My name is Krishan Rajaratnam and I’m data scientist and mathematician. I’ve always had a strong interest in mathematics, science, and technology, and I’m able to combine many of these interests in a career applying machine learning.

I finished my PhD at the University of Toronto under Professor Israel Michael Sigal studying the mathematical theory behind the Fractional Quantum Hall Effect (thesis available here). I also did a Master’s thesis at the University of Waterloo under Professor Dong Eui Chang and Professor Raymond G. McLenaghan studying and developing the mathematical theory behind the orthogonal separation of the Hamilton-Jacobi equation on spaces of constant curvature (thesis available here).

Besides my technical interests, I generally have a growth mindset and am interested in staying fit, with hobbies like biking, running, and weight lifting as well as photography.

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