My research area is machine learning, an approach to Artificial Intelligence that relies on
learning from data, rather than explicit instructions.
I'm broadly interested in inference within structured, complex and combinatorial domains using
graphical and structured deep models.
In addition to its potential role in artificial general intelligence, our ability to draw inference in structured domains,
is essential in a data-driven approach to science.
Before joining the Computer Science Department at UBC in the summer of 2017,
I was a postdoctoral fellow at
Machine Learning Department and Robotics Institute at Carnegie Mellon University, where I worked with Barnabás Póczos and Jeff Schneider .
I was affiliated with the Auton Lab and the McWilliams Center for Cosmology.
I obtained my M.Sc. and Ph.D. at University of Alberta, advised by
Russell Greiner. There, I was affiliated with
Alberta Ingenuity Center for Machine Learning (now amii) as well as
The Metabolomics Innovation Centre.
Before that, I received my B.Sc. from Sharif University.