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
- 08/2022: I was an invited speaker for the [YinzOR Conference] at Carnegie Mellon University.
- 04/2022: I was invited to give a talk on Inverse Optimization, which you can find on [Youtube].
Completed Papers
-
Inverse Optimization: Theory and Applications
with Timothy C.Y. Chan and Rafid Mahmood
Major Revision at Operations Research, 2022 [PDF]
-
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.
Major Revision at Manufacturing & Service Operations Management, 2022
-
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
-
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)
-
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]
-
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
-
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]