Hi! I’m interested in leveraging large-scale data and system design to solve challenging problems. I have worked both on the research and on production software-engineering aspects of city-scale visual SLAM for augmented reality, large-scale visual perception pipelines and on data-driven prediction and planning for autonomous driving. I currently work on leveraging graph learning for decoding complex biology - both on the machine learning and engineering aspects.
Paul Bertin, Jarrid Rector-Brooks, Deepak Sharma, Thomas Gaudelet, Andrew Anighoro, Torsten Gross, Francisco Martinez-Pena, Eileen L. Tang, Suraj M S, Cristian Regep, Jeremy Hayter, Maksym Korablyov, Nicholas Valiante, Almer van der Sloot, Mike Tyers, Charles Roberts, Michael M. Bronstein, Luke L. Lairson, Jake P. Taylor-King, Yoshua Bengio, RECOVER: sequential model optimization platform for combination drug repurposing identifies novel synergistic compounds in vitro, arXiv pre-print, arXiv:2202.04202
Suraj M S, Hugo Grimmett, Lukáš Platinský and Peter Ondrúška, Visual vehicle tracking through noise and occlusions using crowd-sourced maps, Spotlight talk, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), October, 1- 5, 2018 Madrid, Spain
Suraj M S, Hugo Grimmett, Lukáš Platinský and Peter Ondrúška, Predicting trajectories of vehicles using large-scale motion priors, Oral presentation, 2018 IEEE Intelligent Vehicles Symposium (IV) Changshu, Suzhou, China, June 26-30, 2018