Published Papers

2020's:  2020  2021  2022 

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2022


Integrated multimodal artificial intelligence framework for healthcare applications
with Luis R. Soenksen, Yu Ma, Cynthia Zeng, Leonard Boussioux, Kimberly Villalobos Carballo, Liangyuan Na, Holly M. Wiberg, Michael L. Li, Ignacio Fuentes; www.nature.com/npjdigitalmed, 2022


An Exact and Interpretable Solution to Wordle
with Alex Paskov; , 2022


Robust convex optimization: A new perspective that unifies and extends
with Dick den Hertog, Jean Pauphilet, Jianzhe Zhen; Mathematical Programming, https://doi.org/10.1007/s10107-022-01881-w, 2022


World‑class interpretable poker
with Alex Paskov; Machine Learning, https://doi.org/10.1007/s10994-022-06179-8, 2022


POTTER-ICU: An artificial intelligence smartphone-accessible tool to predict the need for intensive care after emergency surgery
with Anthony Gebran, Annita Vapsi, Lydia R. Maurer, Mohamad El Moheb, Leon Naar, Sumiran S. Thakur, Robert Sinyard, Dania Daye, George C. Velmahos and Haytham M.A. Kaafarani; ELSEVIER JOURNAL, 2022


Ethics by design: efficient, fair and inclusive resource allocation using machine learning
with Theodore P. Papalexopoulos, I. GlennCohen, RebeccaR.Goff, DarrenE.Stewart and Nikolaos Trichakis; Journal of Law and the Biosciences, 2022


Global Optimization via Optimal Decision Trees
with Berk Ozturk; Submitted to Operations Research, Manuscript OPRE-2022-02-051, 2022


Integrated Multimodal Artificial Intelligence Framework For Healthcare Applications
with Luis R. Soenksen, Yu Ma2, Cynthia Zeng, Leonard D.J. Boussioux, Kimberly Villalobos Carballo, Liangyuan Na, Holly M. Wiberg, Michael L. Li, Ignacio Fuentes; Manuscript, 2022


Toward Global Food Security Transforming OCP Through Analytics
with Adrian Becker, Kassem Benabderrazik, Nada Chtinna, Nada El Majdoub, El Miloudi Mahboubi, Driss Lahlou Kitane, Steve Kokkotos, Georgia Mourtzinou, Ilyas Rakhis; INFORMS Journal on Applied Analytics, 2022


Personalized Breast Cancer Screening
with Yu Ma, Omid Nohadani, Olga Kyriazi; Working paper, 2022


Sparse PCA: a Geometric Approach
with Driss Lahlou Kitane; Journal of Machine Learning Research 1, 2022

2021


Two-stage sample robust optimization
with S. Shtern and B. Sturt; Operations Research, 2021


Dynamic Optimization with Side Information
with C. McCord and B. Sturt; European Journal of Operations Research, 2021


A Robust Optimization Approach to Deep Learning
with X. Boix, K. Villalobos Carballo and D. den Hertog; Journal of Machine Learning Research, 2021


Mixed-Integer Optimization with Constraint Learning
with I. Birbil, D. den Hertog, A. Fajemisin, D. Maragno, H. Wiberg; Operations Research, 2021


Holistic Deep Learning
with L. Boussioux, K. Villalobos Carballo, M. Li, A. Paskov and I. Paskov; Journal of Machine Learning Research, 2021


Multistage Stochastic Optimization via Kernels
with K. Villalobos Carballo; Operations Research, 2021


Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach
with N. Johnson and R. Cory-Wright; Journal of Machine learning Research, 2021


Interpretable Machine Learning for Policy Analysis: The Case of National Immigration Policy
with M. Fazel-Zarandi; MSOM, 2021


Pricing algorithmic Insurance
with A. Orfanoudaki; Operations Research, 2021


Robust Optimization with Side Data
with N. Koduri; Mathematical Programming, 2021


The Price of Diversity
with H. Bandi; Operations Research, 2021


Stochastic Cutting Planes for Data-Driven Optimization
with M. Li; INFORMS J. Computation, 2021


