Machine Learning and Optimisation

Machine Learning is revolutionising the world.  It is difficult to think of a technology that has progressed so rapidly, in terms of real-world impact.  Our group is interested in new theory, metholodogies, and cross-discipline scientific impact, as well as consumer-driven applications.

Dr Jon Shapiro (Group lead)
Reinforcement learning, game theory, Bayesian methods.
Prof Gavin Brown
Information theoretic methods, feature selection, deep learning, applications in health.
Dr Ke Chen
Deep learning, vision and speech representations, zero-shot learning, game AI.
Dr Tingting Mu
Representation and metric learning, relational data analysis, NLP/vision.
Dr Xiaojun Zeng
Big Data analytics, deep learning, fuzzy systems, applications in finance, energy, and health.
Prof Ross King
Automation of science, inductive logic programming.

Advanced Data Analytics Seminar Series


We are proud to host leading researchers as they present their recent advances in ML and Computational Statistics.
We are maintain cross-discipline collaborations with areas of interest to modern Machine Learning, including high-performance hardware for computer vision and neuro-morphic computing. We are part of a wider University Data Science Institute - see some more details of ML across the university here.   Some of our community groups are linked below, though Manchester is diverse and ever-changing, as such this list non-exhaustive.
 
Health Data AnalyticsImage AnalyticsComputational StatisticsText Analytics
Prof Magnus Rattray
Dr Niels Peek
Prof Richard Emsley
The e-Health Research Centre

 

 Prof Tim Cootes
Dr Neil Thacker
Prof Chris Taylor FREng OBE

 

Dr Thomas House
Dr Christiana Charambous
Probability and Stats Group

 

Prof Goran Nenadic
Prof Sophia Ananiadou

 

 
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