Ryo FUKASAWA
LD2(M2)
mailryo.fukasawa@toki.waseda.jp
March, 2018 Graduated from Tokyo Gakugei University Senior High School
April, 2019 Entered Department of Life Science and Medical Bioscience, Faculty of Advanced Science and Engineering, Waseda Univ.
April, 2019 – March, 2023 Department of Life Science and Medical Bioscience, School of Advanced Science and Engineering, Waseda University (B.Sc.)
April, 2023 – present Department of Advanced Science and Engineering (5-year Doctoral Program), Graduate School of Advanced Science and Engineering, Waseda University
Materials Infomatics Group
Research ThemeDevelopment of high-performance perovskite solar cells by process informatics.
Development of machine learning potentials suitable for organic-inorganic hybrid materials.
Machine Learning, Process Informatics, Solar Cell
MembershipThe Chemical Society of Japan, The Crystallographic Society of Japan, The Meteorological Society of Japan
Scholarships/Grants Academic Presentation< Poster presentation>.
[1] Application of process informatics in predicting the performance of perovskite solar cells.
Ryo Fukasawa, Toru Asahi, Takuya Taniguchi
P6-100, 12th CSJ Chemistry Festa, 18-20 Oct 2022, Funabori, Tokyo, Japan
[2] Performance prediction of perovskite solar cells by process informatics.
R. Fukasawa, T. Asahi, T. Taniguchi
PB-01, 2022 Annual Meeting of the Crystallographic Society of Japan, 26-27 Nov. 2022, Nishinomiya-Uegahara Campus, Kwansei Gakuin University, Nishinomiya, Japan.
[3] Prediction of perovskite solar cells' efficiency by process informatics
Ryo Fukasawa, Toru Asahi, Takuya Taniguchi
P0456, IUCr2023 (26th Congress and General Assembly of the International Union of Crystallography), 22-29 Aug 2023, Melbourne Convention and Exhibition Centre, Australia
[4] Stability evaluation of perovskite thin films using machine learning.
Ryo Fukasawa, Toru Asahi, Takuya Taniguchi
PB-07, 2023 Annual Meeting of the Crystallographic Society of Japan, 27-29 Oct. 2023, Ube City Cultural Hall, Ube, Japan
[5] Stability evaluation of organic-inorganic hybrid perovskite thin films using machine learning.
R. Fukasawa, T. Asahi, T. Taniguchi
P-011, 31st Symposium on Organic Crystals, 2-3 Nov 2023, Suita Campus, Osaka University, Osaka, Japan.
[6] Stability evaluation of organic-inorganic hybrid perovskite solar cells using machine learning.
R. Fukasawa, T. Asahi, T. Taniguchi
P-29, 2nd Soft Crystal Research Meeting, 23-24 Nov 2023, Nipponmaru Memorial Park Training Centre, Yokohama, Japan
< Oral presentations>
[1] Performance prediction of perovskite solar cells by process informatics.
Ryo Fukasawa, Toru Asahi, Takuya Taniguchi
K207-4pm-01, 103rd Spring Annual Meeting of the Chemical Society of Japan, 22-25 Mar 2023, Noda Campus, Tokyo University of Science, Noda, Japan
[2] Stability evaluation of perovskite thin films using machine learning.
Ryo Fukasawa, Toru Asahi, Takuya Taniguchi
C442-2pm-15, 104th Spring Annual Meeting of the Chemical Society of Japan, 18-21 Mar 2024, College of Science and Technology, Nihon University, Funabashi, Japan
[1] Ryo Fukasawa, Asahi Toru, Takuya Taniguchi. Effectiveness and limitation of the performance prediction of perovskite solar cells by process informatics, Energy Advances, 2024, Advance Article. doi:10.1039/D3YA00617D
Others[qualifications]
Certified weather forecaster (2014)
Passed the administrative law exam (2021)
Class A Dangerous Goods Handler's Certificate (2022)
JDLA Deep Learning for GENERAL (2023)
Certified Disaster Prevention Specialist (2023)
[competition prizes]
Naomichi Shiono Memorial 3rd "Free Research in Arithmetic and Mathematics" Competition, Grand Prize, Naomichi Shiono Prize (2015)
[special mentions]
Representative of Certified and Accredited Meteorologists of Japan Students (2023-ongoing)