Hybrid Perovskites
Oct 20–21, 2026
Online
Bridging Human Expertise, Intelligent Agents and Algorithms for Autonomous Science
Materials Science and Materials Physics workshop by Masato Kotsugi, Sarah Allec and Yongtao Liu
Starts in 23 days
Online
About
This MRS workshop, developed with the Japan Society of Applied Physics, examines how AI can advance autonomous materials research beyond property prediction. Sessions connect physics-informed models, fundamental physical understanding, experimental validation and human–AI collaboration. Particular attention goes to data-efficient learning where experimental datasets are small or difficult to obtain. The online programme runs 4 November, 10:00–13:00, and 5 November, 19:00–22:00, US Eastern Time (EST). Registered participants receive session recordings. Registration is USD 100 regular, USD 75 for MRS members and USD 25 for students; qualifying developing-country professionals pay USD 25 and qualifying students attend free, subject to documentation and the published conditions. An MRS account is required.
Topics
- AI
- autonomous materials research
- property prediction
- physics-informed models
- fundamental physical understanding
- experimental validation
- human–AI collaboration
- data-efficient learning
- experimental datasets
- Japan Society of Applied Physics
Organisers
- Masato Kotsugi, Tokyo University of Science
- Sarah Allec, Pacific Northwest National Laboratory
- Yongtao Liu, Oak Ridge National Laboratory
Guest speakers
- Soumendu Bagchi, Oak Ridge National Laboratory
- Ganesh Narasimha, Oak Ridge National Laboratory
- Keita Hiromori, The University of Tokyo
- Kevin Yager, Brookhaven National Laboratory
- Maria Chan, Argonne National Laboratory
- Philippe Schwaller, École Polytechnique Fédérale de Lausanne
- Shi Xuan Leong, Nanyang Technological University
- Shinya Mine, National Institute of Advanced Industrial Science and Technology
- Shoichi Matsuda, National Institute for Materials Science
- Wanlu Li, University of California, San Diego
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