Mahdi Haghifam

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Ph.D. candidate,
University of Toronto‬, Vector Institute‬
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Email: mahdi dot haghifam AT

Short Bio

I am a PhD candidate in Electrical and Computer Engineering at University Toronto and a graduate student researcher at Vector Institute‬. I am honored to be advised by Prof. ‪Daniel M. Roy‬. I also work closely with Dr. Gintare Karolina Dziugaite‬. I received my B.Sc. and M.Sc. degrees in Electrical Engineering from Sharif University of Technology in 2014 and 2016 respectively.
Previously, I was a research intern at Element AI‬ in Winter 2019 and Fall 2020. In early 2020, I was a visiting student at Institute of Advanced Study‬ (IAS) for special-year program on Optimization, Statistics, and Theoretical Machine Learning.

Research Interests

My research focuses broadly on information theory and statistical learning theory. In particular, I have been working on several areas of Generalization Theory in Machine Learing with a focus on deriving provable guarantees for Machine Learing methods using information-theoretic tools. I am also interested in the interplay between information theory and statistics, and understanding the fundamental limits of high-dimensional statistics using the techniques rooted in information theory. For a complete list of my publications, please visit the Publications page.