Cong Yang

Ph.D. Candidate
UBC, Vancouver, BC, Canada
Sauder School of Business

About Me

I’m currently a Ph.D. candidate in Management Science at the Sauder School of Business, University of British Columbia. My research focuses on decision making under uncertainty, with applications spanning partially observable Markov decision processes, inventory control, and healthcare operations. I obtained my M.S. and B.S. in Industrial Engineering and Operations Research from the University of California, Berkeley.

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Papers

For transparency, all co-first authors, or authors with higher orders will be displayed

Partially Observable Markov Dynamic Programming

Optimal Control of a Partially Observable Markov Deterioration Process
Cong Yang and Hao Zhang
Minor Revision in Management Science

Optimization and Learning

Optimal Policy for Inventory Management with Periodic and Controlled Resets
Yoon Lee, Yonatan Mintz, Anil Aswani, Zuo-Jun Max Shen, and Cong Yang
Manufacturing & Service Operations Management , 2025
A Nonparametric Learning Algorithm for a Stochastic Multi-echelon Inventory Problem
Cong Yang and Woonghee Tim Huh
Production and Operations Management , 2024
Optimal Control for Multi-Product Additive Manufacturing Systems
Harry Zhang, Cong Yang, Woonghee Tim Huh, Sergii Kravchenko
Working Paper

Healthcare Operations Research:

Feasibility of reidentifying individuals in large national physical activity data sets from which protected health information has been removed with use of machine learning
Liangyuan Na, Cong Yang, Chi-Cheng Lo, et al
JAMA Network Open (IF: 10.5) , 2018
The Impact of Organ Blood Type Conversion on Kidney Paired Donation: A Simulation and Optimization Study
Cong Yang, Woonghee Tim Huh, Steven Shechter, James Lan
Major Revision in American Journal of Transplantation (IF: 8.2)

Teaching Experience

COMM 190: Introduction to Quantitative Decision Making (Undergraduate), UBC
Instructor, Summer 2025
IEOR 240: Optimization Analytics (Graduate, Master of Engineering), UC Berkeley
Graduate Student Instructor, Fall 2019
STAT 2: Introduction to Statistics (Undergraduate), UC Berkeley
Graduate Student Instructor, Summer 2019
IEOR 142: Introduction to Machine Learning and Data Analytics (Undergraduate), UC Berkeley
Graduate Student Instructor, Fall 2019
BAMS 517: Decision Analysis Under Uncertainty (Graduate, Master of Business Analytics), UBC
Teaching Assistant, Winter 2022-2025
BABS 506: Analyzing and Modelling (Graduate, Master of Business Analytics), UBC
Teaching Assistant, Winter 2022-2025
COMM 190 (COMM 290): Introduction to Quantitative Decision Making (Undergraduate), UBC
Teaching Assistant, Winter 2021-2025
BAMS 500: Process Fundamentals (Graduate, Master of Business Analytics), UBC,
Teaching Assistant, Winter 2022

Awards

The University of British Columbia Affiliated Fellowships Doctoral Program, 2023
Shelby L. Brumelle Memorial Graduate Scholarship Competition, UBC, 2023 & 2025
President’s Academic Excellence Initiative PhD Award, UBC, 2021-2025
Dean Earle D MacPhee Memorial Graduate Scholarship, UBC, 2021-2025
International Tuition Award, UBC, 2021-2025
Finalists & Honorable Mention at INFORMS Undergraduate Student Operations Research Prize, 2019

Talks

Optimal Control of a Partially Observable Markov Deterioration Process

INFORMS 2025 Annual Meeting, Atlanta, GA, United States
INFORMS 2024 Annual Meeting, Seattle, WA, United States

A Nonparametric Learning Algorithm for a Stochastic Multi-echelon Inventory Problem

INFORMS 2023 Annual Meeting, Phoenix, AZ, United States

The Impact of Organ Blood Type Conversion on Kidney Paired Donation: A Simulation and Optimization Study

INFORMS 2023 Healthcare Conference, Toronto, ON, Canada

Feasibility of reidentifying individuals in large national physical activity data sets from which protected health information has been removed with use of machine learning

INFORMS 2019 Annual Meeting, Seattle, WA, United States
INFORMS 2019 Healthcare Conference, Boston, MA, United States

Skills

Languages | Fluent: English; Native: Mandarin, Cantonese
Programming | Proficient: Python, Matlab, R; Prior experience: SQL, Julia, C++
Software Tools | TensorFlow, Gurobi, CAD SolidWorks

References

Prof. Woonghee Tim Huh

Sauder School of Business
University of British Columbia
Tim.huh@sauder.ubc.ca

Prof. Steven M. Shechter
Sauder School of Business
University of British Columbia
steven.shechter@sauder.ubc.ca

Prof. Hao Zhang
Sauder School of Business
University of British Columbia
hao.zhang@sauder.ubc.ca