Personalized prescription of ACEI/ARBs for hypertensive COVID-19 patients
with Alison Borenstein, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Bartolomeo Stellato, Holly Wiberg, Pankaj Sarin, Dirk J Varelmann, Vicente Estrada, Carlos Macaya, Ivn J Nez Gil; Health care management science, 2021


Machine Learning for Real-Time Heart Disease Prediction
with Luca Mingardi, Bartolomeo Stellato; IEEE Journal of Biomedical and Health Informatics, 2021


Selecting Children with Vesicoureteral Re ux Who are Most Likely to Benefit from Antibiotic Prophylaxis: Application of Machine Learning to RIVUR
with Michael Li, Carlos Estrada, Caleb Nelson, Hsin-Hsiao Scott Wang; The Journal of Urology, 2021


Validation of the Artificial Intelligence-Based Predictive Optimal Trees in Emergency Surgery Risk (POTTER) Calculator in Emergency General Surgery and Emergency Laparotomy Patients
with Majed W El Hechi, Lydia R Maurer, Jordan Levine, Daisy Zhuo, Mohamad El Moheb, George C Velmahos, Jack Dunn, Haytham MA Kaafarani; , 2021


Trauma outcome predictor: An artificial intelligence interactive smartphone tool to predict outcomes in trauma patients
with Lydia R Maurer, Hamza Tazi Bouardi, Majed El Hechi, Mohamad El Moheb, Katerina Giannoutsou, Daisy Zhuo, Jack Dunn, George C Velmahos, Haytham MA Kaafarani; Journal of Trauma and Acute Care Surgery, 2021


Prediction of Neutropenic Events in Chemotherapy Patients: A Machine Learning Approach
with Holly Wiberg, Peter Yu, Pat Montanaro, Jeff Mather, Suzi Birz, Michelle Schneider; JCO Clinical Cancer Informatics, 2021


Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme
with V. Digalakis; IEEE Transactions on Knowledge and Data Engineering, 2021


A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave
with Johannes Bracher, Daniel Wolffram, Jannik Deuschel, K Grgen, JL Ketterer, Alexander Ullrich, Sam Abbott, MV Barbarossa, Sangeeta Bhatia, Marcin Bodych, NI Bosse, Jan Pablo Burgard, L Castro, Geoffrey Fairchild, Jan Fuhrmann, Sebastian Funk, Krzysztof Gogolewski, Quanquan Gu, Stefan Heyder, Thomas Hotz, Yuri Kheifetz, Holger Kirsten, Tyll Krueger, Ekaterina Krymova, ML Li, JH Meinke, Isaac James Michaud, Karol Niedzielewski, T Oaski, Franciszek Rakowski, Markus Scholz, Saksham Soni, Ajitesh Srivastava, Jakub Zieliski, Difan Zou, Tilmann Gneiting, Melanie Schienle; Nature communications, 2021


Toward an Optimized Staging System for Pancreatic Ductal Adenocarcinoma: A Clinically Interpretable, Artificial IntelligenceBased Model
with G. A. Margonis, Y. Huang, N. Andreatos, H. Wiberg, Y. Ma, C. Mcintyre, A. Pulvirenti, D. Wagner, JL van Dam, F. Gavazzi, S. Buettner, K. Imai, G. Stasinos, J. He, C. Kamphues, K. Beyer, H. Seeliger, M. J. Weiss, M. Kreis, J. L Cameron, A. C Wei, P. Kornprat, H.Baba, B. Groot Koerkamp, Al. Zerbi, M. D'Angelica, C. L. Wolfgang; JCO Clinical Cancer Informatics, 2021


Ensemble machine learning for personalized antihypertensive treatment
with A. Borenstein, A. Dauvin and A. Orfanoudaki; Naval Research Logistics, 2021


Course Scheduling Under Sudden Scarcity: Applications to Pandemic Planning
with C. Barnhart, A. Delarue and J.Yan; Manufacturing & Service Operations Management, 2021


Sparse classification: a scalable discrete optimization perspective
with J. Pauphilet and B. van Parys; Machine Learning, 2021


Validation of the artificial intelligencebased trauma outcomes predictor (TOP) in patients 65 years and older
with M. El Hechi, A. Gebran, H. Tazi Bouardi, L. R. Maurer, M.El Moheb, D. Zhuo, J. Dunn, G. Velmahos, H. Kaafarani; Surgery, 2021


