Teaching

I teach quantitative modeling as a cycle of building a model, examining its assumptions, learning from data, and using the results to inform a decision. Queueing systems make uncertainty and congestion concrete; machine learning raises questions about what data can reveal and whether a prediction supports a policy change. My teaching and mentoring experience spans undergraduate tutorials, MBA and MMA analytics courses, industry-sponsored capstone projects, and a doctoral guest lecture on queueing causal models.

Teaching and Mentoring Experience

Guest Lecturer, Simon Business School, University of Rochester (Scheduled)

• PhD Seminar (Online): Queueing Causal Models: Comparative Analytics in Queueing Systems — December 4, 2026. Invited by Prof. Ricky Roet-Green.

Guest Speaker, Rotman School of Management, University of Toronto

• RSM3090: Queueing Theory - Models and Analysis (PhD) — Fall 2025

Teaching Assistant, Rotman School of Management, University of Toronto

• RSM1240: Statistics for Management (MBA) — Winter 2024, 2025
• RSM1282: Operations Management (MBA) — Winter 2025
• RSM8414: Tools for Probabilistic Models and Prescriptive Analytics (MMA) — Fall 2024
• RSM8432: Management Analytics Practicum (MMA) — Winter 2024
• RSM2408: Modeling and Optimization for Decision Making (MMA) — Fall 2023
• RSM8415: Service Analytics for Management Analysis (MMA) — Winter 2023
• RSM2405: Supply Chain Management (MBA) — Fall 2022

Project Coach, Master of Management Analytics (MMA) Program, Rotman School of Management, University of Toronto

• Host companies: Imperial Oil, Ontario Health, Scotiabank — Winter 2024

Teaching Assistant, The Chinese University of Hong Kong, Shenzhen (CUHKSZ)

• STA2002: Probability and Statistics II (Undergraduate) — Spring 2021
• MAT2040: Linear Algebra (Undergraduate) — Spring 2020
• CHM1001: General Chemistry (Undergraduate) — Fall 2019
• BIO2001: General Biology (Undergraduate) — Spring 2019

Teaching Interests

I am interested in teaching and developing courses in:

• Stochastic Models and Simulation
• Operations Management
• Business Analytics
• AI and Analytics for Operational Decisions

New course development is a future teaching interest.