Dr. Atin Basuchoudhary is the Roberts Professor of Free Enterprise Economics at Virginia Military Institute, where he has taught since 1998. His research bridges machine learning methodology, conflict economics, and responsible AI — with a focus on making AI systems interpretable, auditable, and subject to meaningful human oversight. He is the lead author of three books on causal machine learning (Springer, Palgrave, Lexington Books) and co-editor of the recently published Cambridge Handbook of the Economics of Terrorism (Cambridge University Press, 2026). His work has appeared in the Eastern Economic Journal, Computers and Security, Games, Defense and Peace Economics, Public Choice, and EBioMedicine (The Lancet).
Dr. Basuchoudhary has secured competitive external funding, including a DoD Minerva Initiative/NSF grant for adversarial behavior modeling and conflict prediction. He is a recurring instructor in the Cybersecurity Strategy Program at the French Military Academy (École spéciale militaire de Saint-Cyr, 2015–2023), and a Fellow of its Center for Economic Analysis of Conflict. He participated in the Wargaming Initiative for NATO 2023 (WIN 23) in Rome and has briefed senior analysts at RAND, the Institute for Defense Analyses (IDA), and DoD defense economics panels.
At VMI, in addition to transformative stints as chair of the Faculty Development Committee and the Tenure and Promotions committee, Dr. Basuchoudhary has been instrumental in leading three consecutive 5-year AACSB accreditation cycles, helping to develop the Decision Analytics concentration (launched Fall 2024) and a Cybersecurity minor, and deploying custom GPT-based coaching systems. He completed the MIT Sloan School of Management / CSAIL AI for Business Strategy Program in 2024–2025. He serves on the Science Advisory Boards of multiple AI governance organizations, was an invited participant at the AlphaPersuade Conference on Ethical AI Guidelines at UCI (2024), and has appeared as a featured expert on NPR’s “With Good Reason” multiple times.
Academic Interests: Dr. Basuchoudhary’s research spans causal machine learning for policy-relevant prediction and risk analysis, the economics of terrorism and civil conflict, responsible and interpretable AI, cybersecurity strategy, and game-theoretic models of adversarial behavior. He applies ensemble ML methods (BART, Random Forest, Neural Networks) with Pearl’s DAG-based causal inference frameworks and Shapley value decomposition to build transparent, human-auditable predictive models. This methodology extends to medical outcomes research (ketogenic diet and epilepsy, EBioMedicine 2022) and small-business financial analytics