岩澤 諄一郎
Solutions Architect at NVIDIA. LLM training/inference for enterprise.
I work with Japanese enterprise customers on large language model training and inference. Previously a researcher and tech lead at Preferred Networks, building medical LLMs and deep-learning solutions for healthcare.
Led the research building the first open LLMs to beat GPT-4 on the JMLE.
Deep-learning diagnostic support developed with a leading pharmaceutical company.
Predicting antibiotic-resistance fitness landscapes from large-scale evolution experiments.
Algebraic correlations and anomalous fluctuations in ordered flocks of active particles.
As a Solutions Architect at NVIDIA, I work with Japanese enterprise customers on large language model training and inference, with a focus on the NeMo framework. I joined NVIDIA in February 2026.
Previously, as a Researcher and Tech Lead at Preferred Networks Inc., I engaged with clients in the healthcare and life sciences sectors and led BtoB solutions built on large language models.
I have experience formulating problems through consultation with clients and delivering deep-learning / machine-learning solutions, and I was the main mentor for four research interns and one part-time engineer.
During my PhD in the Department of Physics at the University of Tokyo, I developed machine-learning methods for gene expression and mutation data to tackle antibiotic resistance in bacteria.
Junichiro Iwasawa (岩澤 諄一郎)
Feb. 2026 – present
Solutions Architect
NVIDIA
Mar. 2025 – Jan. 2026
Tech Lead
Preferred Networks Inc
Apr. 2021 – Jan. 2026
Researcher
Preferred Networks Inc
Apr. 2018 – Mar. 2021
Doctor of Philosophy
Furusawa Laboratory, Dept. of Physics, The University of Tokyo
Apr. 2016 – Mar. 2018
Master of Science
Sano Laboratory, Dept. of Physics, The University of Tokyo
Apr. 2012 – Mar. 2016
Bachelor of Science
Dept. of Physics, The University of Tokyo