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Siamak Ravanbakhsh

Assistant Professor,
School of Computer Science, McGill University
Room 325, McConnell Engineering Building
3480 University Street, Montreal, Quebec, Canada

E-mail: 

Research

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.


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Teaching

COMP 767-002: Probabilistic Graphical Models (Fall 2019)
CPSC 532R (at UBC) : Advanced Topics in AI: Graphical Models (Winter 2018)

Short Bio

Before joining McGill’s School of Computer Science, I held a similar position at the University of British Columbia. Before that, I was a postdoctoral fellow at the Machine Learning Department and the Robotics Institute at the Carnegie Mellon University, where I worked with Barnabás Póczos and Jeff Schneider. I received my M.Sc. and Ph.D. from the University of Alberta, as a member of Alberta Ingenuity Center for Machine Learning, now amii, working with Russ Greiner. During this time, I also spent a few months at Frey Lab, at the University of Toronto. Prior to that, I received my B.Sc. from Sharif University.