Kengo Kamatani

Associate Professor (Koushi; Lecturer)
Graduate School of Engineering Science, Osaka University, and JST CREST
kamatani at
1-3 Machikaneyama-cho, Toyonaka, Osaka, Japan

Research Interest

My background is Mathematical Sciences, and my main interest is in Bayesian Computation. Bayesian Statistics is a branch of Statistics (or Data Science), and Bayesian Computation helps evaluation of the posterior inference, which is the most important object for Bayesian Statistics. See monographs such as Doing Bayesian Data Analysis by Kruschke, and Bayesian Data Analysis by Gelman et al. See also The International Society for Bayesian Analysis webpage. You might be interested in a nice blog by Prof. A. Gelman.

I am interested in the theoretical aspects of Bayesian Computation. More specificaly, I am working on the analysis of Markov chain Monte Carlo, Particle Filter/Sequential Monte Carlo and other related methods. In addition, I am interested in the inference of stochastic processes.


Future Events: I will organize an Organized Invited Session at EcoSta (25-27 June 2019), Topic Contributed Session at EMS (22-26 July), and Invited Paper Session at ISI Malaysia (18-25 Aug2019).
Talk ''Bayesian inference for stable Levy driven stochastic differential equations with high-frequency data'' at Pisa in December
Talk ''Scaling limits of piecewise deterministic Mont Carlo methods'' at Manchester in November [ abst ]
Talk ''Reversible proposal MCMC with heavy-tailed target distributions'' at Singapore in September