- W. A. Albukhanajer, Y. Jin and J. Briffa, Trade-off between computational complexity and accuracy in evolutionary image feature extraction. Congress on Evolutionary Computation (CEC 2015). May 24-28, 2015, Sendai, Japan
- R. Cheng, Y. Jin and K. Narukawa. Adaptive reference vector generation for inverse model based evolutionary multiobjective optimization with degenerate and disconnected Pareto fronts. The 8th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO'2015), Guimarães, Portugal
- S. Gu and Y. Jin. Generating diverse and accurate classifier ensembles using multi-objective optimization. IEEE Symposium Series on Computational Intelligence, December 9-12, 2014, Orlando, Florida, USA
- M. Rustell, A. Orsini, S.T. Khu, Y. Jin and B. Gouldby. (2014). Optimizing an LNG terminal subject to uncertainty. 11th International Conference of Hydroinformatics. New York, 17-20th August 2014.
- M.-H. Yusoff and Y. Jin. Modeling neural plasticity in Echo State Networks for time series prediction. 2014 UK Workshop on Computational Intelligence, Bradford, UK, 8 - 10 September 2014
- H. Oh and Y. Jin. Adaptive swarm robot region coverage using gene regulatory networks. The 15th Towards Autonomous Robotic Systems, September 1-3, 2014, Birmingham, UK.
- A. Ramezan Shirazi, H. Oh and Y. Jin. Morphogenetic self-organization of collective movement without directional sensing. The 15th Towards Autonomous Robotic Systems, September 1-3, 2014, Birmingham, UK
- C. Qian, Y. Yu, Y. Jin and Z.-H. Zhou. On the effectiveness of sampling for evolutionary optimization in noisy environments. Parallel Problem Solving from Nature (PPSN’14), September 13-17, 2014 Ljubljana, Slovenia
- T. Liu, C. Sun, J. Zeng and Y. Jin. Similarity- and reliability-assisted fitness estimation for particle swarm optimization of expensive problems. IEEE Congress on Evolutionary Computation, July 2014
- R. Cheng and Y. Jin. Demonstrator selection in a social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014
- H. Oh and Y. Jin. Evolving hierarchical gene regulatory networks for morphogenetic pattern formation of swarm robotics. IEEE Congress on Evolutionary Computation, July 2014
- W. A. Albukhanajer, Y. Jin and J. A. Briffa. Neural network ensembles for image identification using Pareto-optimal features. IEEE Congress on Evolutionary Computation, July 2014
- C. Smith, J. Doherty and Y. Jin. Multi-objective evolutionary recurrent neural network ensemble for prediction of computational fluid dynamic simulations. IEEE Congress on Evolutionary Computation, July 2014 (Runner-up, Best Student Paper Award)
- R. Cheng, C. Sun and Y. Jin. A multi-swarm evolutionary framework based on a feedback mechanism. In: IEEE Congress on Evolutionary Computation (CEC'2013), Cancun, Mexico, June 20-23 2013
- A. Xiao, B. Wang and Y. Jin. Evolutionary truss layout optimization using the vectorized structure approach. In: IEEE Congress on Evolutionary Computation (CEC'2013), Cancun, Mexico, June 20-23 2013
- J. Lu, B. Li, and Y. Jin. An evolution strategy assisted by an ensemble of local Gaussian process models. In: Genetic and Evolutionary Computation Conference (GECCO'2013), Amsterdam, The Netherlands, 6-10 July 2013
- C. Smith, J. Doherty, and Y. Jin. Recurrent neural network ensembles for convergence prediction in surrogate-assisted evolutionary optimisation. IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Singapore, 16-19 April 2013
- C. Sun, J. Zeng, J. Pan and Y. Jin. Similarity based evolution control for fitness estimation in particle swarm optimisation. IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Singapore, 16-19 April 2013
- S. A. Thomas and Y. Jin. Single and multi-objective in silico evolution of tunable genetic oscillators. The 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), 19-22 March 2013, Sheffield, UK
