Teaching
S12 (Spring) 2025
A12 (Fall) 2025
- Undergraduate seminar II.
(Sabbatical leave: Oct 2025 - Sep 2026)
Seminars
I am the (co-)organizer of:
Past lectures
U Tokyo: Graduate
- "Graduate Mathematical Statistics II" S2 2023
In 2023, we studied Lehmann and Casella "Theory of Point Estimation" Chapters 3 and 4. Grades were based on weekly homeworks and final. Open to undergraduate students.
- "Topics in Bayesian Statistics" (grad), 2016, 2018, 2019, 2021, 2022, 2024
[2022-2024] Reading group: Multivariate dynamic modeling (DDNM, SGDLM), Bayesian predictive synthesis, Polya-gamma mixture, among others.
[2021] Reading group: Prado, Ferreira and West (2021), Chapters 4, 10, 11 and 6.
[2018-2019] Discussion and lecture: non-informative priors for linear models, Bayesian Lasso and horseshoe, DLMs, FFBS, stochastic volatility models, mixture sampler, in addition to the contents covered in 2016.
[2016] Lecture: multivariate distributions, the basics of state space models, or DLMs, filtering and smoothing, the concept of discount factors, multivariate and matrix-variate extension, graphical models and modeling by hyper-(inverse) Wishart distribution.
Student presentation: graphical models, objective Bayes and g-prior, stochastic shotgun search, and parallel computation by GPUs.
U Tokyo: Undergraduate
- "Mathematical Statistics I & II" S12 2020, 2022
Elective for juniors and seniors of economics, this course offers the methodological basics in probability, distributional theory, asymptotic theory, point estimation and hypothesis testing, to take those who has completed "Statistics I & II" to the higher level of statistical science.
The contents covered in this lecture were selected from the textbook by Tatsuya Kubokawa (in Japanese), which required the same level of mathematical rigor as Casella and Berger (2006). I decided I wanted to teach by the classical chalk-and-talk, but also complemented it by the demonstration of statistical computing by R and the brief introduction to the recent research topics by slides. Problem sets were provided weekly and the final exam was based on those problems. The personal support from the lecturer and TA was available via emails and online meeting. In the 2020 academic year, 200+ students were registered for MS I, and 140+ for MS II.
"Good practice of online teaching at UTokyo," article in Japanese
- "Statistics I & II", A12 2017, 2019, 2021, 2024
Mandatory for sophomore students of economics major and elective for those of law science, this lecture covers the basics of statistics at a higher level to have students prepared for the advanced courses such as econometrics. The topics include EDA, introductory probability theory, point estimation and hypothesis testing. Computation with R is the integral part of the lecture. 400+ students registered for this lecture.
- "Mathematics I" S12 2018, 2020, 2024
Introductory linear algebra, open for both undergraduate and graduate students of economics. The conceptual aspects of linear algebra were emphasized, covering the general definition and properties of linear spaces and linear maps, and the examples included the functional space, differential equations, and others. Students were evaluated based on (almost) weekly homeworks, midterm and final. 100+ students registered for this class.
- Undergraduate seminar I & II.
[2023] We read West and Harrison (1997), Chapters 2, 3, 4, 11, 14 and 15, with coding and data analysis exercises.
[2024] Prado, Ferreira and West (2021), Chapters 1, 2 and 4.
- Undergraduate independent study "Proactive learning seminar" A12 2018
Reading group class for undergraduate students of economics. Textbook: Williams "Probability with Martingales", Chapters 9-12.
At Insititute of Statistical Mathematics