Dr. Reza Ramezan is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, where he is also a core member of the institution’s Centre for Theoretical Neuroscience. His work bridges statistical methodology, data science, and neuroscience. His main research is in computational neuroscience where he develops computationally efficient stochastic, multivariate, and high-dimensional models for neural spike trains, with the broader goal of understanding how information is encoded and communicated in the brain. He also collaborates on applied research in behavioural neuroscience, health sciences, paleoclimatology, and other interdisciplinary fields. Dr. Ramezan earned his PhD in Statistics from the University of Waterloo in 2014. He subsequently joined the Department of Mathematics at California State University, Fullerton as an Assistant Professor of Statistics before returning to Waterloo in 2017. His professional leadership includes serving as President of the Business and Industrial Statistics Section of the Statistical Society of Canada in 2022. He has received numerous awards and recognitions for both his teaching and research activities. In 2026, he and his collaborators received the Canadian Journal of Statistics Award for their work on fast and scalable inference for spatial extreme-value models.