Japanese page

SCEJ 87th Annual Meeting (Kobe, 2022) / / IChES 2022

List of received applications (By topics code)

CS) Cross-field Session

CS-1. Frontiers of Data-driven Research and Development <Virtual/Live>

Organizer(s): Shimada Iori (Shinshu Univ.), Koyama Michihisa, (Shinshu Univ.), Ono Tsutomu (Okayama Univ.), Toya Yoshihiro (Osaka Univ.), Yamashita Yoshiyuki (Tokyo Univ. of Agri. and Tech.), Kim Sanghong (Tokyo Univ. of Agri. and Tech.)

Data science has been rapidly developing in recent years as the fourth science following experimental science, theoretical science, and computational science. The early realization of a data-driven society led by data science has been recognized as a key to international competitiveness. This symposium will have speakers who are making pioneering efforts toward a data-driven society from various viewpoints and discuss future research and development.

Most recent update: 2022-06-14 16:59:01

The keywords that frequently used
in this topics code.
machine learning2
domain knowledge1

312Inverse estimation of physical properties using physics informed neural networks in TSSG method for SiC crystal growth
(Osaka U.) *(Stu)Takehara Yuto, (Reg)Okano Yasunori
Numerical simulation
Top-Seeded Solution Growth
Physics Informed Neural Networks
484Use of machine learning and feature engineering for product composition prediction in heavy oil catalytic cracking reactions
(Shinshu U.) *(Reg)Shimada Iori, (Reg)Osada Mitsumasa, (Reg)Fukunaga Hiroshi, (Reg)Koyama Michihisa
machine learning
feature engineering
catalytic cracking
577Prediction of organic compound solubility for subcritical water by machine learning
(Shinshu U.) *(Reg)Osada Mitsumasa, Minesugi Yuuka, (Stu)Tamura Kotaro, (Reg)Shimada Iori
machine learning
subcritical water
640Computer Automated Material Design by Universal Neural Network Potential
(Shinshu U.) *(Reg)Valadez Huerta Gerardo, Tamura Ayako, Nanba Yusuke, Hisama Kaoru, (Reg)Koyama Michihisa
Universal Neural Network Potential
Computational Material Design
714[Invited lecture] Sumitomo Chemical's Materials Informatics Initiatives
(Sumitomo Chemical) *(Reg)Kaneko Shogo, (Cor)Nishino Shinya
materials Informatics
data driven R&D strategy
education and training
715[Invited lecture] How to drive R&D with limited data?
(Kyoto U.) (Reg)Kano Manabu
data-driven approach
domain knowledge
716[Invited lecture] Development of smart cells using Bio Digital Transformation
(Kobe U.) (Reg)Hasunuma Tomohisa
Metabolic engineering
Enzyme engineering
724[Invited lecture] Digitalization of Organic Synthesis
(Kyoto U.) Matsubara Seijiro


List of received applications (By topics code)

List of received applications
SCEJ 87th Annual Meeting (Kobe, 2022)
IChES 2022

(C) 2022 The Society of Chemical Engineers, Japan. . All rights reserved.
Most recent update: 2022-06-14 16:59:01
For more information contact Organizing Committee, SCEJ 87th Annual Meeting (Kobe, 2022) / / IChES 2022
E-mail: inquiry-87awww3.scej.org
This page was generated by easp 2.47; update.pl 2.37 (C)1999-2015 kawase