Daniel J. Hsu

Dr. Daniel J. Hsu is a Professor of Computer Science at Columbia University, affiliated with the Foundations of Data Science Center and TRIPODS Institute. His research focuses on algorithmic statistics, machine learning theory, and their applications in public health informatics. He has advised numerous students and postdocs, and his work bridges foundational theory with practical systems like foodborne illness detection via social media analysis.

• Key roles: Associate Editor (ACM Transactions on Algorithms), Program Chair (ICML 2025, COLT 2019)
• Research areas: Foundations of Data Science, Machine Learning Theory, Fairness, and High-dimensional Statistics

His work on detecting foodborne illnesses using Yelp reviews has been deployed by NYC Health departments. Recent contributions include advancements in transformer architectures, group fairness algorithms, and multi-group learning frameworks.

Scientific awards include the Sloan Fellowship and multiple NSF grants. He has pioneered interactive machine teaching methods and developed algorithms for robust parameter estimation in high-dimensional settings.