H106 - ST-21 - Session programs - SCEJ 54th Autumn Meeting (Fukuoka, 2023)

`SCEJ 54th Autumn Meeting (Fukuoka, 2023)`

Last modified: 2023-12-10 19:09:26

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Session programs : ST-21 : H106

The preprints(abstracts) are now open (Aug. 28). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants and invited persons are required.

ST-21 [Trans-Division Symposium]
Frontiers of Data-driven Research and Development

Organizers:

Shimada Iori (Shinshu Univ.), Kim Sanghong (Tokyo Univ. of Agri. and Tech.), Toya Yoshihiro (Osaka Univ.), Kaneko Shogo (Sumitomo Chemical), Mukaida Shiho (Mitsui Chemicals), Muroga Shun (AIST)

Data science has been rapidly developing in recent years as the fourth science following experimental science, theoretical science, and computational science. In the field of chemical engineering, data-driven science, which derives superior materials and processes by making full use of a large amount of accumulated data and information, is becoming increasingly important, and many efforts are being made. This symposium will have speakers who are making pioneering efforts toward a data-driven society from various viewpoints and discuss future research and development.

Hall H, Day 1 | Hall H, Day 2

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Hall H(835), Day 1(Sep. 11)
(9:00–10:40) (Chair: Shimada Iori)
9:00– 9:20	H101	Development of machine learning model for CO₂ absorption performance of blended amine solutions (AIST) *(Reg)Fujii Tatsuya, (Reg)Kohno Yuki, (Reg)Makino Takashi, (Tokyo Tech) Sako Masami, Ishihama Keisuke, Yasuo Nobuaki, Kawauchi Susumu	CO2 absorption machine learning amine	ST-21	445
9:20– 9:40	H102	Predicting Physical Properties of Structurally Unknown Polymers Using Spectroscopy Data (Resonac) (Cor)Nagai Yuuki	Machine Learning Predict Descriptor	ST-21	353
9:40– 10:00	H103	(withdrawn)		100	364
10:00– 10:20	H104	[Featured presentation] Multimodal Deep Learning for Predictions of Various Properties of Composite Materials (AIST) *(Reg·PCEF)Muroga Shun, Miki Yasuaki, Hata Kenji	multimodal deep learning materials informatics generative deep learning	ST-21	602
10:20– 10:40	H105	Construction of MI platform for functional materials (Resonac) (Cor)Sekiguchi Kazuhide	Materials informatics DX	ST-21	450
(10:40–11:20) (Chair: Kaneko Shogo)
10:40– 11:20	H106	[Invited lecture] Material exploration and process optimization by digital technology (NAIST) Fujii Mikiya	Materials Informatics Process Informatics Quantum Chemistry	ST-21	784
(11:20–12:00) (Chair: Mukaida Shiho)
11:20– 12:00	H108	[Invited lecture] Data-driven Approaches for Functional Materials Development in SEKISUI CHEMICAL. (Sekisui Chemical) (Cor)Masuyama Yoshikazu	Data-Driven Development Functional Materials Materials Informatics	ST-21	976
(13:00–13:40) (Chair: Mukaida Shiho)
13:00– 13:40	H113	[Invited lecture] Remote Operation Support and Automatic Plant Operation Technology In Waste-to-Energy Plants (JFE Eng.) (Cor)Kojima Hiroshi	Remote operation Automatic operation AI and Data analysis	ST-21	979
(13:40–15:20) (Chair: Toya Yoshihiro)
13:40– 14:20	H115	[Invited lecture] Prediction and control of bacterial evolution through high-throughput automated experiments using robots (RIKEN) *Shibai Atsushi, Furusawa Chikara	Laboratory automation Laboratory evolution Escherichia coli	ST-21	805
14:20– 14:40	H117	Deep learning model for predicting all protein-protein interactions from sequence data (Kyutech) *(Reg)Kurata Hiroyuki, Tsukiyama Sho	Cross attention deep learning prediction	ST-21	33
14:40– 15:00		Break
15:00– 15:20	H119	Development of mechanistic cell cultivation models in monoclonal antibody production using data-driven insights (UTokyo) *(Stu)Okamura K., (Int)Badr S., (Stu)Ichida Y., (Reg·SPCE)Yamada A., (Reg)Sugiyama H.	Biopharmaceuticals Lactate consumption Glutamine	ST-21	728
(15:20–17:00) (Chair: Muroga Shun)
15:20– 15:40	H120	Development of microbial production process by model based metabolic design and directed evolution (Osaka U.) *(Reg)Shimizu Hiroshi, (Reg)Toya Yoshihiro, (RIKEN) Furusawa Chikara, Shibai Atsushi, (AIST) Horinouchi Takaaki, (Chuo U.) Suzuki Hiroaki, (Osaka U.) Tokuyama Kento, (Reg)Niide Teppei	Model based metabolic pathway design Directed evolution Metabolic engineering	ST-21	225
