2018: DATA DEMOCRACY DAYS Excellence Award
2021: Prime Minister’s Award, 3rd Japan Open Innovation Prize
2021: Published the book “Foundations of Practical Machine Learning”
2021: Entered the Ph.D. Program, Department of Computer Science, Cornell University
2019-2022: Published many research papers at top-tier conferences in the field of machine learning and data mining (ICML, NeurIPS, WSDM, RecSys, SIGIR, SDM). Won the Best Paper Runner-Up Award at WSDM2022.

As a Ph.D. student in the Department of Computer Science at Cornell University, I am working on machine learning, counterfactual evaluation, and fairness in ranking systems. In particular, I have been actively engaged in fundamental research on developing counterfactual estimators for large-scale problems and redefining fairness in ranking. I am also developing open-source software and writing books to make these techniques easy and accurate for anyone to use. Through these research, development, and dissemination activities, my goal is to make counterfactual evaluation and fair ranking techniques tangible and practical. In the long run, I hope to create new research fields on my own through activities and exchanges at the university and foundation.