CD108 - Hall CD, Day 1 - Hall and day program - SCEJ 56th Autumn Meeting (Tokyo, 2025)

`SCEJ 56th Autumn Meeting (Tokyo, 2025)`

Last modified: 2025-09-29 10:33:36

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Hall and day program : Hall CD, Day 1 : CD108

The preprints(abstracts) are now open. These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants (excludes free registration) and invited persons are required.

Hall CD(C.A. Bldg. 3F 301), Day 1(Sep. 16)

ST-21

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
ST-21 [Trans-Division Symposium] Frontiers of Data-driven Research and Development
(9:20–10:20) (Chair: Shimada Iori)
9:20– 9:40	CD102	High-resolution flow analysis in cell culture tanks using a combination of PINNs and CFD (Akita U.) *(Reg)Horiguchi Ikki, (U. Osaka) Shima Keisuke, (Stu)Mizukami Yuto, (Reg)Okano Yasunori	Suspension culture Computational flow dynamics Neural Networks	ST-21	171
9:40– 10:00	CD103	Prediction of electrostatic inkjet printing characteristics using CNN with electric field distribution as input (Tokyo U. Sci.) *(Reg)Matsukawa Hiroaki, (Reg)Otake Katsuto	Electrostatic inkjet Convolutional Neural Networks Electric field distribution	ST-21	97
10:00– 10:20	CD104	Novel feature suggestion for Predictive Model of the Bacterial Reverse Mutation Test (Kogakuin U.) *(Stu)Kondo Kazuma, (Stu)Miyatake Koshiro, (Reg)Higuchi Hayato, (Reg)Miyagawa Masaya, (Reg)Takaba Hiromitsu	Machine Learning Variational Autoencoder COSMO method	ST-21	744
10:20– 10:40		Break
(10:40–12:00) (Chair: Muroga Shun)
10:40– 11:20	CD106	[Invited lecture] Practical studies of data-driven materials research based on accelerating the data cycle (Science Tokyo) Ando Yasunobu	autonomous experiment machine learning potential spectral analysis	ST-21	939
11:20– 12:00	CD108	[Invited lecture] Accelerating Catalyst Development through High-Throughput Experiments (AIST) Fujitani Tadahiro	Catalyst development High-throughput screening Autonomous experimentation	ST-21	935
(13:00–14:20) (Chair: Mukaida Shiho)
13:00– 13:40	CD113	[Invited lecture] Machine learning-enabled spectroscopy and materials discovery (U. Tokyo) Mizoguchi Teruyasu	Machine learning XANES/ELNES Materials discovery	ST-21	938
13:40– 14:20	CD115	[Invited lecture] Optimization Applications in Business and Information Systems (NS Solutions) Minami Etsuro	Optimization Problems Combinatorial Optimization Business Applications	ST-21	946
(14:20–16:20) (Chair: Toya Yoshihiro)
14:20– 15:00	CD117	[Invited lecture] Perspectives and Challenges in Laboratory Automation Supporting Data-Driven Science in the field of Biotechnology (Riken) Horinouchi Takaaki	Laboratory automation Biotechnology Data-Driven Science	ST-21	945
15:00– 15:20		Break
15:20– 15:40	CD120	Development of automated and autonomous experimental systems for electrode slurry: challenges and approaches (Toyota Central R&D Labs) *(Cor)Kudo Sayako, (Cor)Matsunaga Takuro, (Cor)Makino Soichiro, (Cor)Kusano Takumi, (Cor)Yamawaki Yuya, (Reg)Nakamura Hiroshi, (U. Tokyo) (Stu)Oya Hirotaka, (Reg)Nagato Keisuke	automatic and autonomous laboratory slurry viscosity	ST-21	346
15:40– 16:00	CD121	A Heterogeneous Transfer Learning Approach for Manufacturing Method Transitions in Pharmaceutical Processes (Kyoto U.) *(Stu)Ihira Junya, (Daiichi Sankyo) (Reg)Yaginuma Keita, (Cor)Sato Kanta, (Kyoto U.) (Reg)Kato Shota, (Reg)Kano Manabu	Heterogeneous Transfer Learning Manufacturing Method Transition Pharmaceutical Manufacturing	ST-21	471
16:00– 16:20	CD122	Development of a method for predicting drug-drug interactions using food ingredients as substitute for negative data (Meiji U.) *(Stu)Kosakai Soma, (Reg)Kaneko Hiromasa	Drug-drug interaction Machine learning Positive-unlabeled learning	ST-21	178

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SCEJ 56th Autumn Meeting (Tokyo, 2025)

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