15:40– 16:00	H121	Machine learning guided enzyme’s molecular recognition specificity conversion (Osaka U.) *(Reg)Niide Teppei, Sugiki Sou, Mori Seiya, (Reg)Toya Yoshihiro, (Reg)Shimizu Hiroshi	enzyme design machine learning	ST-21	235
16:00– 16:20	H122	High accuracy prediction of edible oil oxidation stability by multivariate analysis incorporating chemiluminescence information (Tohoku U.) *(Stu·PCEF)Yoshida Yuta, (Reg)Hiromori Kousuke, (Reg)Shibasaki-Kitakawa Naomi, (Reg)Takahashi Atsushi	multivariate analysis oxidative stability edible oil	ST-21	686
16:20– 16:40	H123	Application of reaction mechanism search method using chemical reaction neural network to glycerol oxidation reaction (Shinshu U.) *(Stu)Shionoya Tomoki, (Reg)Shimada Iori	physics informed neural network kinetics model data-driven	ST-21	480
16:40– 17:00	H124	Applicational study of symbolic regression to exploring new materials and constructing kinetics models (Waseda U.) *(Stu)Isoda T., Takahashi S., (WISE/Mitsubishi Chemical Group) Nakano M., (WISE) Nakajima Y., (Waseda U./WISE) Seino J.	Machine learning Materials Informatics Reaction Kinetics	ST-21	948
Hall H(835), Day 2(Sep. 12)
(9:00–10:20) (Chair: Kaneko Shogo)
9:00– 9:20	H201	Elucidation of appropriate data acquisition conditions for API concentration prediction by NIR (Kyoto U.) *(Stu)Fukuoka Norihiko, (Powrex/TUAT) (Reg)Oishi Takuya, (Powrex) (Reg)Nagato Takuya, (TUAT) (Reg·APCE)Kim Sanghong, (Kyoto U.) (Reg)Sotowa Ken-Ichiro	NIR Spectrum diffuse reflectance measurement API concentration prediction	ST-21	741
9:20– 9:40	H202	Development of a soft sensor and a controller system of hydrogen concentration in the exhaust gas in fuel cell systems (TUAT) *(Stu)Izawa Taisei, (Reg·APCE)Kim Sanghong, (Reg)Matsumoto Miyuki, (Kyoto U.) (Reg)Hasegawa Shigeki, (Reg)Kawase Motoaki	PEFC Hydrogen control soft sensor	ST-21	203
9:40– 10:00	H203	Novel encoding method for high dimensional power consumption data in distributed energy system for short-term electricity demand forecasting (TokyoTech) *(Stu)Lee Hyojae, (Stu)Tsuda Shunsaku, (Stu)Iijima Taiki, (Reg)Kameda Keisuke, (Reg)Manzhos Sergei, (Reg)Ihara Manabu	electricity demand prediction distributed energy system big data	ST-21	550
10:00– 10:20	H204	Calculation of Tokyo's Photovoltaic Potential and Study of the Effects of Reducing Daily Power Fluctuations from Facade Installations (Tokyo Tech) *(Stu)Wang Shuai, (Stu)Oya Masashi, (Reg)Kameda Keisuke, (Reg)Manzhos Sergei, (Reg)Ihara Manabu	Facade installation Photovoltaic power potential Power fluctuation	ST-21	646
(10:20–12:00) (Chair: Kim Sanghong)
10:20– 10:40	H205	Gaussian Process Regression Approaches for Process Optimization: A Case Study of Interface State Density Prediction between Insulator and Semiconductor (NAIST) *(Stu)Matsunaga K., (AIST) Uenuma M., (NAIST) Sato A., Uraoka Y., Miyao T.	Gaussian process regression length-scale Metal-oxide-semiconductor	ST-21	204
10:40– 11:00	H206	Design of integrated upstream and downstream monoclonal antibody production processes using surrogate models (U. Tokyo) *(Stu)Shigeyama Akinori, (Reg)Hayashi Yusuke, (Int)Badr Sara, (Reg)Sugiyama Hirokazu	Surrogate model Machine learning Bayesian optimization	ST-21	816
11:00– 11:20	H207	Utilization of Bayesian optimization in the process development of drug substance (Astellas Pharma) *(Reg)Morishita Toshiharu, Sumii Yuta, Hanada Shogo, Shimizu Takashi	DX Bayesian optimization Simulation	ST-21	167
11:20– 11:40	H208	Batch Bayesian optimization method for goal-oriented multi-objective functional materials design (Resonac) (Cor)Hanaoka Kyohei	Bayesian Optimization	ST-21	385
11:40– 12:00	H209	Bayesian Optimization Framework for Polymer Composites Design Using High Dimensional Past Materials Data (Resonac) *(Cor)Arai Ryosuke, (Cor)Sekiguchi Kazuhide, (Cor)Hanaoka Kyohei	Bayesian optimization DX Materials informatics	ST-21	187

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SCEJ 54th Autumn Meeting (Fukuoka, 2023)

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SCEJ 54th Autumn Meeting (Fukuoka, 2023)

Session programs : ST-21 : H106

ST-21 [Trans-Division Symposium] Frontiers of Data-driven Research and Development

`SCEJ 54th Autumn Meeting (Fukuoka, 2023)`

ST-21 [Trans-Division Symposium]
Frontiers of Data-driven Research and Development