Philippe Schwaller

@pschwllr.bsky.social

Assistant Professor at EPFL, ML/AI-accelerated Chemistry & Synthesis | Educating the next generation of chemists and leading a fantastic team (https://schwallergroup.github.io) | Previously IBM Research / Uni Bern / Uni Cambridge / EPFL | he/his

Yay for @pschwllr.bsky.social and @mlederbauer.bsky.social (and all your co-authors who aren't on BlueSky yet) 🥳 This #dataset is a prime example of #GoodData, and it ties nicely with what @clarakirkvold.bsky.social and @grynova.bsky.social were talking about a few weeks ago in their #JournalClub

IOPP Machine Learning and AI@iopp-mlresearch.bsky.social · last yr.

🚨 Dataset article alert! 🚨 Wellawatte, @mlederbauer.bsky.social, @pschwllr.bsky.social and coauthors introduce a new open-source #dataset with >1,000 entries specifically designed for #LLMs applications in #chemistry. #MachineLearningScienceandTechnology #ChemSky 🧪 Article here: bit.ly/4kHdY6x

We demonstrate granular and steerable synthesizability control in molecular generation, allowing to specify reaction and building block constraints while optimizing for molecules with desired properties. Super proud of Jeff Guo and Víctor Sabanza Gil leading this exciting study! #chemsky

Jeff Guo@jeff-guo.bsky.social · last yr.

Generate property-optimized small molecules with 𝘴𝘵𝘦𝘦𝘳𝘢𝘣𝘭𝘦 𝘢𝘯𝘥 𝘨𝘳𝘢𝘯𝘶𝘭𝘢𝘳 synthesizability control - allowing complete user-flexibility to impose various reaction constraints! Pre-print: arxiv.org/abs/2505.08774 Code: github.com/schwallergro... (1/4)

Thrilled to announce our new paper on predicting global minimum adsorption energy (GMAE) for computational catalyst discovery! We developed a multi-modal transformer approach, including adsorption site identification via cross-attention. Huge congrats to Junwu and Xu! www.nature.com/articles/s41...

A multi-modal transformer for predicting global minimum adsorption energy - Nature Communications

The fast evaluation of global minimum adsorption energy (GMAE) is crucial for catalyst screening. Here, authors designed a multi-modal transformer called AdsMT to rapidly predict the GMAE without site...

nature.com

New preprint from the Schwaller group! We investigate the chemical reasoning of LLMs on synthesis routes (up to 26 steps) and reaction mechanisms. Claude 3.7 performs impressively well. - LLMs for direct outcome prediction ❌ - Search algorithms + LLMs 🤩 Congrats to the team! 🙌 #chemsky ⬇️

Andres M Bran@andresbran.bsky.social · last yr.

LLMs are pretty bad at writing molecules, but quite good at analyzing mols and reactions! In our new work we use LLMs+search in chemical tasks, unlocking steerable synth. planning and mechanism prediction 🌟 Chehck out the paper 👉 arxiv.org/abs/2503.08537 1/8