- W. A. Albukhanajer, Y. Jin, J. A. Briffa, and G. Williams. A comparative study of multi-objective evolutionary Trace Transform algorithms for robust feature extraction. The 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), 19-22 March 2013, Sheffield, UK
- S. Gu and Y. Jin. Heterogeneous classifier ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012
- W. Albukhanajer, Y. Jin, J. Briffa and G. Williams. Evolutionary multi-objective optimization of Trace transform for invariant feature extraction. 2012 IEEE Congress on Evolutionary Computation, Brisbane, Australia, June 2012
- J. Chrol-Cannon, A. Gruning and Y. Jin. The emergence of polychronous groups under varying input patterns, plasticity rules and network connectivities. 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 2012
- S. Thomas and Y. Jin. Combining genetic oscillators and switches using evolutionary algorithms. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, USA, May 2012
- L. Schramm, Y. Jin and B. Sendhoff. Quantitative analysis of redundancy in evolution of developmental systems. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, USA, May 2012
- B. Inden, Y. Jin, R. Haschke and H. Ritter. Exploiting inherent regularity in control of multilegged robot locomotion by evolving neural fields. Third World Congress on Nature and Biologically Inspired Computing (NaBIC2011), October 19-21, 2011, Salamanca University, Spain
- D. Bush and Y. Jin. A unified computational model of the genetic regulatory networks underlying synaptic, intrinsic and homeostatic plasticity. 2011 International Conference on Wiring the Brain: Making Connections, April 12-15, 2011, County Wicklow, Ireland
- L. Schramm, Y. Jin, and B. Sendhoff. Redundancy creates opportunity in developmental representations. 2011 IEEE Symposium on Artificial Life, Paris, France, April 11-15, 2011
- H. Guo, Y. Meng, and Y. Jin. Swarm robot pattern formation using a morphogenetic multi-cellular based self-organization algorithm. 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China, May 9-13, 2011
- Y. Meng, Y. Zhang, A. Sampath, Y. Jin, and B. Sendhoff. Cross-ball: A new morphogenetic self-reconfigurable modular robot. 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China, May 9-13, 2011
- J. Goh, L. Tang, L. Al Turk, Y. Jin, G. Saleh, A combined particle swarm optimisation and genetic algorithm for context analysis of medical images. In: 4th International Conference on Health Informatics. Rome, Italy, 26-29, January, 2011
- Y. Jin, Y. Meng and H. Guo. A morphogenetic self-organization algorithm for swarm robotic systems using relative position information. 2010 UK Workshop on Computational Intelligence, Colchester, UK, September 2010
- B. Jones, Y. Jin, B. Sendhoff, and X. Yao. Emerged optimal distribution of computational workload in the evolution of an undulatory animat. The 11th International Conference on Simulation of Adaptive Behaviors (SAB 2010), pp.587-596, August 24-28, 2010
- Y. Jin, S. Oh and M. Jeon. Incremental approximation of nonlinear constraint functions for evolutionary constrained optimization. Congress on Evolutionary Computation, pp.2966-2973, Barcelona, July 2010
- X. Yu, Y. Jin, K. Tang, and X. Yao. Robust optimization over time -- A new perspective on dynamic optimization problems. Congress on Evolutionary Computation, pp. 3998-4003, Barcelona, July 2010
- Y. Meng, Y. Jin, J. Yin, and M. Conforth. Human activity detection using spiking neural networks regulated by a gene regulatory network. Int. Joint Conference on Neural Networks, pp.2232-2237, Barcelona, July 2010
- H. Guo, Y. Meng, and Y. Jin. Analysis of local communication load in shape formation of a distributed morphogenetic swarm robotic system. Congress on Evolutionary Computation, pp. 1117-1124,, Barcelona, July 2010
- Y. Zheng, Y. Meng and Y. Jin. Fusing bottom-up and top-down pathways in neural networks for visual object recognition. Int. Joint Conference on Neural Networks, pp.2064-2031, Barcelona, July 2010
