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A novel algorithm for a broad class of nonconvex optimization problems

with D. de Moor, T. Koukouvinos, D. den Hertog, J. Zhen, submitted to Operations Research, 2023

Adaptive Linear Algebra

with Thodoris Koukouvinos, 2023

Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty

with Angelos Georgios Koulouras, IEEE Transactions on Power Systems, 2023

Automated Segmentation of Sacral Chordoma and Surrounding Muscles Using Deep Learning Ensemble

with Leonard Boussioux, Yu Ma, Nancy Knight Thomas, Nadya Shusharina, Jennifer Pursley, Yen-Lin Chen, Thomas F. DeLaney, Jack Qian, Thomas Bortfeld, International Journal of Radiation Oncology - Biology - Physics, 2023

Cone product reformulation for global optimization

with Danique de Moor, Dick den Hertog, Thodoris Koukouvinos, Jianzhe Zhen, submitted to INFORMS Journal of Computing, 2023

Congenital Heart Surgery Machine Learning-Derived In-Depth Benchmarking Tool

with George E. Sarris, Daisy Zhuo, Luca Mingardi, Jack Dunn, Jordan Levine, Zdzislaw Tobota, Bohdan Maruszewski, Jose Fragata, The Annals of Thoracic Surgery, appeared online, 2023

Data-Driven COVID-19 Vaccine Development for Janssen

with Michael Lingzhi Li, Xinggang Liu, Jennings Xu, Najat Khan, INFORMS Journal on Applied Analytics, 2023

Development of a Machine Learning Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma

with Anthony Gebran, Sumiran S. Thakur, Lydia R. Maurer, Hari Bandi, Robert Sinyard, Ander Dorken-Gallastegi, Mary Bokenkamp, Mohamad El Moheb, Leon Naar, Annita Vapsi, Dania Daye, George C Velmahos, Haytham M.A. Kaafarani, JAMA Surgery, 2023

Distributionally Robust Causal Inference with Observational Data

with Kosuke Imai, Michael Lingzhi Li, submitted to Journal of Machine Learning Research, 2023

Dynamic Optimization with Side Information

with C. McCord and B. Sturt, European Journal of Operations Research, 2023

Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach

with L. Boussioux, submitted to Journal of Machine Learning Research, 2023

Ensembling Wind Forecasting Models to Construct Data-Driven Uncertainty Sets in Robust Optimization

with Panagiotis Andrianesis, Thodoris Koukouvinos, Angelos Georgios Koulouras, submitted to IEEE Power systems, 2023

Explainable vs. interpretable artificial intelligence frameworks in oncology

with Georgios Antonios Margonis, Transl Cancer Res 2023;12(2):217, 2023

Finding neurons in a Haystack - Case studies with sparse probing

with Wes Gurnee, Neel Nanda, Matthew Pauly, Katherine Harvey, Dmitrii Troitskii, 2023

Forecasting COVID-19 and analyzing the effect of government interventions

with Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas A Trikalinos, Nikolaos Trichakis, Operations Research 71(1):184-201, 2023

Global Flood Prediction: a Multimodal Machine Learning Approach

with Cynthia Zeng, arXiv preprint arXiv:2301.12548, 2023

High-performance pediatric surgical risk calculator: A novel algorithm based on machine learning and pediatric NSQIP data

with Michael Li, Nova Zhang, Carlos Estrada, Hsin-Hsiao Scott Wang, The American Journal of Surgery, 2023

Holistic Prescriptive Analytics for Continuous and Constrained Optimization Problems

with Omar Skali Lami, INFORMS Journal on Optimization 5(2):155-171, 2023

Hospital-Wide Inpatient Flow Optimization

with J. Pauphillet, Management Science, appeared online, 2023

Improving Stability in Decision Tree Models

with Vassilis Digalakis Jr, submitted to Operations Research, 2023

Interpretable Matrix Completion: A Discrete Optimization Approach

with Michael Lingzhi Li, INFORMS Journal on Computing, 2023

Interpretable Prescriptive Neural Networks

with Lisa Everest and Vasiliki Stoumpou, submitted to Machine Learning, 2023

Interpretable algorithmic fairness in structured and unstructured data

with Hari Bandi, Thodoris Koukouvinos, Sofie Kupiec, submitted to JMLR, 2023

Learning sparse nonlinear dynamics via mixed-integer optimization

with Wes Gurnee, Nonlinear Dynamics, 2023

Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach

with Cheol Woo Kim, submitted to Operations Research, 2023