Hongseok Namkoong

Hongseok Namkoong is an Assistant Professor in the Decision, Risk, and Operations division at Columbia Business School, Columbia University. He is affiliated with the Data Science Institute (DSI) and focuses on Financial and Business Analytics. He holds a Ph.D. from Stanford University and previously worked as a research scientist at Facebook Core Data Science.

His research integrates machine learning, operations research, and statistics to develop reliable methods for decision-making under uncertainty. Key areas include distributionally robust optimization, adaptive experimentation, AI fairness in compositional systems, and stability analysis under distribution shifts. His work emphasizes both theoretical rigor and practical implementations (e.g., DRO Python library, QGym simulation tool).

Recent publications (2024-2025) demonstrate a focus on: (1) Robust ML methods for distribution shifts, (2) Efficiency in data labeling and experimentation, (3) Fairness frameworks for AI systems, and (4) Applications in healthcare, queuing networks, and personalized LLMs. Over 60% of his latest articles address robustness/adaptation challenges.

Awards:

• Best Paper Award at NeurIPS
• Runner-up Best Paper Award at ICML
• INFORMS Applied Probability Society Best Student Paper

No specific grants, labs, or supervised students are mentioned in the provided text.