Hamsa Sridhar Bastani
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Associate Professor of Operations, Information, and Decisions Co-Director of Wharton Healthcare Analytics Lab Contact557 Jon M. Huntsman Hall |
Bio
I am an Associate Professor of Operations, Information, and Decisions (OID) as well as Statistics and Data Science at the Wharton School of the University of Pennsylvania, where I co-direct the Wharton Healthcare Analytics Lab. My research focuses on developing novel machine learning algorithms for learning and optimization, including methods for sequential decision-making (bandits, reinforcement learning, active learning), learning from auxiliary data sources (transfer learning, meta-learning, surrogates), and designing effective human–AI interfaces (interpretability, fairness). Recently, I have been exploring how AI systems affect and augment human behavior, with the goal of designing AI tools that help humans thrive.
I am passionate about applying machine learning and AI to tackle high-impact societal problems across domains like healthcare, public policy, and education. I have worked closely with national governments to deploy algorithms at the country scale for improving public health outcomes. For example, I collaborated with the Government of Greece to nearly double the efficacy of their national border COVID-19 screening via reinforcement learning, and with the Government of Sierra Leone to improve patient access to essential medicines by nearly 20% via decision-aware learning. Moreover, I co-led the first large field study deploying generative AI tutors in high school math classes, demonstrating critical risks for human overreliance and deskilling. My recent work continues to use a combination of field evidence from randomized controlled trials and theoretical models to inform the careful design necessary for effective human-AI collaboration.
My research has been published in leading outlets including Nature, Management Science, Operations Research, and PNAS, and has garnered numerous recognitions, including the Wagner Prize for Excellence in Operations Research, the INFORMS Pierskalla Award for best healthcare paper, and the George Nicholson Prize. Previously, I graduated summa cum laude from Harvard in 2012 with a A.M. in physics, and a A.B. in physics and mathematics, completed my PhD in Stanford's Electrical Engineering department under the supervision of Mohsen Bayati, and spent a year as a Herman Goldstine postdoctoral fellow at IBM Research.
I primarily teach OIDD 321: Introduction to Management Science, for which I received multiple Wharton Teaching Excellence Awards. I currently serve as an Associate Editor for Operations Research, M&SOM and OR Letters. I serve on the Steering Committee for the Penn Center for Health Incentives and Behavioral Economics and on the statistics advisory committee for the AHA Food is Medicine Initiative. Outside academia, I serve on the Workday AI Advisory Board.
Selected Papers
Bastani, Bastani, Sungu, et al. Generative AI Without Guardrails Can Harm Learning: Evidence from High School Mathematics, PNAS (2025).
Chung et al. Improving Access to Essential Medicines in Sierra Leone via Decision-Aware Machine Learning, Revise & Resubmit, Nature.
Bastani, Drakopoulos, Gupta, et al. Efficient and Targeted COVID-19 Border Testing via Reinforcement Learning, Nature (2021).
Ge, Bastani, and Bastani. Rethinking Algorithmic Fairness for Human-AI Collaboration, preliminary version in ITCS (2024).
Anderer, Bastani, and Silberholz. Adaptive Clinical Trial Designs with Surrogates: When Should We Bother?, Management Science (2022).
Ramchandani, Bastani, and Wyatt. Unmasking Human Trafficking Risk in Commercial Sex Supply Chains with Machine Learning, M&SOM (2025).
Bastani, Bastani, and Sinchaisri. Improving Human Sequential Decision-Making with Reinforcement Learning, Management Science (2025).
Xu and Bastani. Multitask Learning and Bandits via Robust Statistics, Management Science (2025).
Bastani, Simchi-Levi, and Zhu. Meta Dynamic Pricing: Transfer Learning Across Experiments, Management Science (2021).
Bastani. Predicting with Proxies: Transfer Learning in High Dimension, Management Science (2021).
Bastani, Bayati, and Khosravi. Mostly Exploration-Free Algorithms for Contextual Bandits, Management Science (2021).
Bastani and Bayati. Online Decision-Making with High-Dimensional Covariates, Operations Research (2020).