# Deep Learning

## About

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

## 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

COLMAN Owen

LI Hui

LIU Jayson

TRINH Allan

ZHANG Jiyuan

## Honours & Masters (RT) Students

ANAGNOSTOU Lukas

PRYOR Robert

QUAN Yiran

SAVVINOS Alexius

TROIANI William

YANG Yijing

ZHU Yaoyao