Materials Data Algorithms Group
The Materials Data Algorithms Group is redefining the frontiers of materials science by integrating high-level data intelligence with physical experimental research. We develop specialized AI architectures and advanced data analytics methods specifically engineered for the complexities of materials data.
Our expertise goes beyond traditional informatics; we are pioneering the use of quantum computing technologies to solve intractable problems. These cutting-edge engines power our self-driving laboratories, creating a fully autonomous loop of synthesis, characterization, and learning.
We reject the "one-size-fits-all" approach. Recognizing the vast diversity of materials research, we collaborate closely with experimental teams at NIMS and throughout the global research community to create bespoke algorithmic frameworks tailored to each unique study. By synchronizing AI and quantum-enhanced intelligence with the design of lab automation, we provide the custom-built engines that drive the next generation of materials breakthroughs.
The main research topics are as follows.
- ・Development of AI for materials research.
- ・Development of software to control self-driving laboratories.
- ・Development and design of self-driving laboratory systems.
- ・Development of data-driven algorithms for understanding materials data.
- ・Development of MI methods using quantum computation.