Kento Nozawa is a 4th year Ph.D. student who does research on machine learning. His current research interests are self-supervised representation learning and PAC-Bayes theory. He is supervised by Dr. Issei Sato at Issei Sato Lab in The University of Tokyo. He is also a part-time research assistant at RIKEN AIP. During summer 2019, he visited UCL AI Centre and Inria Lille Nord Europe Modal team to work on PAC-Bayes and contrastive representation learning. In order to live, he've been working for Optuna as a part-time machine learning engineer at Preferred Networks, Inc. since April 2021.
Hopefully, I’ll be graduating in Sept. 2022, so I’m on the job market.
Journal / Conference papers
- Kento Nozawa and Issei Sato. Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning. In NeurIPS, 2021.
- Kento Nozawa, Pascal Germain and Benjamin Guedj. PAC-Bayesian Contrastive Unsupervised Representation Learning. In UAI, pages 21–30, 2020.
- Atsunori Kanemura, Yuhsen Cheng, Takumi Kaneko, Kento Nozawa and Shuichi Fukunaga. Imputing Missing Values in EEG with Multivariate Autoregressive Models. In EMBC, pages 2639–2642, 2018.