Taken in Sumida, Tokyo.

My goal is to understand and develop a trustworthy and reliable machine learning system that works with humans to provide knowledge and useful technology to society. Currently, I am a researcher at Preferred Networks, working on machine learning for healthcare and quantum chemistry domains.

Research interests: I am interested in machine learning algorithm analysis and design in general. More specifically, my current research topics include:

  • Loss function
  • Evaluation metric
  • Learning with reject option
  • Weakly supervised learning
  • Domain adaptation
  • Anomaly detection
  • Uncertainty quantification
  • Applications (e.g., healthcare data analysis, neural network potentials for quantum chemistry, speech signal processing, computer vision, natural language processing)

I completed a PhD student under the supervision of Prof. Masashi Sugiyama in Sugiyama-Yokoya-Ishida laboratory, Department of computer science, The University of Tokyo. During my Ph.D., I was honored with the Google Ph.D. Fellowship in Machine Learning (2020) and graduated with the Dean’s Award for outstanding research achievement. My doctoral thesis is “Theory and algorithms of machine learning with rejection based on loss function perspective”.

Links: Publications, CV