- T. Steiner, B. Sendhoff, and Y. Jin. Evolving heterochrony for cellular differentiation using vector field embryogeny. Genetic and Evolutionary Computation Conference, pp.571-578, Portland, July 2010
- B. Inden, Y. Jin, R. Haschke, H. Ritter. NEATfields: Evolution of neural fields for visual discrimination and multiple pole balancing tasks. Genetic and Evolutionary Computation Conference, pp. 645-646, Portland, July 2010
- H. Lex, M. Weigelt, Y. Jin, and T. Schack. Visuo-motor adaptation relies on kinesthetic representation of movement directions. North American Society for Psychology of Sport and Physical Activity (NASPSPA) Conference, Tucson, AZ, June 10-12, 2010 (abstract published in Journal of Sport & Exercise Psychology, 32, 100-101)
- Y. Jin and J. Trommler. A fitness-independent evolvability measure for evolutionary developmental systems. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp.69-76, Montreal, Canada, May 2-5 2010 (Best Paper Award)
- A. Finke, Y. Jin, H. Ritter. A P300 based brain-robot interface for shaping human-robot interaction. Bernstein Conference on Computational Neuroscience, Frankfurt, September 2009. doi: 10.3389/conf.neuro.10.2009.14.108
- B. Jones, Y. Jin, B. Sendhoff, and X. Yao. The evolutionary emergence of neural organization in a hydra-like animat. Bernstein Conference on Computational Neuroscience, Frankfurt, September 2009 (poster presentation)
- B. Jones, Y. Jin, B. Sendhoff, and X. Yao. The effect of proprioceptive feedback on the distribution of sensory information in a model of an undulating organism. 10th European Conference on Artificial Life, Budapest, September 2009
- L. Schramm, Y. Jin, Bernhard Sendhoff. Emerged coupling of motor control and morphological development in evolution of multi-cellular animates. 10th European Conference on Artificial Life, Budapest, September 2009
- Y. Jin, Y. Meng, and B. Sendhoff. Evolvability and robustness of in silico evolution of gene regulatory dynamics. In: Foundations of Systems Biology in Engineering. Omnipress, pages 68-71, 2009
- Y. Jin, H. Guo and Y. Meng. Robustness analysis and failure recovery of a bio-inspired self-organizing multi-robot system. In: Third IEEE International Conference on Self-Adaptive and Self-organizing Systems. IEEE Press, pages 154-164, 2009
- T. Steiner, J. Trommler, M. Brenn, Y. Jin, and B. Sendhoff. Global shape with morphogen gradients and motile polarized cells. Congress on Evolutionary Computation, pp.2225-2232, May 2009, Trondheim, Norway
- Y. Jin, Y. Meng, B. Sendhoff. Influence of regulation logic on the easiness of evolving sustained oscillation for gene regulatory networks. IEEE ALIFE, pp.61-68, March 30 - April 1, 2009, Nashville, TN, USA
- H. Guo, Y. Meng, Y. Jin. Self-adaptive multi-robot construction using gene regulatory networks. IEEE ALIFE, pp. 53-60, March 30 - April 1, 2009, Nashville, TN, USA
- Y. Jin, R. Gruna, I. Paenke, B. Sendhoff. Multi-objective optimization of robustness and innovation in redundant genetic representations. IEEE MCDM, pp.38-45, March 30 - April 1, 2009, Nashville, TN, USA 2009
- Y. Jin, L. Schramm, and B. Sendhoff. A gene regulatory model for the development of primitive nervous systems. INNS-NNN Symposia on Modeling the Brain and Nervous Systems, LNCS 5506, pp.48-55, 2009 (Best paper nomination)
- B. Jones, Y. Jin, X. Yao, and B. Sendhoff. Evolution of neural organization in a Hydra-like animat. 15th Int. Conf. on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP’08), LNCS 5506, pp. 216-223, 2009
- D. Lim, Y.-S. Ong, Y. Jin, and B. Sendhoff. Evolutionary optimization with dynamic fidelity computational models. International Conference on Intelligent Computing, pp.235-242, September 15-18, 2008, Shanghai, China
- B. Jones, Y. Jin, B. Sendhoff, and X. Yao. Evolving functional symmetry in a three dimensional model of an elongated organism. Artificial Life IX, Winchester, UK, pp.305-312, August 2008
