Elina Robeva

Elina Robeva is an Assistant Professor in the Department of Mathematics at the University of British Columbia (UBC), effective until July 2025, when she will be promoted to Associate Professor. She is affiliated with the Institute of Applied Mathematics, CAIDA, and holds the titles of AMII Fellow and Canada CIFAR AI Chair. Her research focuses on the intersection of mathematical statistics, machine learning, combinatorics, and applied algebraic geometry, with an emphasis on causal inference, graphical models, and tensor decomposition.

Education: She earned her PhD in Mathematics from UC Berkeley (2016), advised by Bernd Sturmfels, and a BS with Honors in Mathematics from Stanford University (2011). Prior to UBC, she was an NSF Postdoctoral Fellow and instructor at MIT (2016–2019).

Research Interests: Her work bridges algebraic methods with statistical problems, including causal discovery in linear models, tensor decomposition applications in machine learning, and super-resolution imaging. She employs algebraic geometry and combinatorics to uncover structural insights in statistical problems.

Awards: Recipient of the Andre Aisenstadt Prize (2024), Bernard Friedman Memorial Prize (2016), and Vanier Canada Graduate Scholarship (for student Pardis Semnani). She is also a Canada CIFAR AI Chair and AMII Fellow.

Advising & Mentorship: She has mentored numerous students, including PhD candidates (e.g., Pardis Semnani), MSc students, and undergraduates through programs like NSERC USRA and MITACS. Notable collaborations include work on causal inference, log-concave density estimation, and tensor networks.

Labs/Teams: Active in interdisciplinary research groups at UBC and collaborates internationally through programs like the Institute for Mathematical and Statistical Innovation (IMSI).