Ryo FUKASAWA

LD3(D1)

mail

ryo.fukasawa@toki.waseda.jp

Academic Background

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

Group

Materials Infomatics Group

Research Theme

Development of high-performance perovskite solar cells by process informatics.
Development of machine learning potentials suitable for organic-inorganic hybrid materials.

Research Keywords

Machine Learning, Process Informatics, Solar Cell

Membership

The 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

Awards

Studying abroad

Papers

[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)