Elina Robeva
Department of Mathematics at UBC • Office MATX 1106 • erobeva@math.ubc.ca
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I am an Assistant Professor at the Department of Mathematics in the University of British Columbia in beautiful Vancouver, British Columbia. I am a member of the Institute of Applied Mathematics and CAIDA.

My research lies at the intersection of mathematical statistics, machine learning, combinatorics, multilinear algebra, and applied algebraic geometry. I particularly enjoy discovering mathematical structure which is inherently responsible for the successful solution to a statistical problem. I develop machine learning and optimization methods for inference in models that depict complex dependencies in data. I address situations in which many commonly made yet unrealistic assumptions do not hold by leveraging the mathematical structure of the model at hand. My work spans causal inference, graphical models, tensor decomposition, non-parametric density estimation, hidden variable models, and super-resolution imaging. For example, I develop theory and algorithms for:

  • causal inference for observational data (both temporal and non-temporal) in the presence of hidden variables and causal feedback loops;
  • tensor decomposition applied to machine learning problems;
  • sparse inverse problems, such as super-resolution imaging;
  • high-dimensional, non-parametric density estimation leveraging dependencies between the variables.

In addition to traditional tools from applied mathematics, I utilize algebra, geometry, and combinatorics, which often depict the structure of the models at hand. I have recently started collaborating with climate scientists to infer causal relationships among climate variables from time series data.

Here is a link to my CV.

Prior to joining UBC I was priviliged to spend three years as a Statistics Instructor and an NSF Postdoctoral Fellow in the Department of Mathematics and the Institute for Data, Systems, and Society at MIT.

In the spring of 2016 I received my PhD in mathematics from UC Berkeley under the supervision of Bernd Sturmfels. Here is a link to my thesis, which won the Bernard Friedman Memorial prize in applied mathematics.

In 2011 I received my BS with Honors in mathematics and a minor in computer science from Stanford University.


RECENT NEWS:

  • I have been awarded the Andre Aisenstadt Prize this year.
  • Our paper with Bakytzhan Kurmanbek Multivariate Super-Resolution without Separation has been accepted to Information and Inference!
  • May 2023: Pardis Semnani has won the Lorraine Schwartz Prize at UBC this year!
  • May 2023: Our BIRS Oaxaca Workshop on Computations and Data in Algebraic Statistics was great!
  • May 2023: Pardis Semnani and I have a new preprint on Causal Inference in Directed, Possibly Cyclic, Graphical models.
  • May 2023: I have been awarded the Andre-Eisenstadt Prize this year.
  • May 2023: Two undergraduates join the group this summer: Joshua Boyd (USRA) and Young Lin (WLIURA).
  • April 2023: Three new graduate students will join the group starting next year! Vince Guan will join for his PhD, Cole Gigliotti and Hossein Rahmani will join for their MSc's!