Naoki Awaya

Naoki Awaya is an Assistant Professor at the School of Political Science and Economics, Waseda University. His research focuses on economic statistics, computational statistics, and financial econometrics with applications in machine learning and Bayesian inference.

• Education: Not explicitly stated
• Current Projects: Developing Bayesian estimation methods for nonstationary economic time series and structural changes

His work includes tree-based models for probability distributions and advanced MCMC sampling techniques. He teaches graduate-level econometrics courses (Econometrics I/II) using R programming, emphasizing methodological rigor and theoretical foundations. Research interests span high-dimensional data analysis, density ratio estimation, and financial market applications through multivariate Hawkes processes.

Recent publications highlight innovations in:

• Unsupervised tree boosting
• Hidden Markov Pólya trees
• Particle rolling MCMC algorithms
• Nonstationary errors-in-variables models