Scholar
Tian Xie
Google Scholar ID: xFbOAf8AAAAJ
Microsoft Research
Citations & Impact
Citations
5,567
H-index
22
i10-index
26
Publications
20
Co-authors
0
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- - January 16, 2025, published MatterGen on Nature, representing a new paradigm of materials design with generative AI, and released code on GitHub
- - July 30, 2024, won the Frontier of Science Award of the International Congress of Basic Science, together with his PhD advisor Jeffrey Grossman, for their work CGCNN to AI for Physical Sciences
- - May 13, 2024, announced MatterSim, an emulator for accurate and efficient materials simulation and property prediction over a broad range of elements, temperatures, and pressures
- - December 6, 2023, announced MatterGen, a generative model that enables broad property-guided materials design for inorganic materials
- - October 16, 2023, released MOFDiff, a coarse-grained diffusion model to design MOFs for carbon capture
Research Experience
- - Researcher & Project Lead at Microsoft Research AI for Science, leading the development of MatterGen and MatterSim projects
- - Conducted research as a postdoc at MIT
- - Interned at DeepMind and Google X
Education
- - Ph.D. in Materials Science and Engineering from MIT, graduated in 2020, advised by Jeffrey C. Grossman
- - Postdoc at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), 2020-2022, co-advised by Tommi Jaakkola and Regina Barzilay
Background
- - Research Interests: Application of AI in science, particularly in materials design
- - Professional Field: Materials Science and Engineering, Artificial Intelligence
- - Brief Introduction: A researcher and project lead at Microsoft Research AI for Science, leading a highly interdisciplinary team to develop foundational AI capabilities to accelerate the design of novel materials, aiming to impact broad areas including energy storage, carbon capture, and catalysis.
Co-authors