- T. Steiner, Y. Jin and B. Sendhoff. A cellular model for evolutionary development of lightweight materials with an inner structure. Genetic and Evolutionary Computation Conference, pp.851-858, Atlanta, July 2008 (Best paper nomination)
- Y. Cao, Y. Jin, M. Kowalczykiewicz and B. Sendhoff. Prediction of convergence dynamics of design performance using differential recurrent neural networks. International Joint Conference on Neural Networks, pp.529-534, Hong Kong, June 2008
- A. Zhou, Q. Zhang, Y. Jin and B. Sendhoff. Combination of EDA and DE for continuous bi-objective optimization. Congress on Evolutionary Computation, pp.1447-1454, Hong Kong, June 2008
- N. Samways, Y. Jin, X. Yao, and B. Sendhoff. Toward a gene regulatory network model for evolving chemotaxis behavior. Congress on Evolutionary Computation, pp.2574-2581, Hong Kong, June 2008
- Y. Jin, B. Sendhoff. Evolving in silico bistable and oscillatory dynamics for gene regulatory network motifs. Congress on Evolutionary Computation, pp.386-391,Hong Kong, June 2008
- A. Zhou, Q. Zhang, Y. Jin, B. Sendhoff. Adaptive modeling strategy for continuous multi-objective optimization. Congress on Evolutionary Computation, pp.431-437 Singapore, September 2007
- T. Steiner, L. Schramm, Y. Jin, Bernhard Sendhoff. Emergence of feedback in artificial gene regulatory networks. Congress on Evolutionary Computation, pp.867-874, September 2007 (Best paper 10 finalist)
- Y. Jin, R.Wen, B. Sendhoff. Evolutionary multi-objective optimization of spiking neural networks. International Conference on Artificial Neural Networks, LNCS 4668, pp. 370-379, 2007
- A. Zhou, Q. Zhang, Y. Jin, B. Sendhoff. Adaptive modeling strategy for continuous multi-objective optimization. Congress on Evolutionary Computation, pp.431-437, September 2007
- A. Zhou, Q. Zhang, Y. Jin, B. Sendhoff, E. Tsang, Global multi-objective optimization via estimation of distribution with biased initialization and crossover. Genetic and Evolutionary Computation Conference, pp.617—623, July 8-11, 2007
- D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff. A study on meta-modeling techniques, ensembles and multi-surrogates in evolutionary computation. Genetic and Evolutionary Computation Conference, pp.1288-1295, July 8-11, 2007
- I. Paenke, J. Branke, and Y. Jin. On the influence of phenotype plasticity on genotype diversity. 2007 IEEE Symposium on Foundations of Computational Intelligence, pp.33-40, April 1-4, 2007, Honolulu, Hawaii, 2007 (Best student paper)
- A. Zhou, Y. Jin, Q. Zhang, B. Sendhoff, E. Tsang. Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization. The Fourth International Conference on Evolutionary Multi-Criterion Optimization. Pp. 832-846, LNCS 4403, Springer, 2007
- A. Zhou, Q. Zhang, Y. Jin, B. Sendhoff, E. Tsang. Modeling the population distribution in multi-objective optimization by generative topographic mapping. Parallel Problem Solving from Nature, LNCS 4193, pp.443-452, 2006
- D. Lim, Y.-S. Ong, Y. Jin, B. Sendhoff. Trusted evolutionary algorithms. Congress on Evolutionary Computation, pp.456-463, 2006
- L. Gräning, Y. Jin, B. Sendhoff. Generalization improvement in multi-objective learning. Int. Joint Conference in Neural Networks, pp.9893-9900, 2006
- Y. Jin, B. Sendhoff. Alleviating catastrophic forgetting via multi-objective learning. International Conference on Neural Networks, pp.6367-6374, 2006
- A. Zhou, Y. Jin, Q. Zhang, B. Sendhoff, E. Tsang. Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion. Congress on Evolutionary Computation, pp.3234-3240, 2006
- A. Zhou, Q. Zhang, Y. Jin, E. Tsang, T. Okabe. A model-based evolutionary algorithm for bi-objective optimization. Congress on Evolutionary Computation, pp.2568-2575, Edinburgh, September 2005