Computation of Convex Hull Prices in Electricity Markets with Non-Convexities using Dantzig-Wolfe Decomposition
with P. Andrianesis, M. Caramanis, and W. Hogan; IEEE Power Systems, 2021


Optimal Survival Trees
with J. Dunn, E. Gibson and A. Orfanoudaki; Machine Learning, 2021


Near Optimal Nonlinear Regression Trees
with J. Dunn and Y. Wang; Operations Research Letters, 2021


Probabilistic guarantees in Robust Optimization
with D. den Hertog, J. Pauphilet; SIAM J. Optimization, 2021


A simple and fast spectroscopy-based technique for Covid-19 diagnosis
with D. Lahlou Kitane, S. Loukman, N. Marchoudi, A. Fernandez, J. Badir, JL. Gala, N.Azami, O. Lakbita, O. Moudam, R. Benhida, J. Fekkak; Scientific Reports, 2021


Bootstrap Robust Prescriptive Analytics
with B. van Parys; Mathematical Programming, 2021


Machine Learning for Real-Time Heart Disease Prediction
with L. Mingardi and B. Stelato; IEEE Journal of Biomedical and Health Informatics, 2021


Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality
with R. Cory-Wright and J. Pauphilet; JMLR, 2021


Mixed-Projection Conic Optimization: A New Paradigm for Modeling Low-Rank Constraints
with R. Cory-Wright and J. Pauphilet; Operations Research, 2021


A scalable algorithm for sparse and robust portfolios
with R. Cory-Wright; INFORMS Journal of Computing, 2021


Sparse Regression over Clusters: SparClur
with J. Dunn, L. Kapelevich, R. Zhang; Optimization Letters, 2021


A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms
with R. Cory-Wright and J. Pauphilet; SIAM J. Optimization, 2021


Optimizing Influenza Vaccine Composition: A Machine Learning Approach
with H. Bandi; Naval Research Logistics, 2021


From predictions to prescriptions: A data-driven response to COVID-19
with L. Boussioux, R. Cory-Wright, A. Delarue, V. Digalakis, A. Jacquillat, D. Lahlou Kitane, G. Lukin, M. Li, L. Mingardi, O. Nohadani, A. Orfanoudaki, T. Papalexopoulos, I. Paskov, J, Pauphilet, O. Skali Lami, B. Stellato, H. Tazi Bouardi, K. Villalobos Carballo, H. Wiberg and C. Zeng; Health Care Management Science, 2021


Predicting Inpatient Flow at a Major Hospital Using Interpretable Analytics
with J.Pauphilet, J. Stevens and M.Tandon; MSOM, 2021


Data-Driven Transit Network Design at Scale
with Yee Sian Ng and J. Yan; Operations Research, 2021


Data-Driven Optimization: A Reproducing Kernel Hilbert Space Approach
with N. Koduri; Operations Research, 2021


The Voice of Optimization
with B. Stellato; Machine Learning, 2021


Sparse convex regression
with N. Mundru; Informs Journal of Computing, 2021


Time Series that are Robust to Regime Changes
with Ivan Paskov; Journal of Machine Learning Research, 2021


Technical Note—Two-Stage Sample Robust Optimization
with Shimrit Shtern, Bradley Sturt, Shimrit Shtern, Bradley Sturt; Informs Journal of Operations Research, 2021


Benchmarking in Congenital Heart Surgery using Machine Learning-derived Optimal Classification Trees
with Daisy Zhuo, Jordan Levine, Jack Dunn, Maruszewski Tobota, Jose Fragata, George Sarris; World Journal for Pediatric and Congenital Heart Surgery, 2021


Adverse Outcomes Prediction for Congenital Heart Surgery: A Machine Learning Approach
with Daisy Zhuo, Jack Dunn, Jordan Levine, Eugenio Zuccarelli, Nikos Smyrnakis, Zdzislaw Tobota, Bohdan Maruszewski, Jose Fragata, George E. Sarris; World Journal for Pediatric and Congenital Heart Surgery, 2021


