Research
As explained on my philosophy page, I care about utilizing interdisciplinary tools that I know (statistics, optimization, and analytics) to create impact. I work on both methodology and applications to achieve this goal across my core focus areas:
Optimal and Scalable Machine Learning
Machine learning is already very powerful, but there are still so many tasks outside of its reach. How do we develop machine learning and optimization algorithms for difficult, large-scale tasks? This stream of work aims to push the boundaries on algorithm tractability while providing performance guarantees.
Published in Journal of Machine Learning Research, INFORMS Journal of Computing, and more.
Safe Evaluation of Machine Learning
How can we make sure a machine learning algorithm is doing what we want it to do, at the performance of what we expect? We develop new methodologies for rigorous and safe evaluation of machine learning under both randomized and observational settings with minimal assumptions.
Published in Journal of the American Statistical Association, Manufacturing & Service Operations Management, and more.
Applications in Healthcare
The best test of any method is practice. I apply my methodology in hospitals, pharmaceutical companies, and organizations worldwide to create safe personalized treatments for pediatric patients, optimized clinical trials for life-saving vaccines, mitigation plans for governmental restrictions, and more.
Published in Operations Research, Proceedings of the National Academy of Sciences and more.
Selected Papers
Branch-and Price for Prescriptive Contagion Analytics
with Alexandre Jacquillat, Martin Rame, Kai Wang
Accepted at Operations Research
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Slowly Varying Regression Under Sparsity
with Dimitris Bertsimas, Vassilis Digalakis, Omar Skali Lami
Accepted at Operations Research
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Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning
with Kosuke Imai
Submitted to Biometrika
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Experimental Evaluation of Individualized Treatment Rules
with Kosuke Imai
Journal of American Statistical Association, 2023
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Where to Locate COVID-19 Mass Vaccination Facilities?
with Dimitris Bertsimas, Vassilis Digalakis, Alexandre Jacquillat, Alessandro Previero
Naval Research Logistics, 2022
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Forecasting COVID-19 and Analyzing the Effect of Government Interventions
with Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikos Trichakis, Dimitris Bertsimas
Operations Research, 2022
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Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion
with Dimitris Bertsimas
The Journal of Machine Learning Research, 2021
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Selectin Children with VUR Who are Most Likely to Benefit from Antibiotic Prophylaxis
with Dimitris Bertsimas, Carlos Estrada, Caleb Nelson, Hsin-Hsiao Scott Wang
Journal of Urology, 2021