- V. Khare, X. Yao, B. Sendhoff, Y. Jin, and H. Wersing. Co-evolutionary modular neural networks for automatic problem decomposition. Congress on Evolutionary Computation, pp.2691-2698, Edinburgh, September 2005
- T. Okabe, Y. Jin, and B. Sendhoff. Theoretical comparisons of search dynamics of genetic algorithms and evolution strategies. Congress on Evolutionary Computation, pp.382-389, Edinburgh, September 2005
- T. Okabe, Y. Jin, and B. Sendhoff. A new approach to dynamics analysis of genetic algorithms without selection. Congress on Evolutionary Computation, pp.374-381, Edinburgh, September 2005
- Y. Jin, M. Olhofer, and B. Sendhoff. On evolutionary optimization of large problems with small populations. Int. Conf. on Natural Computation. LNCS 3611, pp.1145-1154, Springer, Changsha, China
- L. Gräning, Y. Jin, B. Sendhoff. Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study. European Symposium on Artificial Neural Networks. pp.273-278, Bruges, April 2005
- Y. Jin, B. Sendhoff, and E. Körner. Evolutionary multi-objective optimization for simultaneous generation of signal-type and symbol-type representations. The Third International Conference on Evolutionary Multi-Criterion Optimization. LNCS 3410, pp.752-766, Springer, Guanajuato, Mexico, March 9-11, 2005
- T. Okabe, Y. Jin, M. Olhofer, and B. Sendhoff. On test functions for evolutionary multi-objective optimization. Parallel Problem Solving from Nature, VIII, LNCS 3242, Springer, pp.792-802, September 2004
- T. Okabe, Y. Jin, B. Sendhoff and M. Olhofer. Voronoi-based estimation of distribution algorithm for multi-objective optimization. Congress Evolutionary Computation, pp. 1594-1602, Portland, 2004
- Y. Jin, T. Okabe and B. Sendhoff. Neural network regularization and ensembling using multi-objective evolutionary algorithms. Congress on Evolutionary Computation, pp.1-8, Portland, 2004
- Y. Jin and B. Sendhoff. Reducing fitness evaluations using clustering techniques and neural network ensembles. Genetic and Evolutionary Computation Conference. LNCS 3102, Springer, pp. 688-699, Seattle, 2004
- Y. Jin and B. Sendhoff. Constructing dynamic test problems using the multi-objective optimization concept. In: Applications of Evolutionary Computing. LNCS 3005, pp.525-536, Springer, 2004
- Y. Jin and B. Sendhoff. Connectedness, regularity and the success of local search in evolutionary multi-objective optimization. In: Congress on Evolutionary Computation, Vol.3, pp.1910-1917, 2003
- L. Willmes, Th. Bäck, Y. Jin and B. Sendhoff. Comparing neural networks and kriging in fitness approximation in evolutionary optimization. Congress on Evolutionary Computation, Vol.1, pp.663-670, 2003
- T. Okabe, Y. Jin and B. Sendhoff. A critical survey of performance indices for multi-objective optimization. Congress on Evolutionary Computation, pp.878-885, 2003
- T. Okabe, K. Foli, M. Olhofer, Y. Jin and B. Sendhoff. Comparative studies on micro heat exchanger optimization. In: Congress on Evolutionary Computation, Vol.1, pp.647-654, 2003
- T. Okabe, Y. Jin and B. Sendhoff. Evolutionary multi-objective optimization with a hybrid representation. In: Congress on Evolutionary Computation, Vol.4, pp. 2262-2269, 2003
- Y. Jin, T. Okabe and B. Sendhoff. Solving three-objective optimization problems using evolutionary dynamic weighted aggregation: Results and analysis. In: Genetic and Evolutionary Computation Conference, pp.636, Chicago, 2003
- Y. Jin and B. Sendhoff. Trade-off between performance and robustness: An evolutionary multi-objective approach. In: The Second International Conference on Evolutionary Multi-criteria Optimization. LNCS 2632, Springer, pp.237-251, Faro, 2003
- Y. Jin and B. Sendhoff. Fuzzy preference incorporation into evolutionary multi-objective optimization. In: Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution and Learning, Vol.1, pp.26-30, Singapore, Nov. 2002
