Kazuki Fujii

藤井一喜 Kazuki Fujii is an incoming PhD student at the Institute of Science Tokyo (formerly Tokyo Tech). He is a core contributor to the Swallow Project, leading the development of open Japanese-English bilingual LLMs.

His research sits at the intersection of HPC and Machine Learning, with a focus on large-scale distributed training and low-precision optimization (FP8/NVFP4) using Megatron-LM and TransformerEngine. He also researches data-centric approaches to improve reasoning capabilities in LLMs. His recent work on rewriting pre-training data for Math and Code was accepted to ICLR 2026.

He will be presenting his work on Swallow LLM at NVIDIA GTC 2026. He is currently seeking research internship opportunities in the US.

Contact: kazuki.fujii [at] rio.scrc.iir.isct.ac.jp

CV Publications Blog Blog(Japanese)

Research Interests

2023 2024 2025 2026

Distributed Training

Continual Pre-Training

Low Precision Training

Data Improvement

Diffusion LM

RLVR

VLA

Education

2026 – 2029 PhD in CS, Institute of Science Tokyo Adv: Rio Yokota

2024 – 2026 MS in CS, Institute of Science Tokyo Adv: Jun Sakuma

2020 – 2024 BS, Tokyo Institute of Technology Adv: Rio Yokota

2016 – 2019 Azabu High School (麻布高等学校)