People-centred multimodal perception

This project aims to develop fundamental machine learning and AI techniques with multimodal perception abilities to ingest large-scale and heterogenous information data. The objective is to enable a machine system to draw the underlying/latent intelligence and knowledge predictive for the future via interpreting and reasoning about abundant multimodal information sources, reminiscent of human perception but at the level of scalable machine computing. A potential topic (not limited to) is AI journalism which consumes 24/7 social media streams at scale to provide useful insights with enormous positive social and human wellbeing impact. The fundamental people-centred factors (e.g., fairness, accountability, transparency, and ethics) will be well considered.

Candidates with a strong mathematics background, machine learning, programming skills, and relevant research experience including peer-review-based publication are preferred.

All applicants should have (or expect to obtain) a first-class degree in a numerate discipline (mathematics, science or engineering) or MSc with Distinction (or 70% average) and a strong interest in pursuing research in this field. Additional experience which is relevant to the area of research is also advantageous.

IELTS requirements: IELTS 6.5 or above (or equivalent) with no sub-test of less than 6. 

This studentship is open to UK, EU and international students. 

Surrey Institute for People-Centred AI