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 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. I develop 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, nudges). I am also passionate about applying these techniques to tackle impactful societal problems, and have worked closely with national governments to deploy algorithms at the country-scale to improve public health outcomes. For example, I worked with the Government of Greece to improve their national border COVID screening via reinforcement learning, and the Government of Sierra Leone to improve their national essential medicine distribution via decision-aware learning. My research has been published in leading outlets including Nature, Management Science, and Operations Research, and has received numerous recognitions, including the Wagner Prize, the Pierskalla Award, 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 (Forthcoming).
Chung et al. Improving Access to Essential Medicines in Sierra Leone via Decision-Aware Machine Learning, Preprint.
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, 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 (Forthcoming).
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).