Matt J. Kusner is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds additional affiliations as a Senior Academic Member at Mila - Quebec Artificial Intelligence Institute and as a Member at the Institute for Data Valorization (IVADO). Previously, he served as an Associate Professor at University College London and the University of Oxford. Professor Kusner's research spans machine learning, with particular focus on causal inference, fairness in algorithms, representation learning, and domain adaptation. His work bridges theoretical foundations with practical applications in natural language processing, algorithmic fairness, and scientific computing domains including plasma physics and renewable energy systems. His research interests include Pattern Analysis and Artificial Intelligence, Algorithms, and Learning and Inference Theories. His publication record shows consistent output across top machine learning venues including NeurIPS, ICML, and ICLR, with recent work trending toward causal machine learning methods and applications in scientific domains. Professor Kusner has 42 publications spanning from 2014 to 2025, demonstrating sustained research productivity. Turner Dissertation Award for best doctoral dissertation in Computer Science & Engineering Professor Kusner received his PhD in Computer Science from Washington University in St. Louis in 2016 under Kilian Weinberger. His work has been featured in major media outlets including The Guardian, Forbes, and the Harvard Business Review, and he has presented at prestigious institutions including the Federal Reserve Banks, Cambridge Centre for Mathematical Sciences, and the Royal Society.