Publications

My research combines methodological work in large-scale discrete optimization and machine learning with firsthand implementation of predictive and prescriptive analytics, especially in healthcare and sustainability settings.
My research is organized into four broad streams:

Algorithms for discrete and robust optimization
  1. The Surprising Performance of Random Partial Benders Decomposition [Preprint]
    Submitted, 2025, with Yupeng Wu
  2. Improved Approximation Algorithms for Low-Rank Problems Using Semidefinite Optimization [Preprint]
    Submitted, 2025, with Ryan Cory-Wright
  3. Disjunctive Branch-And-Bound for Certifiably Optimal Low-Rank Matrix Completion [Preprint]
    Submitted, 2023, with Dimitris Bertsimas, Ryan Cory-Wright, and Sean Lo
  4. A Stochastic Benders Decomposition Scheme for Large-Scale Stochastic Network Design [Preprint]
    INFORMS Journal on Computing, 2024, with Dimitris Bertsimas, Ryan Cory-Wright, and Periklis Petridis
  5. Minkowski Centers via Robust Optimization: Computation and Applications [Preprint]
    Operations Research, 2023, with Dick den Hertog and Mohamed Yahya Soali
  6. A New Perspective on Low-Rank Optimization [Preprint] [Code]
    Mathematical Programming, 2023, with Dimitris Bertsimas and Ryan Cory-Wright
  7. Robust Convex Optimization: A New Perspective That Unifies And Extends [Preprint]
    Mathematical Programming, 2022, with Dimitris Bertsimas, Dick den Hertog, and Jianzhe Zhen
  8. Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank Constraints [Preprint] [Code]
    Operations Research, 2021, with Dimitris Bertsimas and Ryan Cory-Wright
  9. Probabilistic Guarantees in Robust Optimization [Preprint]
    SIAM Journal on Optimization, 2021, with Dimitris Bertsimas and Dick den Hertog
  10. 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

Optimization for machine learning and statistics
  1. Operationalizing Experimental Design: Data Collection for Remote Ocean Monitoring [Preprint]
    Submitted, 2025, with Baizhi Song
  2. Sparse PCA with Multiple Components [Preprint][Code]
    Submitted, 2022, with Ryan Cory-Wright
      Winner of the 2024 INFORMS Data Mining and Decision Analytics Workshop Best Theoretical Paper
    • Adaptive Optimization for Prediction with Missing Data [Preprint]
      Machine Learning, 2025, with Dimitris Bertsimas and Arthur Delarue
    • Simple Imputation Rules for Prediction with Missing Data: Theoretical Guarantees vs. Empirical Performance [Preprint]
      Transactions on Machine Learning Research, 2024, with Dimitris Bertsimas and Arthur Delarue
    • 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
    • Sparse Classification: A Scalable Discrete Optimization Perspective [Preprint] [Code]
      Machine Learning, 2021, with Dimitris Bertsimas and Bart Van Parys
    • 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

    Analytics for healthcare operations
    1. 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
    2. Patient Outcome Predictions Improve Operations at Hartford HealthCare [Preprint]
      INFORMS Journal on Applied Analytics, 2025 (accepted), with Dimitris Bertsimas, Irra Na, Kimberley Villalobos Carballo, and Hartford HealthCare
        Finalist for the 2023 INFORMS Doing Good with Good OR Student Paper Competition (Irra Na and Kimberley Villalobos Carballo)
      • Optimization Automates Nurse Scheduling at Hartford Hospital Emergency Department
        INFORMS Journal on Applied Analytics, 2024, with Dimitris Bertsimas, Irra Na, and Hartford HealthCare
      • The Best Decisions Are Not the Best Advice: Making Adherence-Aware Recommendations [Preprint]
        Management Science, 2024, with Julien Grand-Clément
      • Hospital-wide Inpatient Flow Optimization [Preprint]
        Management Science, 2023, with Dimitris Bertsimas
          Winner of the 2022 POMS College of Healthcare Operations Management Best Paper Competition
          Winner of the 2021 Canadian Healthcare Optimization Workshop Best Paper Competition
          Honorable Mention at the 2020 INFORMS Doing Good with Good OR Student Paper Competition
        • Robust Combination Testing: Methods and Application to COVID-19 Detection [Preprint] [Media]
          Management Science, 2023, with Sanjay Jain, Jonas Jonasson, and Kamalini Ramdas
        • 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 [Preprint] [Code] [NYT]
          Health Care Management Science, 2021, with Dimitris Bertsimas et al.
            Winner of the 2020 INFORMS Pierskalla Award

          Analytics for sustainable operations
          1. Optimizing the Path Towards Plastic-Free Oceans [Preprint] [Media]
            Operations Research, 2024, with Dick den Hertog, Baizhi Song, and Bruno Sainte-Rose and Yannick Pham (The Ocean Cleanup)
              Runner-up the 2025 MSOM Responsible Research Award
              Finalist for the 2025 Best OM Paper in Operations Research Award
              Third Place at the 2025 INFORMS Innovative Applications in Analytics Award
              Honorable Mention for the 2024 INFORMS Doing Good with Good OR Student Paper Competition (Baizhi Song)
              Winner of the 2024 POMS College of Sustainable Operations Student Paper Competition (Baizhi Song)
              Honorable Mention for the 2023 INFORMS Transportation Science and Logistics Best Student Paper Award (Baizhi Song)
            • 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
            • 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

            PhD dissertation

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