Matt J. Kusner

Also known as Matt Kusner

Matt J. Kusner is a machine learning researcher whose work covers algorithmic fairness, causal inference and the evaluation of learning systems. He presented the Word Mover's Distance at ICML in 2015 with Yu Sun, Nicholas Kolkin and Kilian Weinberger, finished a PhD under Weinberger in 2016, and joined the first cohort of Research Fellows at the Alan Turing Institute. After coauthoring Counterfactual Fairness and the Grammar Variational Autoencoder in 2017, he held associate professorships at Oxford and University College London, received a Royal Society Leverhulme Trust Senior Research Fellowship in 2024–2025 and was appointed a Canada CIFAR AI Chair in 2025. He is an associate professor at Polytechnique Montréal and a core academic member at Mila.

Now at: Polytechnique Montréal and Mila

Timeline

2015

The Word Mover's Distance

At ICML in 2015, he presents the Word Mover's Distance with Yu Sun, Nicholas Kolkin and Kilian Weinberger. The metric measures the dissimilarity between two text documents as the minimum distance that the embedded words of one document must travel to reach the embedded words of the other.
2016

PhD at Washington University

He holds a BA in computer science and mathematics from Macalester College and completes a PhD in computer science at Washington University in St. Louis in 2016, supervised by Kilian Weinberger. His dissertation wins the Turner Dissertation Award for best doctoral dissertation in computer science and engineering.
2016–2018

Turing Institute Research Fellow

He is part of the first cohort of Research Fellows at the Alan Turing Institute in London. The fellowship runs from 2016 to 2018.
2017

Counterfactual fairness and Grammar VAE

In 2017, he coauthors Counterfactual Fairness with Joshua Loftus, Chris Russell and Ricardo Silva, a framework that models fairness with tools from causal inference and is demonstrated on predicting success in law school. He also coauthors the Grammar Variational Autoencoder with Brooks Paige and José Miguel Hernández-Lobato, a model that encodes and decodes the parse trees of a context-free grammar so that generated outputs are always valid.
By 2019

Associate professor at Oxford

He is an associate professor in the University of Oxford's Department of Computer Science, working on artificial intelligence and machine learning, and a tutorial fellow at Jesus College. He leaves the department in August 2019.
2020

Associate professor at UCL

In 2020, he is an associate professor in the Department of Computer Science at University College London and a fellow at the Alan Turing Institute. With Joshua Loftus, he publishes the Nature comment "The long road to fairer algorithms" in February 2020, which calls for models that identify and mitigate the causes of discrimination.
2024–2025

Royal Society fellowship and CIFAR Chair

He holds a Leverhulme Trust Senior Research Fellowship from the Royal Society in 2024–2025. In December 2025, Mila announces his appointment as a Canada CIFAR AI Chair, with research on privacy and regulation and on the foundations of machine learning evaluation.
As of October 2026

Polytechnique Montréal and Mila

He is an associate professor in the Department of Computer and Software Engineering at Polytechnique Montréal, a core academic member at Mila and a member of ELLIS. His research interests are in the fundamentals of machine learning evaluation and machine learning for society, and he teaches ML Evaluation: Post-Deployment Auditing in Fall 2026.