I am a Ph.D. candidate in Machine Learning at the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology, advised by Prof. Nagi Gebraeel. My research focuses on decentralized learning and causal reasoning in interconnected cyber-physical systems. Specifically, I develop theoretical and algorithmic foundations for causal learning and inference in distributed and heterogeneous industrial settings. My work emphasizes causal discovery, uncertainty quantification, counterfactual reasoning, and root cause analysis under anomaly.

A brief background: I graduated from the Indian Institute of Technology (IIT) Kharagpur, India with a B.S. in Manufacturing Science and Engineering and a M.S. in Industrial Engineering and Management. Building on this foundation in manufacturing, I transitioned into machine learning for large-scale industrial systems. This interdisciplinary experience now informs my research on data-driven methods for complex engineering environments.

You can reach me at ayush.mohanty@gatech.edu.