Prediction with Missing Data
with A. Delarue and J. Pauphilet; submitted to Operations Research, 2021


Imputation of Clinical Covariates in Time Series
with A.Orfanoudaki and C. Pawlowski; submitted to Journal of Machine Learning Research, 2021


Interpretable Clustering: An Optimization Approach
with A. Orfanoudaki and H. Wiberg, A. Orfanoudaki and H. Wiberg; submitted to Machine Learning, 2021


Slowly Varying Regression under Sparsity
with V. Digalakis, M. Li and O. Skali Lami, V. Digalakis, M. Li and O. Skali Lami; submitted to Journal of Machine Learning Research, 2021


Where to locate COVID-19 mass vaccination facilities?
with V. Digalakis, A. Jacquillat, M. Li, A. Previero; to appear in Naval Research Logistics Quarterly, 2021


World-Class Interpretable Poker
with A. Paskov; submitted to Machine Learning, 2021

2020


On Polyhedral and Second-Order Cone Decompositions of Semidefinite Optimization Problems
with R. Cory-Wright; Operations Research Letters, 2020


Balancing efficiency and fairness in liver transplant access: tradeoff curves for the assessment of organ distribution policies
with T. Papalexopoulos, N. Trichakis, Y. Wang, R. Hirose, P. A. Vagefi; Transplantation, 2020


From Predictive to Prescriptive Analytics
with N. Kallus; Management Science, 2020


Bus routing optimization helps Boston Public Schools design better policies
with A. Delarue, W. Eger, J. Hanlon, and S. Martin; INFORMS Journal on Applied Analytics, 2020


Computation of exact bootstrap confidence intervals: complexity and deterministic algorithms
with B. Sturt; Operations Research, 2020


Sparse regression: Scalable algorithms and empirical performance
with J. Pauphilet and B. Van Parys; Statistical Science, 2020


Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score
with Agni Orfanoudaki ,Emma Chesley, Christian Cadisch, Barry Stein, Amre Nouh, Mark J. Alberts; PLOS ONE, 2020


Personalized treatment of coronary artery disease patients using electronic medical records: a machine learning approach
with A. Orfanoudakis and R. Weiner; submitted to Health Management Science, 2020


FTIR spectroscopy combined with multivariate data analysis for diagnosis of Covid-19
with D. Lahlou Kitane, S. Loukman, N. Marchoudi, A. Fernandez, J. Badir, JL. Gala, N.Azami, O. Lakbita, O. Moudam, R. Benhida, J. Fekkak; submitted to Nature Biotechnology, 2020


COVID-19 Mortality Risk Assessment: An International Multi-Center Study
with G. Lukin, L. Mingardi, O. Nohadani, A. Orfanoudaki, B. Stellato, H. Wiberg, J.M. Cisneros- Herreros, S. Gonzalez Garcia, C. Caldern, The Hellenic COVID-19 Study Group, K. Robinson, M. Schneider, B. Stein, L. Beccara, R. Canino, M. Dal Bello, F. Pezzetti and A. Pan; submitted to PLOS One, 2020


Prescriptive Machine Learning for Public Policy: The Case of Immigration Enforcement
with M. Fazel-Zarandi; submitted to Operations Research, 2020


Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank Constraints
with R. Cory-Wright and J. Pauphilet; submitted to Operations Research, 2020


Holistic Prescriptive Analytics for Continuous and Constrained Optimization Problems
with O. Skali Lami; submitted to INFORMS Journal on Optimization, 2020


Early Detection of Opioid Over-Procurement: A Machine Learning Approach
with M. Fazel-Zarandi and J. Ivanhoe; submitted to MOSM, 2020


Robust Convex Optimization: A New Perspective That Unifies And Extends
with D. den Hertog, J. Pauphilet, T. Zhen; submitted to Mathematics of Operations Research, 2020


Stable Classification
with J. Dunn and I. Paskov; submitted to Journal of Machine Learning Research, 2020


Optimization-based Scenario Reduction for Data-Driven Two-stage Stochastic Optimization
with N. Mundru; submitted to Operations Research, 2020


The Backbone Method for Ultra-High Dimensional Sparse Machine Learning
with V. Digalakis Jr.; submitted to Machine Learning, 2020


