Dr Matthew Thorpe

Lecturer in Applied Mathematics

Affiliations:
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Overview

I have two main research interests: The first is in the application of methods from the calculus of variations to analyse large data limits of problems that arise from machine learning and statistics. The second is in the application and development of optimal transport distances to signal and image analysis.

Currently I am a co-organiser for the One World Seminar Series on the Mathematics of Machine Learning and an editor for the journal Foundations of Data Science.

I am also a part of the Cambridge led project on AI assisted diagnosis and prognostication in Covid-19, and the European Union's Horizon 2020 program NoMADS (grant agreement number 777826).

Further information

I can be contacted at matthew[dot]thorpe[dash]2@manchester[dot]ac[dot]uk.

External positions

Research Fellow, University of Cambridge

1 Sep 2017 → 29 Feb 2020

Postdoctoral Associate, Carnegie Mellon University

1 Sep 2015 → 31 Aug 2017

Keywords

  • Machine Learning, Calculus of Variations, Statistics, Optimal Transport

Related information

Publications

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

Research output: Contribution to journal › Article › peer-review

Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms

Research output: Contribution to journal › Article › peer-review

Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

View all (13)