Summary
Abishek Sankararaman is a Senior Machine Learning Scientist in San Francisco with 11 years of experience building principled online adaptive algorithms that harness large, fast streaming unlabeled data for detection, estimation, and decision making. He designs and ships fast unsupervised anomaly-detection systems at AWS (including algorithms used for GuardDuty RDS protection) and has a strong theoretical backbone from a PhD in applied math/electrical engineering and postdoctoral work at UC Berkeley. His research spans sequential decision making (bandits, RL), random geometric structures, and multi-agent networks, combining rigorous theorems with practical deployments. A prolific researcher with publications across mathematics, CS, and EE, he often translates abstract probabilistic and combinatorial insights into production-grade systems. Notably, his work bridges decentralized multi-agent learning and real-time cloud detection, reflecting both deep theory and applied product impact. He credits mentors and collaborators for much of his success, signaling a collaborative, mentor-driven approach to research and engineering.
11 years of coding experience
7 years of employment as a software developer
Indian Institute of Technology Madras
Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering, Applied Mathematics, Doctor of Philosophy (Ph.D.), Electrical and Computer Engineering, Applied Mathematics at The University of Texas at Austin
c++, python, python