Research

Research Interests

• Methodologies: Stochastic Modeling and Optimization, Queueing Theory, Interpretable Machine Learning, Markov Decision Processes, Approximate Dynamic Programming
• Application Areas: Healthcare, Service Systems Staffing and Scheduling

Working Papers

1. Multiclass Queue Scheduling Under Slowdown: An Approximate Dynamic Programming Approach [link]
   with Jing Dong and Vahid Sarhangian

2. Optimizing Hard-to-Place Kidney Allocation: A Machine Learning Approach to Center Ranking [link]
   with Sean Berry, Sait Tunc and Mucahit Cevik

3. Intepretable Machine Learning for Personalized Breast Cancer Screening Recommendations
   with Sean Berry, Sait Tunc and Mucahit Cevik

4. Prototype Forest in Multiple Instance Learning
   with Ozgur E. Sivrikaya, Ali E. Banak and Mustafa G. Baydogan

5. A Concurrent CNN-RNN Approach for Multi-Step Wind Power Forecasting
   with Syed Kazmi, Mucahit Cevik and Mustafa G. Baydogan

Journal Papers

1. What Causes Delays in Admission to Rehabilitation Care? A Structural Estimation Approach [link]
   with Jing Dong and Vahid Sarhangian
   Manufacturing and Service Operations Management (2024)

2. Inventory Management with Advance Booking Information: The Case of Surgical Supplies and Elective Surgeries [link]
   with Jacky Chan and Vahid Sarhangian
   Manufacturing and Service Operations Management (2024)

3. Column generation-based prototype learning for optimizing area under the receiver operating characteristic curve [link]
   with Erhan C. Ozcan and Mustafa G. Baydogan
   European Journal of Operational Reserach (2024)

4. Association between delayed discharge from acute care and rehabilitation outcomes and length of stay: a retrospective cohort study [link]
   with Jing Dong, Karen Hunter, Krista M. Bettio, Betty Vukusic, Jonathan Ranisau, Gary Spencer, Terence Tang, and Vahid Sarhangian
   Archives of Physical Medicine and Rehabilitation (2023)

5. A Newsvendor Approach to Design of Surgical Preference Cards [link]
   with Vahid Sarhangian
   Service Science (2022)

6. Randomized trees for time series representation and similarity [link]
   with Mustafa G. Baydogan
   Pattern Recognition (2021)

7. Explainable boosted linear regression for time series forecasting [link]
   with Igor Ilic, Mucahit Cevik and Mustafa G. Baydogan
   Pattern Recognition (2021)

8. A Data Adaptive Biological Sequence Representation for Supervised Learning[link]
   with Hande Cakin and Mustafa G. Baydogan
   Journal of Healthcare Informatics Research (2018)

Conference Publications

1. Augmented out-of-sample comparison method for time series forecasting techniques [link]
   with Igor Ilic and Mucahit Cevik
   Advances in Artificial Intelligence: 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, Ottawa, ON, Canada, May 13–15, 2020, Proceedings (2020)

2. An Adaptive Large Neighborhood Search Heuristic for Jointly Solving Storage Location Assignment and Picker Routing Problem [link]
   with Necati Aras
   Operations Research Proceedings 2018: Selected Papers of the Annual International Conference of the German Operations Research Society (GOR), Brussels, Belgium, September 12-14, 2018 (2018)