Jangwon Park

Jangwon Park

PhD student in operations research

About Me

Hi! My name is Jang. I am a fourth-year Ph.D. student in Operations Research at the University of Toronto. My advisors are Timothy Chan and Vahid Sarhangian.

In my research, I am particularly motivated by the growing risk of large-scale illness events that create spatially uneven demand for hospital care and medical resources. This can occur both within and across hospitals, and is especially pronounced during pandemics, natural disasters, and extreme weather events. I am very interested in studying how to improve the sustainability of healthcare systems through intelligent pooling and allocation of resources. Currently, my research focuses on optimizing patient transfer decisions between hospitals, and leverages stochastic modeling and control, optimization, and applications of econometrics and data analytics.

Before joining U of T, I completed MSc. in Business Analytics at EPFL in 2020, and was a research scientist on Swissgrid’s Research and Digitalization team from March-Oct 2020. I completed BASc. in Engineering Science at U of T in 2018.

Contact: jangwon.park [at] mail.utoronto.ca

Working Papers

6. Causal impact of inter-hospital patient transfers
with Carri Chan, Timothy Chan, and Vahid Sarhangian
Work in progress, 2025

5. Robust confidence bands for stochastic processes using simulation [Preprint]
with Timothy Chan and Vahid Sarhangian
Minor revision, Operations Research Letters, 2024
      Accepted for presentation, 2024 Winter Simulation Conference PhD Colloquium

4. Dynamic transfer policies for parallel queues [Preprint]
with Timothy Chan and Vahid Sarhangian
Major revision, Operations Research, 2024
      Second place, 2024 CORS Queueing and Applied Probability SIG Student Paper Competition

3. Optimizing inter-hospital patient transfer decisions during a pandemic: a queueing network approach [Preprint]
with Timothy Chan, Frances Pogacar, and Vahid Sarhangian
Major revision, Manufacturing & Service Operations Management, 2024
     First place, 2024 CORS Healthcare SIG Student Paper Competition
     Accepted for presentation, 2025 MSOM Healthcare SIG

Published Papers

2. Evolution of the surgical procedure gap during and after the COVID-19 pandemic in Ontario, Canada: a cross-sectional and modeling study [DOI]
with Timothy Chan, Vahid Sarhangian, and Rachel Stephenson
British Journal of Surgery, 2023

1. Trends in short-term renewable and load forecasting for applications in smart grid [DOI]
with Deepa Kundur and Dongchan Lee
Smart City 360, 2016

Industry Project

1. A hybrid optimization approach for employee rostering: Use cases at Swissgrid and lessons learned [arXiv]
with Evangelos Vrettos
Swissgrid Ltd., Aarau, Switzerland, 2021

Presentations

  • Applied Probability Society: 2025 (scheduled)
  • MSOM: 2025 (scheduled)
  • Winter Simulation Conference: 2024
  • INFORMS Annual Meeting: 2022, 2023, 2024
  • CORS Annual Conference: 2024, 2025
  • INFORMS Healthcare Conference: 2023

Teaching

As an instructor:

  • MIE 368: Analytics in Action (2024)
    Third-year undergraduate class in applied analytics, University of Toronto.

As a teaching assistant:

  • MIE 368: Analytics in Action (2022, 2023)
    Third-year undergraduate class in applied analytics, University of Toronto.

  • MIE 1613: Stochastic Simulation (2023, 2024)
    Graduate class in stochastic modeling and simulation, University of Toronto.

  • Volunteer Instructor for Statistics Without Borders (2023)
    Topic: Machine learning (link to online video lesson)

  • MGOD 31: Advanced Business Data Analytics (2022)
    Third-year undergraduate class in applied machine learning, University of Toronto Scarborough.

Awards

Service

Ad-hoc journal referee:

  • Health Care Management Science

Conference session chair:

  • CORS Annual Conference 2025
  • INFORMS Annual Meeting 2024
  • INFORMS Healthcare Conference 2023