Summary
Aurghya Maiti is a researcher and PhD candidate in Computer Science at Columbia University with eight years of experience focused on causality, bandits, and reinforcement learning, particularly for decision-making and recommendation systems. He has held multiple research roles at Adobe Research where he developed algorithms for Bayesian network generation, disentangling mixture interventions, time-series analysis, and bandit-based decision policies. At Columbia he works with Prof. Elias Bareinboim on causal decision-making, bridging theoretical causal inference with practical applications in recommendations and insights generation. An IIT Kharagpur alumnus with a strong academic record, he combines rigorous theory with hands-on algorithm design and production-minded research experience across industry and academia.
8 years of coding experience
2 years of employment as a software developer
Class XII, Class XII at Nava Nalanda
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Columbia University
Bachelor of Technology, Computer Science, Bachelor of Technology, Computer Science at Indian Institute of Technology, Kharagpur
English, Bengali, Hindi