Last updated : October 07, 2022
- Areas of Expertise
- Comparative political economy
- political methodology (formal modeling, machine learning)
- Japanese politics
After earning a law degree from the University of Tokyo, joined the Ministry of International Trade and Industry (MITI, now the Ministry of Economy, Trade, and Industry, or METI) in 1991. At MITI and METI, served as assistant director for the Aircraft and Defense Industries Division, deputy director for the International Economic Division, and senior fellow at the Research Institute of Economy, Trade, and Industry (RIETI). Also served as associate professor at Yokohama National University and professor at the International University of Japan (IUJ). Received an MBA (with honors) from Harvard Business School and PhD in political science from the University of Michigan. Is concurrently a visiting professor at IUJ.
Kato, S., T. Nakanishi, Y. Seki, and B. Ahsan. 2021. “Estimating media effects from an ideologically diverse news curation platform.” Presented at the annual meeting (2021) of the American Political Science Association (APSA).
Ahsan, B., S. Kato, and S. Ibaragi. 2021. “Forecasting Japanese elections by applying ensemble learning methods.” TKFD Working Paper Series. 20-05. Originally presented at the annual meeting (2020) of the American Political Science Association (APSA).
Kato, S., T. Nakanishi, B. Ahsan, and H. Shimauchi. 2021. “Time-series topic analysis using singular spectrum transformation for detecting political business cycles.” Journal of Cloud Computing 10-21. Springer.
Xuan, L., S. Kato, B. Ahsan, and T. Nakanishi. 2021. “Co-detecting visuals and scene texts: A joint deep learning model for image classification.” Presented at the annual meeting (2021) of the Midwest Political Science Association (MPSA).
Kato, S. and I. Yoshimoto. 2020. “Why did Abe’s popularity fall during pandemic?” East Asia Forum Quarterly. 12-3. Australian National University.
Kato, S. 2020. “Political economic transition and output loss: Evidence from Japanese Political Economy 1990-2005.” TKFD Working Paper Series. 20-04. Originally presented at the annual meeting (2019) of the Midwest Political Science Association (MPSA).
Kato, S., T. Nakanishi, H. Shimauchi, and B. Ahsan. 2019. “Topic variation detection method for detecting political business cycles. Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT ’19).” ACM, New York, NY, USA, 85-93.