Tian Xie
@xie-tian.bsky.social
Principal Research Manager & Project lead @ Microsoft Research AI for Science; AI for materials; Previously @ MIT, DeepMind, Google X. Views my own.
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Tian Xie
@xie-tian.bsky.social
· Jan 16
Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments. www.microsoft.com/en-us/resear...
Excited to finally announce the publication of MatterGen on Nature. MatterGen represents a new paradigm of materials design with generative AI. We are releasing the code of MatterGen under MIT license. Look forward to seeing how the community will use the tool and build on top of it.
🚨We are hiring! 🚨 Want to join a highly talented, collaborative team and build the next frontier model for materials design? Apply to the following roles and join our materials team at @msftresearch.bsky.social AI for Science. Location can be Cambridge UK or Amsterdam NL or Berlin DE.
October 10, 2025 at 10:18 AM
🚨We are hiring! 🚨 Want to join a highly talented, collaborative team and build the next frontier model for materials design? Apply to the following roles and join our materials team at @msftresearch.bsky.social AI for Science. Location can be Cambridge UK or Amsterdam NL or Berlin DE.
I am honored to join this year’s MIT technology review’s innovators under 35 list. Amazing to see the impact of generative AI on materials design being recognized in this prestigious list. Credits to the whole MatterGen team for making this happen.
We’re thrilled to share that Tian Xie, Principal Research Manager at Microsoft Research AI for Science, has been named to MIT Technology Review’s 2025 Innovators Under 35! Tian recently led the development of MatterGen, our generative AI model for materials discovery. msft.it/6010s9dse
September 8, 2025 at 9:35 PM
I am honored to join this year’s MIT technology review’s innovators under 35 list. Amazing to see the impact of generative AI on materials design being recognized in this prestigious list. Credits to the whole MatterGen team for making this happen.
Want to join our efforts @msftresearch.bsky.social AI for Science to push the frontier of AI for materials? We are the team behind MatterGen & MatterSim and we have 2 job openings! Each can be in Amsterdam, NL, Berlin, DE, or Cambridge, UK.
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July 31, 2025 at 2:36 PM
Want to join our efforts @msftresearch.bsky.social AI for Science to push the frontier of AI for materials? We are the team behind MatterGen & MatterSim and we have 2 job openings! Each can be in Amsterdam, NL, Berlin, DE, or Cambridge, UK.
Reposted by Tian Xie
Today in the journal Science: BioEmu from Microsoft Research AI for Science. This generative deep learning method emulates protein equilibrium ensembles – key for understanding protein function at scale. www.science.org/doi/10.1126/...
July 10, 2025 at 6:10 PM
Today in the journal Science: BioEmu from Microsoft Research AI for Science. This generative deep learning method emulates protein equilibrium ensembles – key for understanding protein function at scale. www.science.org/doi/10.1126/...
Reposted by Tian Xie
Very excited and proud of this incredible team effort!
Microsoft researchers achieved a breakthrough in the accuracy of DFT, a method for predicting the properties of molecules and materials, by using deep learning. This work can lead to better batteries, green fertilizers, precision drug discovery, and more. www.microsoft.com/en-us/resear...
June 18, 2025 at 10:40 AM
Very excited and proud of this incredible team effort!
Reposted by Tian Xie
🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT ⚛️🔥🧪🧬
June 18, 2025 at 11:24 AM
🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT ⚛️🔥🧪🧬
Huge congrats to our DFT team in achieving the first big milestone towards a universal XC functional. It is a key step towards bridging the gap between computation and experiments for the computational design of molecules and materials.
Microsoft researchers achieved a breakthrough in the accuracy of DFT, a method for predicting the properties of molecules and materials, by using deep learning. This work can lead to better batteries, green fertilizers, precision drug discovery, and more. www.microsoft.com/en-us/resear...
June 18, 2025 at 10:24 AM
Huge congrats to our DFT team in achieving the first big milestone towards a universal XC functional. It is a key step towards bridging the gap between computation and experiments for the computational design of molecules and materials.
Reposted by Tian Xie
Thermal conductivity is critical in modern electronics, but in a post-Moore’s Law world, the need for novel structures that surpass the heat transfer properties of silicon is essential. Learn how AI is helping scientists discover these next-gen materials. msft.it/6013SnPAN
May 8, 2025 at 4:31 PM
Thermal conductivity is critical in modern electronics, but in a post-Moore’s Law world, the need for novel structures that surpass the heat transfer properties of silicon is essential. Learn how AI is helping scientists discover these next-gen materials. msft.it/6013SnPAN
Reposted by Tian Xie
⭐️MatterGen has reached 1K stars on GitHub⭐️
Thanks for giving it a try, we look forward to seeing what you can discover with it!
This is what we discovered so far 🙃 (audio on)
Thanks for giving it a try, we look forward to seeing what you can discover with it!
This is what we discovered so far 🙃 (audio on)
February 11, 2025 at 6:33 PM
⭐️MatterGen has reached 1K stars on GitHub⭐️
Thanks for giving it a try, we look forward to seeing what you can discover with it!
This is what we discovered so far 🙃 (audio on)
Thanks for giving it a try, we look forward to seeing what you can discover with it!
This is what we discovered so far 🙃 (audio on)
Excited to finally announce the publication of MatterGen on Nature. MatterGen represents a new paradigm of materials design with generative AI. We are releasing the code of MatterGen under MIT license. Look forward to seeing how the community will use the tool and build on top of it.
Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments. www.microsoft.com/en-us/resear...
January 16, 2025 at 10:10 AM
Excited to finally announce the publication of MatterGen on Nature. MatterGen represents a new paradigm of materials design with generative AI. We are releasing the code of MatterGen under MIT license. Look forward to seeing how the community will use the tool and build on top of it.