Ian Yihang Zhu

Ph.D. Candidate
Department of Mechanical and Industrial Engineering

Contact: i.zhu [at] mail.utoronto.ca
CV: [PDF] (updated Sept. 2022)

headshot
About Me

I am a 5th year PhD candidate at the University of Toronto, supervised by Professors Merve Bodur and Timothy Chan. Previously, I completed my Master of Applied Science at UofT and my Bachelor of Science in Mathematics at UBC. My research interests broadly lie in the design of algorithms for data-driven estimation and decision-making problems in the context of transportation, supply chain analytics, and operations management. Two recurring themes that underlie my work is the use of (i) data and (ii) mathematical programming. Currently, my main research interest is in parameter estimation problems (i.e., inverse optimization): how they can be solved efficiently and be better integrated into downstream decision-making models.

I am on the 2022-2023 academic job market.

News/Upcoming Talks
  • 09/2022: I am a Finalist at the 2022 MSOM Student Paper Competition! Come watch me present this paper at INFORMS (Session SB34). At INFORMS, I will also present new work on robust optimization in [Session TA37].
  • 08/2022: I am an invited speaker for the [YinzOR Conference] at Carnegie Mellon University.
  • 06/2022: I will be chairing two sessions at CORS, one on [Robust Optimization] and another on [Bilevel Optimization].
  • 04/2022: I was invited to give a talk on Inverse Optimization, which you can find on [Youtube].
Completed Papers
  1. Inverse Optimization: Theory and Applications
    with Timothy C.Y. Chan and Rafid Mahmood
    Under review at Operations Research, 2022 [PDF]
  2. Got (the Best) Milk? Pooling Donations in Human Milk Banks with Machine Learning and Optimization
    with Timothy C.Y. Chan, Rafid Mahmood, Rachel K. Wong et al.
    Under review at Manufacturing & Service Operations Management, 2022
  3. Spatial Price Integration in Commodity Markets with Capacitated Transportation Networks
    with John R. Birge, Timothy C.Y. Chan and J. Michael Pavlin
    Operations Research, 2022 [DOI, PDF]
      Finalist, MSOM Student Paper Competition 2022
      Finalist, CORS Student Paper Competition 2022 (Open Category)
      Media coverage: Chicago Booth Review
  4. Inverse Mixed Integer Optimization: Polyhedral Insights and Trust Region Methods
    with Merve Bodur and Timothy C.Y. Chan
    INFORMS Journal on Computing, 2022 [DOI, PDF, Poster]
      First Place, CORS Student Paper Competition 2022 (Open Category)
  5. Advising Student-Driven Analytics Projects: A Summary of Experiences and Lessons Learned
    with Aaron Babier and Craig Fernandes
    INFORMS Transactions on Education, 2022 [DOI, PDF]
  6. Prediction of Protein and Fat Content in Human Donor Milk Using Machine Learning
    with Timothy C.Y. Chan, Rafid Mahmood, Rachel K. Wong et al.
    The Journal of Nutrition, 2021 [DOI]
Working Papers
  1. Network Flow Models for Robust Binary Optimization with Selective Adaptability
    with Merve Bodur and Timothy C.Y. Chan
    In preparation for INFORMS Journal on Computing
Teaching
  • MIE368: Analytics in Action
    University of Toronto, Teaching Assistant, Fall 2020, 2021
      MIE Group Teaching Assistant Award (2020-2021)
      MIE Teaching Assistant Award (2021-2022)
  • MIE263: Stochastic Operations Research
    University of Toronto, Teaching Assistant, Winter 2019, 2020
  • MATH110/104/190: Differential Calculus
    UBC, Teaching Assistant, 2014-2015
Past Conference Talks
  • 2022: Montreal Optimization Days, CORS/INFORMS International, CPAIOR
  • 2021 and before: INFORMS (x5), CORS, MSOM, MIP Workshop
Follow me on [Twitter]