Junpei Komiyama

Biography

Junpei Komiyama joined New York University Stern School of Business as an Assistant Professor of Technology, Operations and Statistics in September 2019.

Professor Komiyama’s research interests lie in machine learning methodology and its application to business processes. His interests include decision making models such as the multi-armed bandit problem, designing experiments, analyzing algorithmic bias such as fairness in machine learning models and guaranteeing reproducibility of scientific findings. He is interested in re-thinking how we define findings with data science methods. His work has been presented in machine learning and data mining conferences such as Neural Information Processing Systems (NeurIPS) and Knowledge Discovery and Data Mining (KDD).

Before joining NYU Stern, Professor Komiyama worked in the University of Tokyo as a research associate. Professor Komiyama received his BTech and MS in Applied Physics from the University of Tokyo Engineering Department. He received his PhD in Information Science from the University of Tokyo Graduate School of Information Science.

Research Interests

• Machine Learning Methodology
• Decision-making Models
• Algorithmic Bias

Courses Taught

• Programming and Machine Learning

Academic Background

Ph.D., Information Science
University of Tokyo

M.S., Applied Physics
University of Tokyo

B.Tech.
University of Tokyo