Muroga Shun - Program search result - SCEJ 54th Autumn Meeting (Fukuoka, 2023)

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

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Program search result : Muroga Shun : 2 programs

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.

Authors field exact matches “Muroga Shun”; 2 programs are found. (“Poster with Flash” presentations are double-counted.)
The search results are sorted by the start time.

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Day 1 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
Day 1 15:20– 17:00	Chair: Muroga Shun
	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
	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
	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
	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
	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

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SCEJ 54th Autumn Meeting (Fukuoka, 2023)

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