Yifeng Cao

My research centers on socially responsible operations and sustainable operations, with a particular focus on operations in the public sector, where a key challenge lies in balancing the trade-off between efficiency and fairness. A common theme in my work is the study of centralized resource allocation problems, in which limited resources must be allocated among competing players both efficiently and equitably. In terms of methodology, my research employs online optimization and stochastic matching queue models to study and design resource allocation systems.

I have completed two main research projects in this area:

1. In a centralized resource allocation setting, where a central decision maker allocates limited resources among a finite set of agents, I characterized the maximum efficiency loss, commonly referred to as the price of fairness, that results from incorporating fairness considerations under various fairness notions such as proportional fairness and max-min fairness.

2. In a public housing system, where a housing authority allocates available units to both new applicants and existing tenants requesting transfers, I designed a periodic review policy that accommodates both types of applicants while balancing efficiency and fairness.

3. In a parallel queueing system, where arriving customers choose among queues according to a conditional logit model, we analyzed the equilibrium and asymptotic behavior. We applied this framework to U.S.–Canada border services, capturing how travelers respond to congestion and delays across different entry points.

Currently, I collaborate with BC Housing, the provincial housing authority in British Columbia, Canada, to design a public housing allocation system that explicitly address the efficiency–fairness trade-off. This work supports the agency’s mission to enhance equitable access to safe, quality, and affordable housing for underserved and vulnerable populations.

1. Tight Bounds for the Price of Fairness. Yifeng Cao, Yichuan Ding and Daniel Granot. Minor revision in Operations Research.

   • Second Prize, Best Student Paper Award, 2025 POMS International Conference in China. 

   • Third prize, Best Paper Award Competition of the 17th International Conference of the Chinese Scholars Association for Management Science and Engineering (CSAMSE) 2025.

2. Asymptotic Behavior of Parallel Queueing Systems with Discrete-Choice Driven Arrivals. Yichuan Ding, Mahesh Nagarajan, Zhe George Zhang, Yifeng Cao. Second-round major revision in Operations Research.

3. (Job market paper) Optimizing Mobility and Fairness in Public Housing Allocation. Yifeng Cao, Yichuan Ding, Daniel Granot, Hao Zhang, and Weihua Zhang. Submitted to Operations Research.

   • Finalist,  "the 2025 Student Paper Competition in the Queueing and Applied Probability Special Interest Group" of Canadian Operational Research Society (CORS) Conference 2025.

   • Third prize, Best Paper Award Competition of the 17th International Conference of the Chinese Scholars Association for Management Science and Engineering (CSAMSE) 2025.

4. Nash Bargaining with Stochastic Player Weights. Yifeng Cao, Yichuan Ding, Daniel Granot. Manuscript in preparation.

• Optimizing Mobility and Fairness in Public Housing Allocation

  • INFORMS Annual Meeting, Atlanta, USA, October 2025. (Scheduled) 

  • Canadian Operational Research Society (CORS) Conference, Edmonton, Canada, June 2025.

  • MSOM Conference, London, United Kingdom, July 2025.

  • INFORMS Annual Meeting, Seattle, USA, October 2024.

• Tight Bounds for the Price of Fairness

  • INFORMS Annual Meeting, Seattle, USA, October 2024.

  • MSOM Conference, Minneapolis, USA, June 2024.

  • INFORMS Annual Meeting, Phoenix, USA, October 2023.

• Instructor, UBC Sauder School of Business

  • COMM 204 - Logistics and Operations Management (Summer 2024)

    • Core course of Bachelor of Commerce program

    • Introductory course for undergraduate students in the Bachelor of Commerce program. The course introduce the philosophy of operations management and covers classical topics, including process analysis, project management, queueing theory, forecasting, inventory management and supply chain management. 

• Teaching assistant, Sauder School of Business

  • COMM 414 Data Visualization and Business Analytics (Winter 2024/2025)

    • Introductory course of AI and its application in business setting.

    • This course examines the role of artificial intelligence and data analytics in solving real-world business problems. It introduces fundamental machine learning techniques and explores how AI is applied in practice through case studies drawn from diverse business contexts. Students will gain hands-on experience with tools such as R, learn to build and interpret predictive and prescriptive models, and develop the skills to generate business insights from data. Two written exams assess students’ technical knowledge, while case discussions and assignments reinforce practical application. The course is ideal for students interested in the intersection of AI, analytics, and business decision-making.

• Teaching assistant, McGill Desautels Faculty of Management

  • MGSC 702 - Stochastic System (Ph.D.)