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In-Person: MIE Distinguished Seminar Series with Professor Mark Van Oyen: “A Hospital Bed Placement Decision Support System Implementation and New Methods for Patient Decisions Via Capacitated Multi-Armed Bandits with Delayed Rewards and Reusable Resources”

September 22, 2023 @ 2:00 pm - 3:00 pm

Interested members of the U of T community who would like to attend the seminars can email Kendra Hunter at hunter@mie.utoronto.ca

Professor Mark Van Oyen Headshot

Professor Mark Van Oyen
University of Michigan (Industrial and Operations Engineering)

A hospital bed placement decision support system implementation and new methods for patient decisions via capacitated multi-armed bandits with delayed rewards and reusable resources


This talk presents work on two related problems.  First, we discuss insights into a real world implementation of a hospital decision support system. This system brings together a wealth of information to recommend a specific hospital bed for each patient waiting for a bed considering capacity and many other constraints.

The second part advances methodology to address the potential to improve patient health outcomes through effective decisions on the type of bed unit a patient should receive. One motivation is that COVID 19 revealed the need for joint adaptive machine learning and optimization when a novel disease has no historical record of data that can be used to build a model offline. Our new algorithms make patient class-based decisions for allocating an arriving patient to the  bed unit type (ICU, PCU, General) for the purpose of minimizing the number of  patient readmissions. We develop online methods for reusable resources in the face of bandit feedback that is delayed.  That is, we develop and characterize the performance of an adaptive method for learning and decision making under capacity constraints. The algorithm must allocate unit capacity efficiently and identify the extent to which each patient type benefits from an ICU, intermediate care unit, and general care units. In addition to performance guarantees, we present a case study employing hospital data.

Mark Van Oyen’s research spans operations management, operations research, systems engineering, data analytics/machine learning, stochastic control, and industrial engineering. His current research emphasizes stochastic systems, optimization, and prescriptive analytics for healthcare operations and medical decision making. He co-authored papers that won numerous awards including the Manufacturing and Service Operations Management (MSOM) Best Published Paper published 2013-2016, MSOM Service Special Interest Group best published paper, 2010 Pierskalla Award, two 1st and two 2nd place best paper awards from the POMS College of Healthcare Op’s. Mgmt., and 2012 INFORMS “Doing Good with Good OR” first prize to his students for his joint work. He has served as Associate Editor for Operations Research, Management Science, Naval Research Logistics, Service Science, IIE Transactions, and IIE Trans. Healthcare Syst. Engr. and Senior Editor for Flexible Services & Manufacturing. He has received grant funding from the NSF, ONR, NIH, EPRI, ALCOA, General Motors, and the VA. He served as President and VP for the INFORMS Health Applications Society. He received his Ph.D. from Electrical Engr. Systems from the Univ. of Michigan and has also worked for GE Corporate R&D, GE Aerospace, Northwestern University (IEMS), and Loyola University of Chicago (Business – OM).

MIE’s Distinguished Seminar Series features top international researchers and leading experts across major areas of Mechanical Engineering and Industrial Engineering. The speakers present about their latest research and offer their perspectives on the current state of their field. The seminars are part of the program requirements for MIE Master of Applied Science and PhD students. The Distinguished Seminar Series is coordinated for 2023-2024 by Associate Professor Eric Diller.

View all upcoming MIE Distinguished Seminars.

Event Details



Mechanical Engineering Building, MC102, 5 King’s College Road, Toronto, Canada

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