- T. Okabe, Y. Jin, B. Sendhoff. On the dynamics of multi-objective optimization. In: Genetic and Evolutionary Computation Conference, pp. 247-256, New York, July 2002 (Best paper nomination)
- Y. Jin. Fitness approximation in evolutionary computation - A survey. In: Genetic and Evolutionary Computation Conference, pp.1105-1112, New York, July 2002
- Y. Jin and B. Sendhoff. Incorporation of fuzzy preferences into evolutionary multiobjective optimization. In: Proceedings of Genetic and Evolutionary Computation Conference, pp.683, New York, July 2002
- Y. Jin, M. Olhofer and B. Sendhoff. Managing approximate models in evolutionary aerodynamic design optimization. In: Congress on Evolutionary Computation, vol.1, pp.592-599. Seoul, Korea, May 2001
- M. Olhofer, Y. Jin and B. Sendhoff. Adaptive encoding for aerodynamic shape optimization using evolution strategies. In: Congress on Evolutionary Computation, vol.1, pp.576-583, Seoul, Korea, May 2001
- Y. Jin, M. Olhofer and B. Sendhoff. Dynamic weighted aggregation for evolutionary multi-objective optimization: Why does it work and how? In: Genetic and Evolutionary Computation Conference, pp.1042-1049, San Francisco, USA, 2001
- Y. Jin, T. Okabe and B. Sendhoff. Adapting weighted aggregation for multi-objective evolution strategies. In: The First International Conference on Evolutionary Multi-criterion Optimization. LNCS 1993, Springer, pp.96-110, Zurich, Switzerland, March 7-9, 2001
- Y. Jin, M. Olhofer and B. Sendhoff. On evolutionary optimization with approximate fitness functions. In: The Genetic and Evolutionary Computation Conference, Las Vegas, Nevada, USA. pp.786- 793, July 10-12, 2000
- A. Buczak, Y. Jin, H. Darabi and M. Jafari. Genetic algorithm based sensor network optimization for target tracking. Intelligent Engineering Systems through Artificial Neural Networks, Vol. 9, pp.349-354, 1999
- R. Burne, A. Buczak, Y. Jin, V. Jamalabad, I. Kadar and E. Eadan. A self-organizing, cooperative sensor network for remote surveillance: Current results. SPIE Proceedings of Unattended Ground Sensor Technologies and Applications, Vol.3713, pp.238-248, 1999
- Y. Jin, W. von Seelen and B. Sendhoff. An approach to rule-based knowledge extraction. In: IEEE International Conference on Fuzzy Systems, Anchorage, Alaska, pp.1188-1193, 1998
- Y. Jin, J. Zhu and J. Jiang. Fuzzy linearization of nonlinear systems. In: IEEE International Conference on Fuzzy Systems, pp.1688-1672, Orlando, Florida, USA, 1994
Refereed Journal Papers (in Chinese)
- Y. Jin, J.P. Jiang. Performance analysis of fuzzy controllers based on genetic algorithms. Pattern Recognition and Artificial Intelligence 10(1):75-80, 1997 (in Chinese)
- Y. Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings of Chinese Society of Electrical Engineering. 16(3):201-204, 1996 (in Chinese)
- Y. Jin and J.P. Jiang. Optimization of fuzzy control rules by means of genetic algorithms. Control and Decision, 11(6):672-676, 1996 (in Chinese)
- Y. Jin, J. Zhu. Neural network based fuzzy modeling and its simulation techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)
- Y. Jin, J.P. Jiang. Neuro-fuzzy control of robot manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)
- Y. Jin, J.P. Jiang. A neural network model with applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)
- Y. Jin, J.P. Jiang. Fuzzy logic integrated multivariable adaptive neuro-control. Information and Control, 23(4):223-228, 1994 (in Chinese)
- Y. Jin, J. Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Electronics Technology, 4:35-40, 1994 (in Chinese)
- Y. Jin, J. Zhu and J.P. Jiang. State estimation and adaptive control of multivariable systems using fuzzy logic and neural networks. AMSE Advances in Modeling and Analysis, 43(2), 1994
- Y. Jin, X. Shen. Two-level hierarchical intelligent fuzzy control of servo systems. Journal of Zhejiang University, 28(6):644-654, 1994 (in Chinese)
