Associate Professor & CIFAR AI Chair
Department of Mathematics, University of British Columbia (UBC)
About
Dr. Elina Robeva leads the “Causal Discovery from Real-World Data” theme. She brings profound expertise in machine learning and modeling complex data dependencies using algebra, geometry, and combinatorics. Her leadership ensures robust mathematical foundations across the cluster’s research initiatives. Dr. Robeva is highly decorated in her field, holding a CIFAR AI Chair and having received numerous accolades, including the Bernard Friedman Memorial Prize in Applied Mathematics, the SIAM Algebraic Geometry Early Career Award, the André-Aisenstadt Prize, and the UBC Mathematical Sciences Young Faculty Award. She is a recognized advocate for Women in STEM.
Publications
- Kubjas K, Kuznetsova O, Robeva E, Semnani P, Sodomaco L. Log-concave density estimation in undirected graphical models. Bernoulli 2024 (Accepted).
- Liu Y, Robeva E, Wang H. Learning linear non-Gaussian graphical models with multidirected edges. Journal of Causal Inference 2021;9(1):250-63.
- Drton M, Robeva E, Weihs L. Nested covariance determinants and restricted trek separation in Gaussian graphical models. Bernoulli 2020;26(4):2503-40.