Scholar
Hongseok Namkoong
Google Scholar ID: dyXX1EgAAAAJ
Columbia University
Citations & Impact
Citations
8,918
H-index
21
i10-index
27
Publications
20
Co-authors
37
list available
Publications
Resume (English only)
Academic Achievements
- Selected publications include 'Data-driven Stochastic Modeling using Autoregressive Sequence Models' (2025) and 'Optimization-Driven Adaptive Experimentation' (2024), which was selected for oral presentations at the Econometric Society Interdisciplinary Frontiers: Economics and AI+ML conference and the Conference on Digital Experimentation.
Research Experience
- He is currently an Assistant Professor in the Decision, Risk, and Operations division at Columbia Business School and a member of the Data Science Institute. He has also served as a LinkedIn Scholar at LinkedIn’s Core AI team.
Education
- Before joining Columbia, he received his Ph.D. from Stanford University and spent a year at Meta’s Adaptive Experimentation team as a research scientist.
Background
- Research interests include building trustworthy AI systems capable of solving real-world decision-making problems. He takes a data-centric view of AI systems and believes in algorithmic ideas grounded in empirical foundations and principled thinking. As an interdisciplinary researcher, he connects and extends tools from machine learning, operations research, and statistics.
Miscellany
- Personal interests not mentioned.
