367 citations · 418 across the 8 of their papers we have counts for
8 papers
Deciding When to Decide: Testing Operational Suboptimality Under Distributional Shift
Minxing Zheng, Holly Wiberg, Shixiang Zhu
Deployed decisions are often optimized once and retained because updates impose operational, regulatory, or switching costs. As operating conditions change, when should such decisi…
Making a Case for Research Collaboration Between Artificial Intelligence and Operations Research Experts
Radhika Kulkarni, Gianluca Brero, Yu Ding +7
In 2021, INFORMS, ACM SIGAI, and the Computing Community Consortium (CCC) hosted three workshops to explore synergies between Artificial Intelligence (AI) and Operations Research (…
Can LLMs Support Medical Knowledge Imputation? An Evaluation-Based Perspective
Xinyu Yao, Aditya Sannabhadti, Holly Wiberg +2
Medical knowledge graphs (KGs) are essential for clinical decision support and biomedical research, yet they often exhibit incompleteness due to knowledge gaps and structural limit…
Assortment Optimization for Patient-Provider Matching
Naveen Raman, Holly Wiberg
Rising provider turnover results in frequently needing to rematch patients with available providers. However, the rematching process is cumbersome for both patients and health syst…
Integrated multimodal artificial intelligence framework for healthcare applications
Luis R. Soenksen, Yu Ma, Cynthia Zeng +7
Artificial intelligence (AI) systems hold great promise to improve healthcare over the next decades. Specifically, AI systems leveraging multiple data sources and input modalities…
Mixed-Integer Optimization with Constraint Learning
Donato Maragno, Holly Wiberg, Dimitris Bertsimas +3
We establish a broad methodological foundation for mixed-integer optimization with learned constraints. We propose an end-to-end pipeline for data-driven decision making in which c…
From predictions to prescriptions: A data-driven response to COVID-19
Dimitris Bertsimas, Léonard Boussioux, Ryan Cory Wright +18
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a d…
Interpretable Clustering via Optimal Trees
Dimitris Bertsimas, Agni Orfanoudaki, Holly Wiberg
State-of-the-art clustering algorithms use heuristics to partition the feature space and provide little insight into the rationale for cluster membership, limiting their interpreta…