About me

I am a fourth year Ph.D candidate in Operations Research at the Insitute of Operations Research & Analytics (IORA) at NUS, working with Prof. Andrew Lim and Prof. Jussi Keppo. I earned a BS and MS in Industrial Engineering at EMINES School of Industrial Management, UM6P.

I am interested in Data-driven Decision-making, with a focus on leveraging problem structure to develop tailored decision-making tools. My current research lies on the intersection of stochastic control and robust decision-making and learning, with applications in Inventory Management, Financial Engineering, and Personalized Learning.

Research

Published Papers

• Dynamic Black-Litterman with Andrew Lim
  Accepted in Operations Research

Working Papers

• Integrating Forward-Looking Expert Views into Dynamic Factor models with Andrew Lim
• When Worst-Case Isn’t Robust: On The Limitations of Distributionally Robust Formulations in Secretary Problems with Andrew Lim
• Personalized Learning in Partially Observable Environments with Jussi Keppo and Tan Hong Ming
• Technical Note - Brownian Bridge From Noisy Observations With Andrew Lim

Teaching

Instructor

• DAO1704 Decision Analytics using Spreadsheets (Undergraduate Core, NUS Business School), Fall 2024

Teaching Assistant

• DBA3803 Predictive Analytics in Business (Undergraduate Core, NUS Business School), Spring 2024
• BDC6112 Stochastic Processes (PhD Core, NUS Business School), Fall 2022

Selected Talks

Integrating Forward-Looking Expert Views into Dynamic Factor models

• INFORMS Annual Meeting, October 2024, Seattle US
• Quantitative Finance Workshop, Singapore Management University, July 2025, Singapore

Dynamic Black-Litterman

• INFORMS APS Market Showcases, October 2024, Seattle US
• Quantitative Finance Workshop, Singapore Management University, July 2024, Singapore
• Mathematics & Decisions Conference, UM6P, December 2023, Morocco
• International Research & Innovation Seminar, UM6P, December 2023, Morocco
• INFORMS Applied Probability Society, June 2023, France (Poster Session)

Personalized Learning in Partially Observable Environments

• INFORMS Annual Meeting, October 2023, Arizona US