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Published Papers

2020’s:  2021  |  2020

2010 – 2019 |  2000 – 2009 |  1990 – 1989

2021

Stochastic Cutting Planes for Data-Driven Optimization
with M. Lingzhi Li, Submitted to Mathematical Programming, 2021

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Stochastic Optimization in Supply Chain Networks: Averaging Robust Solutions
with N. Youssef, Optimization Letters, 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, to appear in PLOS One, 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

Sparse Convex Regression
with N. Mundru, to appear in INFORMS Journal of Computing, 2020

The Voice of Optimization
with B. Stellato, to appear in Machine Learning, 2020

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

Data-Driven Optimization: A Reproducing Kernel Hilbert Space Approach
with N. Koduri, to appear in Operations Research, 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

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

Data-Driven Transit Network Design at Scale
with Yee Sian Ng and J. Yan, to appear in Operations Research, 2020

Predicting Patient Flow at a Major Hospital Using Interpretable Analytics
with J. Pauphilet, J. Stevens and M.Tandon, to appear in MSOM, 2020

Personalized Prescription of ACEI/ARBs for Hypertensive COVID-19 Patients
with A. Borenstein, L. Mingardi, O. Nohadani, A. Orfanoudaki, B. Stellato, H. Wiberg, to appear in Health Care Management Science, 2020

Optimizing Influenza Vaccine Composition: A Machine Learning Approach
with H. Bandi, to appear in Naval Research Logistics, 2020

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

The Edge of Optimization in Large-Scale Vehicle Routing for Paratransit
with J. Yan, submitted to Transporation Science, 2020

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

Probabilistic Guarantees in Robust Optimization
with D. den Hertog, submitted to SIAM J. of Optimization, 2020

A scalable algorithm for sparse and robust portfolios
with R. Cory-Wright, submitted to INFORMS Journal of Computing, 2020

Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme
with V. Digalakis, submitted to IEEE Transactions on Knowledge and Data Engineering, 2020

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

Sparse Regression over Clusters: SparClur
with J. Dunn, L. Kapelevich, R. Zhang, submitted to Operations Research Letters, 2020

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

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

Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality
with R. Cory-Wright and J. Pauphilet, submitted to Mathematical Programming, 2020

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

Near Optimal Nonlinear Regression Trees
with J. Dunn and Y. Wang, submitted to Operations Research Letters, 2020

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

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

A Unified Approach to Mixed-Integer Optimization: Nonlinear Formulations and Scalable Algorithms
with R. Cory-Wright and J. Pauphilet, submitted to SIAM J. Optimization, 2020

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

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

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

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

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

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

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

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, submitted toit PNAS, 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

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