Jangwon Park

Jangwon Park

PhD student in operations research

About Me

Hi! My name is Jang. I am a 4th-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

5. Robust confidence bands for stochastic processes using simulation [Preprint]
with Timothy Chan and Vahid Sarhangian
Under review
      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

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

  • Winter Simulation Conference: 2024 (scheduled)
  • INFORMS Annual Meeting: 2022, 2023, 2024 (scheduled)
  • CORS Annual Conference: 2024
  • INFORMS Healthcare Conference: 2023

Teaching

As an instructor:

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

As a teaching assistant:

  • MIE 368: Analytics in Action (2022, 2023)
    Senior 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)
    Senior undergraduate class in applied machine learning, University of Toronto Scarborough.

Awards