Research achievements, publications, and conference presentations
Publication
Paper Published in APL Machine Learning
Our research team has published a paper on AI-driven "materials maps" in the international journal APL Machine Learning.
This research demonstrates a method for rapidly extracting useful information from massive materials databases using machine learning, accelerating materials discovery.
Paper: Y. Hashimoto, X. Jia, H. Li, T. Tomai, "A materials map integrating experimental and computational data via graph-based machine learning for enhanced materials discovery", APL Machine Learning3, 036104 (2025)
Delivered an invited talk at the Quantum Physics and Nanoscience Seminar, Institute of Science Tokyo.
Title: AI and Robotics: Opening New Frontiers in Materials Science
Keynote Lecture
Keynote Lecture at IMPRES2025
Selected as keynote speaker at IMPRES2025 (The 7th International Symposium on Innovative Materials and Processes in Energy Systems).
Title: Mapping Thermoelectric Materials Using Machine Learning on Integrated Computational and Experimental Datasets
Presented research at the Japan Society of Applied Physics (JSAP) annual meeting.
Title: Application of a Material Structural Similarity Map to Materials Process Exploration
Invited Seminar
Invited Seminar at Stanford University
Delivered an invited talk at the GLAM Special Seminar, Stanford University.
Title: Local and Global Mapping of Thermoelectric Materials Based on Computational and Experimental Datasets
Talk
Talk at Laboratory Automation Monthly Study Group
Will present "Building Chemical Automated Experiments from Scratch" at the Laboratory Automation monthly study group.
The talk will cover practical approaches to experiment automation.