Debabrata Mahapatra is a research scientist with a decade of experience bridging theory and production in machine learning, currently at Adobe after roles at Amazon and a PhD at NUS. He has a strong publication record (5 conferences, 1 journal R&R, 2 preprints) and practical impact—designing and shipping a fair search-ranking model during a 3-month Amazon internship that became a KDD paper. His doctoral work solved a fundamental issue in non-convex multi-objective optimization, proving linear convergence to preferred Pareto optima and improving multi-task learning on real problems like drug response prediction. He is an effective communicator and mentor, having taught 15 graduate tutorials, presented at international conferences, and supervised four student projects. Notably, he combines solid systems experience (AWS, LightGBM/C++) with deep theoretical contributions, enabling him to take research ideas from proposal to large-scale experiments.
10 years of coding experience
8 years of employment as a software developer
Master’s Degree, System Science & Automation, jointly offered by 2 departments: CS and EE., 8/8 for research project and 7.2/8 for courseworks, Master’s Degree, System Science & Automation, jointly offered by 2 departments: CS and EE., 8/8 for research project and 7.2/8 for courseworks at Indian Institute of Science
Bachelor’s Degree, Electrical and Electronics Engineering, 8.6 out of 10, Bachelor’s Degree, Electrical and Electronics Engineering, 8.6 out of 10 at National Institute of Technology Rourkela
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at National University of Singapore
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