معرفی
Tenichi Cho is an Assistant Professor (without tenure) at the Center for Data Science, Waseda University, Japan. He specializes in sedimentary geochemistry, palaeoclimate reconstruction and compositional-data analysis, with a focus on Mesozoic oceanic anoxic events and chemical weathering proxies. Since 2023 he has led competitive JSPS grants and teaches an extensive portfolio of data-science courses across Waseda’s Global Education Center.
Education:
- Ph.D. 2023, Waseda University, Graduate School of Creative Science and Engineering (Earth Sciences, Resources and Environmental Engineering)
- B.Sc. 2018, Waseda University, School of Education, Department of Science (Earth Science Major)
Research Interests: Sedimentology, palaeoenvironmental change, chemical weathering indices, Cretaceous and Triassic climate extremes, global warming feedbacks, and multivariate statistical techniques applied to sedimentary compositional data.
Recent Publications Trend: Cho’s 2022–2025 articles reveal a consistent trajectory in high-resolution chemostratigraphy, combining novel weathering indices (RW index) with redox-sensitive element and isotope analyses to decode Jurassic and Triassic environmental crises such as the Toarcian OAE and the Carnian Pluvial Episode. His work increasingly couples field-based sedimentary records with quantitative data-science tools.
Scientific Awards:
- Best Oral Presentation, 37th IGC (2024)
- GeoSciAI2024 Award, JpGU (2024)
- Sedimentological Society of Japan Paper Award (2024)
- Waseda Early-Bird Best Collaborative Research Award (2022)
- Best Poster, IGCP 679 (2019)
Grants & Projects: Cho currently heads two JSPS KAKENHI projects (2024-2027) targeting universal palaeoclimate proxies and carbon-cycle feedbacks, and has completed Waseda and Fukada Geological Institute grants on Cretaceous Asian weathering and Triassic volcanism–climate coupling.
Teaching & Labs: He delivers over 30 undergraduate data-science and statistics courses each year at Waseda’s Global Education Center, spanning introductory literacy to advanced modelling with R and Python, and is affiliated with the university’s Center for Data Science research community.
