Yaron Shaposhnik
Associate Professor of Operations Management and Information Systems
Simon Business School, University of Rochester
About
I am an Associate Professor at the Simon Business School, University of Rochester. My research focuses on machine learning methodologies and their application to solving business problems, sequential decision-making with uncertainty-reduction mechanisms, and business analytics.
I received my PhD in Operations Research from MIT, where I was advised by Retsef Levi and Tom Magnanti; my MS in Industrial Engineering from the Technion–Israel Institute of Technology, where I was advised by Yale Herer and Hussein Naseraldin; and my BS in Information Systems Engineering, also from the Technion.
Publications
| Year | Publication | Journal | Links |
|---|---|---|---|
| 2026 | Pandora's Box Problem with Sequential Inspections |
Operations Research | JournalSSRN |
| 2025 | Waiting-Time Prediction with Invisible Customers |
Manufacturing & Service Operations Management | JournalSSRN |
| 2025 | A Dual-Index Rule for Managing Temporary Congestion | European Journal of Operational Research | Journal |
| 2024 | Scheduling with Testing of Heterogeneous Jobs |
Management Science | JournalSSRN |
| 2024 | Interpretable Prediction Rules for Congestion Risk in Intensive Care Units |
Stochastic Systems | JournalSSRN |
| 2023 | Visualizing the Implicit Model Selection Tradeoff |
Journal of Artificial Intelligence Research | JournalSSRN |
| 2023 | Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation |
Journal of Machine Learning Research | JournalCode |
| 2022 | A Polynomial-Time Approximation Scheme for Sequential Batch-Testing of Series Systems |
Operations Research | JournalSSRNCode |
| 2022 | A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations |
Decision Support Systems | JournalarXiv |
| 2021 | Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization |
Journal of Machine Learning Research | Journal |
| 2020 | Mining Optimal Policies: A Pattern Recognition Approach to Model Analysis |
INFORMS Journal on Optimization | JournalSSRN |
| 2019 | Scheduling with Testing |
Management Science | Journal |
| 2015 | Optimal Ordering for a Probabilistic One-Time Discount |
European Journal of Operational Research | Journal |
Working papers
| Publication | Status | Links |
|---|---|---|
| Algorithm Adoption and Explanations: An Experimental Study on Self and Other Perspectives |
Under review | |
| Explaining Model Behavior Across Space and Time: Differential and Intertemporal Explanations |
Under review | SSRN |
| Dynamic Prediction of Waiting Time Intervals: Application to Cancer Care Facilities |
Under review | |
| Stochastic Selection Problems with Testing |
Working paper | SSRN |
PhD students
- Yuting Yuan (graduated 2022) — Assistant Professor of Mathematics and Operations Research, William & Mary
- Zezhen (Dawn) He (graduated 2025) — Postdoc, MIT
- Yashi Huang (6th-year PhD student)
- Le (Lexie) Sun (4th-year PhD student)
- Hongyu Wang (3rd-year PhD student)
- Shanshan Huang (2nd-year PhD student)
Teaching
At the Simon Business School:
- Predictive Analytics using Python (MS/MBA)
- Supply Chain Analytics (MBA)
- PhD course on Optimization
- PhD seminars on data analytics in operations, interpretable machine learning, and statistical learning
Contact
Simon Business School, University of Rochester
Carol Simon Hall 3-345, Rochester, NY 14627
yaron@simon.rochester.edu