- Y. Jin, J.P. Jiang. Adaptive fuzzy prediction with application to weather forecast. Pattern Recognition and Artificial Intelligence, 6(4):283-290, 1993 (in Chinese)
- Y. Jin, J.P. Jiang. Neural network based non-linear feedback control. Journal of Zhejiang University, 27, 1993 (in Chinese)
- Y. Jin, J.P. Jiang. Fuzzy logic integrated variable structure control of a class of nonlinear systems. Control and Decision, 7(1):36-40, 1992 (in Chinese)
Edited Books / Conference Proceedings
- H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, and C. Grimme. (Eds.). 9th International Conference Evolutionary Multi-Criterion Optimization (EMO 2017), Münster, Germany, March 19-22, 2017
- Y. Jin and S. Kollias (Editors). 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 2016
- Y. Meng and Y. Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011
- Y. Jin and L. Wang (Editors). Fuzzy Systems in Bioinformatics and Computational Biology. Springer, Berlin Heidelberg, 2009
- S. Yang, Y.S. Ong, and Y. Jin (Editors). Evolutionary Computation in Dynamic and Uncertain Environments. Springer, Berlin Heidelberg, 2007
- Y. Jin (editor). Multi-Objective Machine Learning. Springer, Berlin Heidelberg. 2006
- L. Wang and Y. Jin (editors), 2005 International Conference on Fuzzy Systems and Knowledge Discovery. LNAI 3613, 3614, Springer, August 2005
- F. Rothlauf, J. Branke, S. Codnoni, D.W. Corne, R. Drechsler, Y. Jin, P. Machado, E. Marchiori, J. Romerero, G.D. Smith, G. Squillero (editors). Applications of Evolutionary Computing. LNCS 3449, Springer, March 2005
- Y. Jin (editor). Knowledge Incorporation in Evolutionary Computation. Springer, 2005
- G. Raidl, S. Cagnoni, J. Branke, D.W. Corne, R. Drechsler, Y. Jin, C.G. Johnson, P. Machado, E. Marchiori, F. Rothlauf, G.D. Smith, G. Squillero (editors). Applications of Evolutionary Computing. LNCS 3005, Springer, April 2004
Invited / Contributed Book Chapters
- H. Trautmann, G. Rudolph, K. Klamroth, O. Schütze, M. Wiecek, Y. Jin, and C. Grimme. (Eds.). 9th International Conference Evolutionary Multi-Criterion Optimization (EMO 2017), Münster, Germany, March 19-22, 2017
- Y. Jin and S. Kollias (Editors). 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 2016
- Y. Meng and Y. Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011
- Y. Jin and L. Wang (Editors). Fuzzy Systems in Bioinformatics and Computational Biology. Springer, Berlin Heidelberg, 2009
- S. Yang, Y.S. Ong, and Y. Jin (Editors). Evolutionary Computation in Dynamic and Uncertain Environments. Springer, Berlin Heidelberg, 2007
- Y. Jin (editor). Multi-Objective Machine Learning. Springer, Berlin Heidelberg. 2006
- L. Wang and Y. Jin (editors), 2005 International Conference on Fuzzy Systems and Knowledge Discovery. LNAI 3613, 3614, Springer, August 2005
- F. Rothlauf, J. Branke, S. Codnoni, D.W. Corne, R. Drechsler, Y. Jin, P. Machado, E. Marchiori, J. Romerero, G.D. Smith, G. Squillero (editors). Applications of Evolutionary Computing. LNCS 3449, Springer, March 2005
- Y. Jin (editor). Knowledge Incorporation in Evolutionary Computation. Springer, 2005
- G. Raidl, S. Cagnoni, J. Branke, D.W. Corne, R. Drechsler, Y. Jin, C.G. Johnson, P. Machado, E. Marchiori, F. Rothlauf, G.D. Smith, G. Squillero (editors). Applications of Evolutionary Computing. LNCS 3005, Springer, April 2004
Granted Patents
- Combining model-based and genetics-based offspring generation for mulit-objective optimization using a convergence criterion, US Patent No 7739206, 2010
- Fuzzy preferences in multi-objective optimization (MOO), US Patent No 7383236, 2008 / Japan Patent No 433510, 2009
- Estimation of distribution algorithm (EDA). US Patent No 7428514, 2008
- Multi-objective optimization, US Patent No 7363280, 2008
- Reduction of fitness evaluations using clustering techniques and neural network ensembles. European Patent No 1557788 / US Patent No 7363281, 2008
- Approximate fitness functions. US Patent No 7043462, 2006