The keywords that frequently used in this topics code.
| Shimada Iori (Shinshu Univ.), Kim Sanghong (Tokyo Univ. of Agri. and Tech.), Toya Yoshihiro (Osaka Univ.), Kaneko Shogo (Sumitomo Chemical), Mukaida Shiho (Mitsui Chemicals) |
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: 2023-05-13 20:50:01
| The keywords that frequently used in this topics code. | Keywords | Number | |
|---|---|---|---|
| machine learning | 6 | | |
| Materials Informatics | 3 | | |
| Reinforcement Learning | 2 | | |
| database | 2 | | |
| Multimodal AI | 1 | | |
| ACKN No. | Title/Author(s) | Keywords | Style |
|---|---|---|---|
| 60 | Reinforcement learning to optimally control the bio and chemical processes | Reinforcement Learning Process control Optimal control | O |
| 101 | Effect of physics-based feature engineering in predicting product yields of catalytic cracking reactions | catalytic cracking machine learning feature engineering | O |
| 102 | [Invited lecture] Data-driven AI Laboratory and Cyber Catalysis | Data-driven Cyber Catalysis Computational Chemistry | O |
| 103 | [Invited lecture] Exploration of functional inorganic thin-film materials using autonomous systems | autonomous synthesis inorganic materials functional thin films | O |
| 129 | [Invited lecture] Data-driven polymer material development powered by Polymer SmartLab and Material DX | smart lab material DX database | O |
| 187 | Design of both membrane-based process and membrane materials with machine learning | Membrane module Materials Informatics Process design | O |
| 316 | [Invited lecture] AI-Driven peptide/antibody molecule design for drug discovery | Artificial Intelligence Drug Discovery Antibody | O |
| 328 | Discusstion on initial sample selection for Bayesian optimization of compound combinations | Bayesian optimization Machine learning Clustering | O |
| 366 | Soft sensor study in film manufacturing process | Soft sensor Fault detection Film manufacturing process | O |
| 396 | Development of digital twin of the bulk single crystal growth of Si by using PINNs (Physics Informed Neural Networks) | Digital twin Machine learning Physics Informed Neural Networks | O |
| 428 | Growth interface shape optimization and adaptive process control for InGaSb crystal growth under microgravity using machine learning | Machine Learning Reinforcement Learning Crystal Growth | O |
| 532 | Prediction of phase equilibrium of water-organic compounds system at high-temperature and high-pressure using machine learning | machine learning prediction of phase equilibrium high-temperature and high-pressure | O |
| 580 | Developing identifiers to link materials databases | materials informatics database | O |
| 590 | Multi-step approach for data-driven equipment condition assessment in biopharmaceutical drug product manufacturing | Predictive maintenance Unsupervised learning Industrial application | O |
| 641 | Data-driven analysis of charge variants in monoclonal antibody production | Charge variant Monoclonal antibody PLS | O |
| 669 | Multimodal Artificial Intelligence for Data-driven Developments of Complex Composite Materials | Multimodal AI Materials Informatics Composite Material | O |
| 712 | Inverse design of polymer membrane structure for gas separation using Junction Tree VAE machine learning | machine learning polymer membrane gas separation | O |
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