Alex Guangyuan Wang

Hi! I'm Alex, a final year Joint Honours Mathematics and Computer Science student at McGill University.

I've done research on machine learning as well as pure and applied mathematics. Specifically, the topics I have explored are designing deep exploration and posterior sampling algorithms in reinforcement learning, artificial intelligence feedback and reward alignment, high-dimensional stochastic optimization with connections to random matrices and non-commutative probability theory, and singularity formation detection in evolutionary PDEs using neural operators.

I have been very fortunate to be advised by Professors Doina Precup, Elliot Paquette, Siamak Ravanbakhsh, and Tim Hoheisel at McGill University, Mila - Québec AI Institute and Centre de recherches mathématiques. I have also been working closely with Professor Anima Anandkumar's research group at Caltech CMS.

Research

Broadly speaking, my current interests include reinforcement learning, high-dimensional optimization, AI for science, generative models, and machine learning theory. Feel free to reach out to me in case you have any questions or want to chat about research!

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