Setareh Cohan is a PhD student and graduate research assistant at the University of British Columbia with nine years of experience at the intersection of machine learning, reinforcement learning, and computer vision. She develops intelligent agents for character motion, control and planning using deep RL and generative models (including diffusion models), and has applied graph-based sequence modeling to sports trajectory prediction. Her industry experience includes research at Borealis AI where she integrated probabilistic and selective prediction methods for regression at scale. Comfortable both designing new model architectures and running large-cluster experiments, she bridges theory and practical implementation under advisors Michiel van de Panne, Jim Little, and Leonid Sigal. Based in Vancouver, she combines rigorous academic training with hands-on engineering to push applications of deep RL into character animation and planning.
9 years of coding experience
2 years of employment as a software developer
Regular/General High School/Secondary Diploma Program, mathemati, Regular/General High School/Secondary Diploma Program, mathemati at Farzanegan Highschool
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of British Columbia
Bachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at Sharif University of Technology
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.