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SCEJ 53rd Autumn Meeting (Nagano, 2022)

Last modified: 2022-12-14 13:12:56

Hall and day program : Hall DC, Day 3 : DC315

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Hall DC(C3 1F 102), Day 3(Sep. 16)

ST-21

TimePaper
ID
Title / AuthorsKeywordsTopic codeAck.
number
ST-21 [Trans-Division Symposium]
Frontiers of Data-driven Research and Development
(9:00–10:20) (Chair: Mukaida Shiho)
9:009:40DC301[Invited lecture] Data-driven AI Laboratory and Cyber Catalysis
(Shinshu U.) (Reg)Koyama Michihisa
Data-driven
Cyber Catalysis
Computational Chemistry
ST-21102
9:4010:20DC303[Invited lecture] AI-Driven peptide/antibody molecule design for drug discovery
(MOLCURE) Tamaki Satoshi
Artificial Intelligence
Drug Discovery
Antibody
ST-21316
(10:20–12:00) (Chair: Toya Yoshihiro)
10:2010:40DC305Data-driven analysis of charge variants in monoclonal antibody production
(U. Tokyo) *(Stu)Yoshiyama Yuki, (Int)Badr Sara, (Stu)Okamura Kozue, (Manufacturing Tech. Association of Biologics) Murakami Sei, (U. Tokyo) (Reg)Sugiyama Hirokazu
Charge variant
Monoclonal antibody
PLS
ST-21641
10:4011:00DC306Multi-step approach for data-driven equipment condition assessment in biopharmaceutical drug product manufacturing
(U. Tokyo) *(Int)Zuercher Philipp Samuel, (Int)Badr Sara, (ROCHE) Knueppel Stephanie, (U. Tokyo) (Reg)Sugiyama Hirokazu
Predictive maintenance
Unsupervised learning
Industrial application
ST-21590
11:0011:20DC307Reinforcement learning to optimally control the bio and chemical processes
(Kyoto U.) (Int)Oh Tae Hoon
Reinforcement Learning
Process control
Optimal control
ST-2160
11:2011:40DC308Soft sensor study in film manufacturing process
(Meiji U.) *(Stu)Nakayama Yuki, Shiraki Yuya, (Zeon) (Cor)Natori Satoshi, (Cor)Ono Yuki, (Cor)Suda Kazuya, (Meiji U.) (Reg)Kaneko Hiromasa
Soft sensor
Fault detection
Film manufacturing process
ST-21366
11:4012:00DC309Prediction of phase equilibrium of water-organic compounds system at high-temperature and high-pressure using machine learning
(Shinshu U.) *(Stu)Tamura Kotaro, (Reg)Shimada Iori, (Reg)Fukunaga Hiroshi, (Reg)Takahashi Nobuhide, (Reg)Osada Mitsumasa
machine learning
prediction of phase equilibrium
high-temperature and high-pressure
ST-21532
(13:00–14:20) (Chair: Kaneko Shogo)
13:0013:40DC313[Invited lecture] Exploration of functional inorganic thin-film materials using autonomous systems
(Tokyo Tech) Shimizu Ryota
autonomous synthesis
inorganic materials
functional thin films
ST-21103
13:4014:20DC315[Invited lecture] Data-driven polymer material development powered by Polymer SmartLab and Material DX
(NIMS) Naito Masanobu
smart lab
material DX
database
ST-21129
(14:20–15:40) (Chair: Shimada Iori)
14:2014:40DC317Inverse design of polymer membrane structure for gas separation using Junction Tree VAE machine learning
(Kogakuin U.) *(Stu)Matsumoto Takumi, (Reg)Miyagawa Masaya, (Reg)Takaba Hiromitsu
machine learning
polymer membrane
gas separation
ST-21712
14:4015:00DC318Design of both membrane-based process and membrane materials with machine learning
(Meiji U.) *(Stu)Yuyama Shunsuke, (Reg)Kaneko Hiromasa
Membrane module
Materials Informatics
Process design
ST-21187
15:0015:20DC319[Featured presentation] Development of digital twin of the bulk single crystal growth of Si by using PINNs (Physics Informed Neural Networks)
(Osaka U.) *(Stu)Takehara Yuto, (Reg)Okano Yasunori
Digital twin
Machine learning
Physics Informed Neural Networks
ST-21396
15:2015:40DC320Growth interface shape optimization and adaptive process control for InGaSb crystal growth under microgravity using machine learning
(Osaka U.) *(Stu)Ghritli Rachid, (JAXA-SOKENDAI) Inatomi Yuko, (Osaka U.) (Reg)Okano Yasunori
Machine Learning
Reinforcement Learning
Crystal Growth
ST-21428
(15:40–17:00) (Chair: Kim Sanghong)
15:4016:00DC321Multimodal Artificial Intelligence for Data-driven Developments of Complex Composite Materials
(AIST) *(Reg)Muroga Shun, Miki Yasuaki, (ADMAT) Honda Takashi, (AIST) Morita Hiroshi, Okazaki Toshiya, Hata Kenji
Multimodal AI
Materials Informatics
Composite Material
ST-21669
16:0016:20DC322Effect of physics-based feature engineering in predicting product yields of catalytic cracking reactions
(Shinshu U.) *(Stu)Yasuike Shun, (Reg)Osada Mitsumasa, (Reg)Shimada Iori
catalytic cracking
machine learning
feature engineering
ST-21101
16:2016:40DC323Developing identifiers to link materials databases
(UTokyo) *(Reg)Muraoka Koki, Munekata Tsubasa, Nakayama Akira
materials informatics
database
ST-21580
16:4017:00DC324Discusstion on initial sample selection for Bayesian optimization of compound combinations
(Meiji U.) *(Stu)Morishita Toshiharu, (Reg)Kaneko Hiromasa
Bayesian optimization
Machine learning
Clustering
ST-21328

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SCEJ 53rd Autumn Meeting (Nagano, 2022)


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