Research Interests

I am a probabilist working primarily on problems coming from data science, statistics, and physics. I am particularly interested in the implementation and study of efficient algorithms for optimizing and sampling from complex high dimensional energy landscapes. These includes examples such as the loss landscape arising in statistical inference, or Gibbs’ measures of disordered media (spin glasses).

Bio

I received a B.Sc. in mathematics from the University of Toronto in 2021, and received my Ph.D. from Northwestern University in 2026.

My Ph.D. was supervised by Tuca Auffinger and Reza Gheissari.

I am currently a postdoctoral fellow at the University of Waterloo, in the department of Statistics and Actuarial Sciences.

My CV can be found here.

Contact me

For Math related inquiries contact me at: cgrant(dot)math(at)gmail(dot)com

For any others: curtis(dot)grant(at)uwaterloo(dot)ca