Excited to share our preprint on a scalable ML optimisation framework applied to automated HTE reaction optimisation in highly parallel batches! preprint: chemrxiv.org/engage/chemrxi… Thanks to my PI Philippe Schwaller (he/him) (LIAC at EPFL) and Roche for this exciting collaboration! (1/3)

We are hiring (resharing appreciated)! Given a few recent successful grant applications (I got my SNSF Starting Grant 🚀), we are extending the LIAC (LIAC at EPFL) team and have multiple openings (PhD/postdoc) for 2025. Are you interested in #AI4Science and machine learning

1/ Starting material constrained synthesis planning is now possible using a general retrosynthesis algorithm *without* training a dedicated value network! Check-out our new paper, TangoStar. Preprint : arxiv.org/abs/2412.03424

🚨New preprint! ✨My precious✨ GOLLuM: GP-Optimized LLMs for Bayesian Optimization — the first of its kind! LLMs as deep kernels in GPs jointly optimized via marginal likelihood → implicit metric learning, calibrated uncertainty & superior sampling 🚀 📄 arxiv.org/abs/2504.06265

🔥 AutoAdsorbate 🔥 has been the workhorse of high throughput computation in heterogeneous catalysis modeling and ML BASF for the previous few years. 🧵 Now it is available open source! #MatSci #CompChem Preprint: doi.org/10.26434/chemr… Code: github.com/basf/autoadsor…

How it feels to bash your own previous work in a new paper💀 Anywaaays, hello from #ICLR2025 in Singapore! 🇸🇬 I’m presenting GOLLuM: GP-optimised LLMs at the World Models Workshop on Monday. Let's discuss LLMs, finetuning, GPs, BO, life, pain, PhD👀 🔗 arxiv.org/abs/2504.06265

Happy to present a poster of my work on starting material constrained synthesis planning, Tango*, in the AI4Materials workshop at #ICLR2025 in 🇸🇬 Thanks to collaborators Jeff Guo and Zlatko Jončev and my PI Philippe Schwaller (he/him)!

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/schwallergroup… (1/4)