Hospital-wide Patient Flow Optimization
with J. Pauphilet; submitted to Management Science, 2020


Imbalanced classification via robust optimization
with Y. Wang; submitted to Machine Learning, 2020


The Power and Limits of Decision Making with Confounded Data: The Case of Pricing
with N. Kalllus; submitted to INFORMS Journal on Optimization, 2020


Forecasting COVID-19 and Analyzing the Effect of Government Interventions
with M. Li, H. Tazi, O. Skali, T. Trikalinos and N. Trichakis; submitted to Operations Research, 2020


Optimal Predictive Clustering
with M. Sobiesk and Y. Wang, M. Sobiesk and Y. Wang; submitted to Machine Learning, 2020


The edge of optimization in large-scale vehicle routing for paratransit
with J. Yan; submitted to Transportation Science, 2020


Tensor Completion with Noisy Side Information
with C. Pawlowski; submitted to Machine Learning Research, 2020


Fast Exact Matrix Completion: A Unifying Optimization Framework
with M. Li; to appear in Journal of Machine Learning Research, 2020


Joint Frequency-Setting and Pricing Optimization in Multi-Modal Transit Networks at Scale
with Yee Sian Ng and J. Yan; to appear in Transportation Science, 2020


Novel Mixed Integer Optimization Sparse Regression Approach in Chemometrics
with D. Lahlou Kitane, N. Azami and F.R. Doucet; to appear in Analytica Chimica Acta, 2020


Certifiably Optimal Sparse Inverse Covariance Estimation
with J. Lamperski and J. Pauphilet; to appear in Mathematical Programming, 2020


Development and Validation of a Novel, Non-Linear Stroke Risk Assessment Tool
with C. Cadisch, E. Chesley, A. Orfanoudaki, M. Alberts, B. Stein and A. Nouh; to appear in PLOS One, 2020


Machine Learning and Natural Language Processing Methods to Identify Ischemic Stroke, Acuity and Location from Radiology Reports
with C. Ong, A. Orfanoudaki, R. Zhang, F. Caprasse, M. Ma, D. Fard, O. Balogun, M. Miller, M. Minnig, H. Saglam, B. Prescott, D. Gree and S. Smirnakis; PLOS One, 2020


Stochastic Optimization in Supply Chain Networks: Averaging Robust Solutions
with N. Youssef; Optimization Letters, 2020


Sparse High Dimensional Regression: Exact Scalable Algorithms and Phase Transitions
with B. van Parys; Annals of Statistics, 2020


Novel Target Discovery of Existing Therapies: Path to Personalized Cancer Therapy
with D. Zhuo; INFORMS Journal on Optimization, 2020


Scalable Holistic Linear Regression
with M. Li; to appear in Operations Research Letters, 2020


Sparse Hierarchical Regression with Polynomials
with B. van Parys; Machine Learning, 2020


Machine Learning in Oncology: Methods, Applications, and Challenges
with H. Wiberg; to appear in JCO Clinical Cancer Informatics, 2020


Stable Regression: On the Power of Optimization over Randomization in Training Regression Problems
with I. Paskov; Journal of Machine Learning Research, 21, 230, 125, 2020


Pareto Adjustable Robust Optimality via a Fourier-Motzkin Elimination Lens
with S. C. M. ten Eikelder, D. den Hertog and N. Trichakis; submitted to Operations Research, 2020


Interpretable Matrix Completion: A Discrete Optimization Approach
with M. Li; submitted to Machine Learning, 2020


Machine Learning for Real-Time Heart Disease Prediction
with L. Mingardi and B. Stelato; submitted to IEEE Journal of Biomedical and Health Informatics, 2020


Optimizing Vaccine Allocation to Combat the COVID-19 Pandemic
with J. Ivanhoe, A. Jacquillat, M. Li, A. Previero, O. Skali Lami, H. Tazi Bouardi; submitted to Health Care Management Science, 2020


Optimizing Vaccine Allocation to Combat the COVID-19 Pandemic
with J. Ivanhoe, A. Jacquillat, M. Li, A. Previero, O. Skali Lami, H. Tazi Bouardi; submitted to Health Care Management Science, 2020