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Sushant Sachdeva is an Associate Professor at the University of Toronto Mississauga and a faculty member at the Vector Institute. He has a distinguished academic career with various notable positions, including a visitor role at the Institute for Advanced Study from 2016 to 2017 and as a research scientist at Google from 2014 to 2016. He completed his Ph.D. in Computer Science at Princeton University and has held postdoctoral positions at the Simons Institute and Yale University. His research interests lie in algorithms, particularly in designing fast algorithms and mathematical machine learning, emphasizing optimization, representation learning, and mixing Markov chains. He actively supports MSc and PhD students with a strong background in computer science and mathematics, guiding them through projects related to model training and learning efficiency. His contributions to the field have been recognized with multiple awards, including the Sloan Research Fellowship and prestigious paper awards at leading conferences in computer science.
University of Toronto Mississauga • Toronto, ON, Canada
Teaching and research in computer science, focusing on algorithms and machine learning.
Institute for Advanced Study • Princeton, NJ, USA
Conducted research on algorithms and optimization.
Google • Mountain View, CA, USA
Worked on machine learning and algorithm design.
Yale University • New Haven, CT, USA
Research in the field of mathematics and computer science related to algorithms.
Department of Sociology