Research Group Details

Deep Learning


Deep learning studies a class of algorithms, based on artificial neural networks, that learn representations from data and compute with those representations. These algorithms are simple and perform remarkably well in tasks across computer vision, speech recognition, natural language processing and many other areas, including the natural sciences. The search for a theory of deep learning raises many new and difficult problems for mathematicians.

Group website

Deep Learning website

Academic Staff

Dr Jesse GELL-REDMAN (Lecturer)
Research interests: Microlocal analysis, Partial Differential Equations, Differential geometry
Dr Mingming GONG (Lecturer)
Research interests: Machine Learning, Causal Reasoning, Computer Vision
Dr Daniel MURFET (Lecturer)
Research interests: Mathematical logic, Algebraic geometry, Topological field theories
Dr Thomas QUELLA (Senior Lecturer)
Research interests: Representation Theory and Applications, Conformal field theory, quantum integrable models, Topological states of matter, tensor network states, Lie (super) algebras, diagram algebras, quantum groups, Quantum many-body physics
Dr Susan WEI (Lecturer)
Research interests: Statistical inference for big data, Machine Learning, Data Science

Postgraduate Students

LI Hui
LIU Jayson

Honours & Masters (RT) Students

BEAR Vivian
MEAD William
PRYOR Robert
QUAN Yiran
YANG Yijing
ZHU Yaoyao