About Me

Hi! My name is Jang. I am a 3rd-year Ph.D. student in Operations Research at the University of Toronto. My advisors are Timothy Chan and Vahid Sarhangian. Before joining U of T, I completed MSc. in Business Analytics at EPFL (2020) and BASc. in Engineering Science at U of T (2018).

My research focuses on data-driven modeling and control of stochastic dynamical systems with applications to healthcare operations management.

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

Working Papers

4. Dynamic Transfer Policies for Parallel Queues
with Timothy Chan and Vahid Sarhangian
In preparation for submission, 2023.

3. Optimizing inter-hospital patient transfer decisions during a pandemic: a queueing network approach [Preprint]
with Timothy Chan, Frances Pogacar, and Vahid Sarhangian
In preparation for resubmission to Manufacturing & Service Operations Management, 2023

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
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


  • INFORMS Annual Meeting: 2022, 2023 (scheduled)
  • INFORMS Healthcare Conference: 2023


  • MIE 368: Analytics in Action (2022), Teaching Assistant
    Senior undergraduate class in end-to-end analytics, University of Toronto.

  • MGOD 31: Advanced Business Data Analytics (2022), Teaching Assistant
    Senior undergraduate class in applied machine learning, University of Toronto Scarborough.

  • MIE 1613: Stochastic Simulation (2023), Teaching Assistant
    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)