Prateek was a Ph.D. student at the University of Oxford, supervised by Professor M. Pawan Kumar and co-supervised by Professor
Prateek's doctoral research is summarised as follows:
The impact of your work is substantial and multidisciplinary. For the field of Operational Research, your novel imitation learning framework has the potential to greatly enhance the efficiency and effectiveness of mixed-integer linear programming solvers. This could influence various industries that depend on such solvers, including logistics, manufacturing, and supply chain management, among others.
In terms of public health, your proactive contact tracing framework presents a significant advancement in infectious disease containment methods, providing a tool that intelligently estimates infection risk while preserving privacy. This development could drastically improve the effectiveness of contact tracing, leading to faster containment of infectious diseases and more informed decision-making.
Proactive Contact Tracing, PLOS Digital Health, 2023
Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, et al.
Lookback for Learning to Branch, TMLR, 2022
Prateek Gupta, Elias Khalil, Didier Chetélat, Maxime Gasse, Yoshua Bengio, Andrea Lodi, M. Pawan Kumar
Predicting Infectiousness for Proactive Contact Tracing, ICLR, 2021 (Top 15%)
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, et al.
Hybrid Models for Learning to Branch, NeurIPS, 2020
Prateek Gupta, Maxime Gasse, Elias B. Khalil, M. Pawan Kumar, Andrea Lodi, Yoshua Bengio
AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N, AAAI Climate Symposium, 2022
Tianyu Zhang, Andrew Williams, Soham Phade, Sunil Srinivasa, Yang Zhang, Prateek Gupta, Yoshua Bengio, Stephan Zheng
Deep Metric Learning: Revisiting Training & Generalization, ICML, 2020
Karsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen