Robert Pinsler
@rpinsler.bsky.social
AI for materials design at Microsoft Research AI for Science | Prev. University of Cambridge. Views are my own.
Reposted by Robert Pinsler
Skala is now available to everyone!
Why are we releasing it? Because we’re not just aiming to publish a cool paper — we’re on a mission to bring DFT to chemical accuracy using deep learning. And to make real progress, we need the community’s feedback.
#compchem
Why are we releasing it? Because we’re not just aiming to publish a cool paper — we’re on a mission to bring DFT to chemical accuracy using deep learning. And to make real progress, we need the community’s feedback.
#compchem
The wait is over! Microsoft Research is sharing Skala, the new exchange-correlation functional, marking a major milestone in the accuracy/cost trade-off in DFT. Help us learn from your testing so we can improve. Available on Azure AI Foundry and GitHub. msft.it/6016sFDLY
October 9, 2025 at 4:46 PM
Skala is now available to everyone!
Why are we releasing it? Because we’re not just aiming to publish a cool paper — we’re on a mission to bring DFT to chemical accuracy using deep learning. And to make real progress, we need the community’s feedback.
#compchem
Why are we releasing it? Because we’re not just aiming to publish a cool paper — we’re on a mission to bring DFT to chemical accuracy using deep learning. And to make real progress, we need the community’s feedback.
#compchem
Job alert! Check out our open roles (Senior Researcher, Senior Applied Scientist, Senior Data Engineer) for AI for materials discovery.
🚨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 10:58 AM
Job alert! Check out our open roles (Senior Researcher, Senior Applied Scientist, Senior Data Engineer) for AI for materials discovery.
Reposted by Robert Pinsler
Incredibly excited to see that Aardvark-Weather is finally out in Nature!! An amazing project with a truly fantastic team. The lead authors Anna Allen and Stratis Markou have worked really really hard to make this project happen.
www.nature.com/articles/s41...
www.nature.com/articles/s41...
End-to-end data-driven weather prediction - Nature
Nature - End-to-end data-driven weather prediction
www.nature.com
March 20, 2025 at 5:22 PM
Incredibly excited to see that Aardvark-Weather is finally out in Nature!! An amazing project with a truly fantastic team. The lead authors Anna Allen and Stratis Markou have worked really really hard to make this project happen.
www.nature.com/articles/s41...
www.nature.com/articles/s41...
Reposted by Robert Pinsler
Today we have published BioEmu-Benchmarks (MIT license): a code to evaluate the multi-conformation sampling benchmarks, MD free energy landscape benchmarks, and folding free energy benchmarks shown in the BioEmu-1 paper with BioEmu or your own model. Some details below 🧵
github.com/microsoft/bi...
github.com/microsoft/bi...
GitHub - microsoft/bioemu-benchmarks: Benchmarking code accompanying the release of `bioemu`
Benchmarking code accompanying the release of `bioemu` - microsoft/bioemu-benchmarks
github.com
February 21, 2025 at 3:49 PM
Today we have published BioEmu-Benchmarks (MIT license): a code to evaluate the multi-conformation sampling benchmarks, MD free energy landscape benchmarks, and folding free energy benchmarks shown in the BioEmu-1 paper with BioEmu or your own model. Some details below 🧵
github.com/microsoft/bi...
github.com/microsoft/bi...
Reposted by Robert Pinsler
Nature published Microsoft research detailing our WHAM, an AI model that generates video game visuals & controller actions. We're releasing the model weights, sample data & WHAM Demonstrator on Azure AI Foundry to enable researchers to build on this work. www.microsoft.com/en-us/resear...
February 19, 2025 at 4:08 PM
Nature published Microsoft research detailing our WHAM, an AI model that generates video game visuals & controller actions. We're releasing the model weights, sample data & WHAM Demonstrator on Azure AI Foundry to enable researchers to build on this work. www.microsoft.com/en-us/resear...
Reposted by Robert Pinsler
Check out this great BioEmu talk by @jjimenezluna.bsky.social and @yuxie.bsky.social in the VantAI lecture series. Thank you for hosting @mmbronstein.bsky.social @lucanaef.bsky.social
www.youtube.com/watch?v=8vsT...
www.youtube.com/watch?v=8vsT...
Emulation of protein equilibrium ensembles with generative deep learning | José Jiménez Luna, Yu Xie
YouTube video by VantAI
www.youtube.com
February 17, 2025 at 9:23 AM
Check out this great BioEmu talk by @jjimenezluna.bsky.social and @yuxie.bsky.social in the VantAI lecture series. Thank you for hosting @mmbronstein.bsky.social @lucanaef.bsky.social
www.youtube.com/watch?v=8vsT...
www.youtube.com/watch?v=8vsT...
Reposted by Robert Pinsler
⭐️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)
Reposted by Robert Pinsler
Excited to share the news that MatterGen is published on Nature today.
Since the publication of our preprint, we have bee busy improving our evaluation; we have also shown successful exp synthesis!
Grateful for the team members for their hard work and perseverance, and #MSR colleagues for support!
Since the publication of our preprint, we have bee busy improving our evaluation; we have also shown successful exp synthesis!
Grateful for the team members for their hard work and perseverance, and #MSR colleagues for support!
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 9:58 PM
Excited to share the news that MatterGen is published on Nature today.
Since the publication of our preprint, we have bee busy improving our evaluation; we have also shown successful exp synthesis!
Grateful for the team members for their hard work and perseverance, and #MSR colleagues for support!
Since the publication of our preprint, we have bee busy improving our evaluation; we have also shown successful exp synthesis!
Grateful for the team members for their hard work and perseverance, and #MSR colleagues for support!
Reposted by Robert Pinsler
Super excited to share that MatterGen is published in Nature!
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 1:55 PM
Super excited to share that MatterGen is published in Nature!
Reposted by Robert Pinsler
MatterGen now published in Nature 🔥 Very strong work from the materials team at MSR AI for Science!
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 1:08 PM
MatterGen now published in Nature 🔥 Very strong work from the materials team at MSR AI for Science!
Reposted by Robert Pinsler
Super excited to share that the MatterGen code is now public on GitHub! github.com/microsoft/ma...
January 16, 2025 at 10:26 AM
Super excited to share that the MatterGen code is now public on GitHub! github.com/microsoft/ma...
Reposted by Robert Pinsler
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.
Reposted by Robert Pinsler
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 12:18 PM
Reposted by Robert Pinsler
A new diffusion-driven model called MatterGen generates stable inorganic crystals by refining random atom placements. Zeni et al. show it can be steered toward specific properties, opening efficient pathways for materials design. www.nature.com/articles/s41...
January 16, 2025 at 1:21 PM
A new diffusion-driven model called MatterGen generates stable inorganic crystals by refining random atom placements. Zeni et al. show it can be steered toward specific properties, opening efficient pathways for materials design. www.nature.com/articles/s41...
Reposted by Robert Pinsler
📢 Paper + code release 📃💻
After 2 years of work, I'm excited to announce our newest paper, MatterGen, has been published in Nature!
www.nature.com/articles/s41...
We are also releasing all the training data, model weights, model code, and evaluation code on GitHub!
github.com/microsoft/ma...
After 2 years of work, I'm excited to announce our newest paper, MatterGen, has been published in Nature!
www.nature.com/articles/s41...
We are also releasing all the training data, model weights, model code, and evaluation code on GitHub!
github.com/microsoft/ma...
January 16, 2025 at 10:15 AM
📢 Paper + code release 📃💻
After 2 years of work, I'm excited to announce our newest paper, MatterGen, has been published in Nature!
www.nature.com/articles/s41...
We are also releasing all the training data, model weights, model code, and evaluation code on GitHub!
github.com/microsoft/ma...
After 2 years of work, I'm excited to announce our newest paper, MatterGen, has been published in Nature!
www.nature.com/articles/s41...
We are also releasing all the training data, model weights, model code, and evaluation code on GitHub!
github.com/microsoft/ma...
MatterGen is out in Nature! MatterGen is a SOTA generative model for materials design. We also raise the bar for evaluation by considering compositional disorder and experimentally validating model capabilities. Code is open-source!
www.nature.com/articles/s41...
github.com/microsoft/ma...
www.nature.com/articles/s41...
github.com/microsoft/ma...
January 16, 2025 at 1:33 PM
MatterGen is out in Nature! MatterGen is a SOTA generative model for materials design. We also raise the bar for evaluation by considering compositional disorder and experimentally validating model capabilities. Code is open-source!
www.nature.com/articles/s41...
github.com/microsoft/ma...
www.nature.com/articles/s41...
github.com/microsoft/ma...
Reposted by Robert Pinsler
Excited to talk about MatterGen and MatterSim (now on GitHub!) today at the @cecamevents.bsky.social l workshop at CECAM-HQ in EPFL Lausanne.
If you're interested, drop by at 11.15, or let's chat afterwards.
💻
github.com/microsoft/ma...
📄
arxiv.org/abs/2312.03687
📄📄
arxiv.org/abs/2405.04967
If you're interested, drop by at 11.15, or let's chat afterwards.
💻
github.com/microsoft/ma...
📄
arxiv.org/abs/2312.03687
📄📄
arxiv.org/abs/2405.04967
GitHub - microsoft/mattersim: MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
MatterSim: A deep learning atomistic model across elements, temperatures and pressures. - microsoft/mattersim
github.com
December 11, 2024 at 6:39 AM
Excited to talk about MatterGen and MatterSim (now on GitHub!) today at the @cecamevents.bsky.social l workshop at CECAM-HQ in EPFL Lausanne.
If you're interested, drop by at 11.15, or let's chat afterwards.
💻
github.com/microsoft/ma...
📄
arxiv.org/abs/2312.03687
📄📄
arxiv.org/abs/2405.04967
If you're interested, drop by at 11.15, or let's chat afterwards.
💻
github.com/microsoft/ma...
📄
arxiv.org/abs/2312.03687
📄📄
arxiv.org/abs/2405.04967
Reposted by Robert Pinsler
Another great model from @msftresearch.bsky.social AI for Science - CHIMERA, an accurate retrosynthesis prediction model by @marwinsegler @MaziarzKris and team!
new preprint on chemical synthesis ML models
- showing how to combine multiple models in a principled way
- modern Transformers + GNN to featurize chemical reaction:
- new insights in where the models shine
+ bonus: find the quirky named reaction!
Feedback welcome!
arxiv.org/abs/2412.05269
- showing how to combine multiple models in a principled way
- modern Transformers + GNN to featurize chemical reaction:
- new insights in where the models shine
+ bonus: find the quirky named reaction!
Feedback welcome!
arxiv.org/abs/2412.05269
Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
Planning and conducting chemical syntheses remains a major bottleneck in the discovery of functional small molecules, and prevents fully leveraging generative AI for molecular inverse design. While ea...
arxiv.org
December 9, 2024 at 3:11 PM
Another great model from @msftresearch.bsky.social AI for Science - CHIMERA, an accurate retrosynthesis prediction model by @marwinsegler @MaziarzKris and team!
Reposted by Robert Pinsler
new preprint on chemical synthesis ML models
- showing how to combine multiple models in a principled way
- modern Transformers + GNN to featurize chemical reaction:
- new insights in where the models shine
+ bonus: find the quirky named reaction!
Feedback welcome!
arxiv.org/abs/2412.05269
- showing how to combine multiple models in a principled way
- modern Transformers + GNN to featurize chemical reaction:
- new insights in where the models shine
+ bonus: find the quirky named reaction!
Feedback welcome!
arxiv.org/abs/2412.05269
Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
Planning and conducting chemical syntheses remains a major bottleneck in the discovery of functional small molecules, and prevents fully leveraging generative AI for molecular inverse design. While ea...
arxiv.org
December 9, 2024 at 2:19 AM
new preprint on chemical synthesis ML models
- showing how to combine multiple models in a principled way
- modern Transformers + GNN to featurize chemical reaction:
- new insights in where the models shine
+ bonus: find the quirky named reaction!
Feedback welcome!
arxiv.org/abs/2412.05269
- showing how to combine multiple models in a principled way
- modern Transformers + GNN to featurize chemical reaction:
- new insights in where the models shine
+ bonus: find the quirky named reaction!
Feedback welcome!
arxiv.org/abs/2412.05269
Reposted by Robert Pinsler
Exciting stuff! will be interesting to test this on our own favourite protein ensembles!
Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @msftresearch.bsky.social ch AI for Science.
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
December 6, 2024 at 12:14 PM
Exciting stuff! will be interesting to test this on our own favourite protein ensembles!
Reposted by Robert Pinsler
Excited to present what we've been up to the last couple years. Introducing BioEmu, a Biomolecular Emulator of protein dynamics: www.biorxiv.org/content/10.1...
Scalable emulation of protein equilibrium ensembles with generative deep learning
Following the sequence and structure revolutions, predicting the dynamical mechanisms of proteins that implement biological function remains an outstanding scientific challenge. Several experimental t...
www.biorxiv.org
December 6, 2024 at 8:22 AM
Excited to present what we've been up to the last couple years. Introducing BioEmu, a Biomolecular Emulator of protein dynamics: www.biorxiv.org/content/10.1...
Reposted by Robert Pinsler
hi everyone!! let's try this optimal transport again 🙃
December 5, 2024 at 12:58 PM
hi everyone!! let's try this optimal transport again 🙃
Reposted by Robert Pinsler
Great progress from @franknoe.bsky.social and collaborators on the protein conformational sampling problem using AI!
Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @msftresearch.bsky.social ch AI for Science.
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
December 6, 2024 at 1:13 PM
Great progress from @franknoe.bsky.social and collaborators on the protein conformational sampling problem using AI!
Reposted by Robert Pinsler
Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @msftresearch.bsky.social ch AI for Science.
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
December 6, 2024 at 8:39 AM
Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @msftresearch.bsky.social ch AI for Science.
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
Reposted by Robert Pinsler
If you are at #F24MRS in Boston today, check out Tian's talk at symposium MT04 at 1:30pm.
He will present our efforts to build AI tools for materials design at @msftresearch.bsky.social AI for Science.
#materialsscience #machinelearning #mattergen #mattersim
He will present our efforts to build AI tools for materials design at @msftresearch.bsky.social AI for Science.
#materialsscience #machinelearning #mattergen #mattersim
December 4, 2024 at 2:06 PM
If you are at #F24MRS in Boston today, check out Tian's talk at symposium MT04 at 1:30pm.
He will present our efforts to build AI tools for materials design at @msftresearch.bsky.social AI for Science.
#materialsscience #machinelearning #mattergen #mattersim
He will present our efforts to build AI tools for materials design at @msftresearch.bsky.social AI for Science.
#materialsscience #machinelearning #mattergen #mattersim