Publications
Filters
Show all
Healthcare
Machine Learning
Discrete optimization
Robust optimization
Misc.
Adaptive Optimization for Prediction with Missing Data [Preprint]
Submitted , 2024, with Dimitris Bertsimas and Arthur Delarue
Simple Imputation Rules for Prediction with Missing Data: Contrasting Theoretical Guarantees with Empirical Performance [Preprint]
Submitted , 2024, with Dimitris Bertsimas and Arthur Delarue
Optimizing the Path Towards Plastic-Free Oceans [Preprint] [Media]
Submitted , 2023, with Dick den Hertog, Baizhi Song, and Bruno Sainte-Rose and Yannick Pham (The Ocean Cleanup)
Occupancy Prediction with Patient Data: Evaluating Time-Series, Patient-Level Aggregation, and Deep Set Models [Preprint]
Submitted , 2023, with Song-Hee Kim and William Overman
Patient Outcome Predictions Improve Operations at a Large Hospital Network [Preprint]
Submitted , 2023, with Dimitris Bertsimas, Irra Na, Kimberley Villalobos Carballo, and Hartford HealthCare
Optimal Low-Rank Matrix Completion: Semidefinite Relaxations and Eigenvector Disjunctions [Preprint]
Submitted , 2023, with Dimitris Bertsimas, Ryan Cory-Wright, and Sean Lo
A Stochastic Benders Decomposition Scheme for Large-Scale Data-Driven Network Design [Preprint]
Submitted , 2023, with Dimitris Bertsimas, Ryan Cory-Wright, and Periklis Petridis
Sparse PCA with Multiple Components [Preprint] [Code]
Submitted , 2022, with Ryan Cory-Wright
Optimization Automates Nurse Scheduling at Hartford Hospital Emergency Department
INFORMS Journal on Applied Analytics , 2024 (accepted), with Dimitris Bertsimas, Irra Na, and Hartford HealthCare
The Best Decisions Are Not the Best Advice: Making Adherence-Aware Recommendations [Preprint]
Management Science , 2023 (accepted), with Julien Grand-Clément
Hospital-wide Inpatient Flow Optimization [Preprint]
Management Science , 2023, with Dimitris Bertsimas
Robust Combination Testing: Methods and Application to COVID-19 Detection [Preprint] [Media]
Management Science , 2023, with Sanjay Jain, Jonas Jonasson, and Kamalini Ramdas
Minkowski Centers via Robust Optimization: Computation and Applications [Preprint]
Operations Research , 2023, with Dick den Hertog and Mohamed Yahya Soali
A New Perspective on Low-Rank Optimization [Preprint] [Code]
Mathematical Programming , 2023, with Dimitris Bertsimas and Ryan Cory-Wright
Robust Convex Optimization: A New Perspective That Unifies And Extends [Preprint]
Mathematical Programming , 2022, with Dimitris Bertsimas, Dick den Hertog, and Jianzhe Zhen
Robust and Heterogeneous Odds Ratio: Estimating Price Sensitivity for Unbought Items [Preprint]
Manufacturing & Service Operations Management , 2022
Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality [Preprint] [Code]
Journal of Machine Learning Research , 2022, with Dimitris Bertsimas and Ryan Cory-Wright
Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank Constraints [Preprint] [Code]
Operations Research , 2021, with Dimitris Bertsimas and Ryan Cory-Wright
Probabilistic Guarantees in Robust Optimization [Preprint]
SIAM Journal on Optimization , 2021, with Dimitris Bertsimas and Dick den Hertog
Sparse Classification: A Scalable Discrete Optimization Perspective [Preprint] [Code]
Machine Learning , 2021, with Dimitris Bertsimas and Bart Van Parys
A Unified Approach to Mixed-Integer Optimization Problems with Logical Constraints [Preprint] [ICS Newsletter]
SIAM Journal on Optimization , 2021, with Dimitris Bertsimas and Ryan Cory-Wright
Predicting Inpatient Flow at a Major Hospital Using Interpretable Analytics [Preprint]
Manufacturing & Service Operations Management , 2021, with Dimitris Bertsimas, Jennifer Stevens, and Manu Tandon
From Predictions to Prescriptions: A Data-Driven Response to COVID-19 [Website] [Preprint] [Code]
[NYT]
Health Care Management Science , 2021, with Dimitris Bertsimas et al.
Direct Optimization across Computer Generated Reaction Networks Balances Materials Use and Feasibility of Synthesis Plans for Molecule Libraries
Journal of Chemical Information and Modeling , 2021, with Hanyu Gao, Thomas Struble, Connor Coley , and Klavs F. Jensen
Sparse Regression: Scalable Algorithms and Empirical Performance [Preprint] [Code]
Statistical Science , 2020, with Dimitris Bertsimas and Bart Van Parys
Certifiably Optimal Sparse Inverse Covariance Estimation [Preprint]
Mathematical Programming , 2020, with Dimitris Bertsimas and Jourdain Lamperski
A Tractable Numerical Strategy for Robust MILP and Application to Energy Management
IEEE 55th Conference on Decision and Control (CDC) , 2016, with Laurent El Ghaoui , Damien Faille, and Diego Kiener
Algorithmic advancements in discrete optimization: Applications to machine learning and healthcare operations [30-page version]
Ph.D. Thesis, Massachusetts Institute of Technology, May 2020
⟵ Back