I am a third-year Ph.D. student in statistics at the University of Chicago, Booth School of Business. My CV is available here.

I’m broadly interested in the mathematical theory and algorithms underlying statistics and machine learning, as well as applied research in modern AI. My previous research has focused on high-dimensional statistics, high-dimensional probability and geometry, and combinatorial stochastic processes.

Preprints

• Power-law clustering with Gibbs partitions: universal estimation and predictive limits Takuya Koriyama, working paper.

• A Markov Chain Approach to Preference Alignment
  Takuya Koriyama and Tengyuan Liang arXiv:2606.22652, 2026. [slides]

• Existence of solutions to the nonlinear equations characterizing the precise error of M-estimators
  Pierre C. Bellec and Takuya Koriyama (alphabetical order)
  arXiv:2312.13254, 2023, submitted. [slide]

Publications

• Asymptotic Inference for Exchangeable Gibbs Partitions
  Takuya Koriyama
  Stochastic Processes and their Applications, 202, 105074, 2026. [short slide]

• Asymptotics of resampling without replacement in robust and logistic regression
  Pierre C. Bellec and Takuya Koriyama (alphabetical order)
  Bernoulli, 32(4) 3063-3087, 2026.

• Denoising Diffusions with Optimal Transport: Localization, Curvature, and Multi-Scale Complexity
  Tengyuan Liang, Kulunu Dharmakeerthi, and Takuya Koriyama
  Transactions on Machine Learning Research, 2835-8856, 2026.

• Precise asymptotics of bagging regularized M-estimators
  Takuya Koriyama, Pratik Patil, Jin-Hong Du, Kai Tan, and Pierre C. Bellec
  The Annals of Statistics, 54(2) 796-833, 2026. [github]

• Phase transitions for the existence of unregularized M-estimators in single index models
  Takuya Koriyama and Pierre C. Bellec
  Proceedings of the 42nd International Conference on Machine Learning (ICML2025).

• Asymptotic mixed normality of maximum likelihood estimator for Ewens–Pitman partition
  Takuya Koriyama, Takeru Matsuda and Fumiyasu Komaki
  Advances in Applied Probability, 58(1) 214-234, 2026

• Error estimation and adaptive tuning for unregularized robust M-estimator
  Pierre C. Bellec and Takuya Koriyama (alphabetical order)
  Journal of Machine Learning Research 26 (16), 1-40, 2025.

• Corrected generalized cross-validation for finite ensembles of penalized estimators
  Pierre C. Bellec, Jin-Hong Du, Takuya Koriyama, Pratik Patil and Kai Tan (alphabetical order)
  Journal of the Royal Statistical Society Series B: Statistical Methodology, 87(2), 289-318, 2025. [journal], [slide], [github].

• Fully Data-driven Normalized and Exponentiated Kernel Density Estimator with Hyvärinen Score
  Shunsuke Imai, Takuya Koriyama, Shouto Yonekura, Shonosuke Sugasawa and Yoshihiko Nishiyama
  Journal of Business & Economic Statistics 43 (1), 110-121, 2025. [journal]

Education

• 2024-present. PhD student in Econometrics and Statistics at The University of Chicago, Booth School of Business. Advisor: Tengyuan Liang.
• 2022-2024. PhD student in Statistics at Rutgers University. Advisor: Pierre C. Bellec.
• 2018-2022. BE in Mathematical Engineering, The University of Tokyo, MEIP.