1/ 🧪💡 Curious about faster material & molecular discoveries? Multi-fidelity Bayesian Optimization (MFBO) is your friend! In this paper, we investigate when MFBO is truly effective compared to standard BO methods, helping to balance cost & accuracy in optimization campaigns.

General-purpose (without any constraints) molecular generative models can *directly* optimize for *constrained* synthesizability using retrosynthesis models! Find out why it *takes two to tango*: Pre-print: arxiv.org/abs/2410.11527 Code: github.com/schwallergroup… (1/2)

FSscore has now been published in Chemistry-Methods (Chemistry Europe)! 🚀 Check out the updated paper on personalized synthesizability scoring here: …mistry-europe.onlinelibrary.wiley.com/doi/10.1002/cm…

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

Hello from Singapore 🇸🇬! Thrilled to be at #ICLR2025 presenting our work on fragment-based drug discovery 🧩. We go beyond virtual screening with a generative, structure-aware approach. 📃 openreview.net/forum?id=bZW1H… 🔗 github.com/rneeser/Latent… A thread 🧵👇

🚨 PhD opportunity! I’m recruiting a PhD student with a strong background in math/stats/CS to join my group at NTU Singapore 🇸🇬 Start: Jan or Aug 2026 Topic: Foundations of Epistemic Uncertainty in ML 🧠🔍 📌 Details: chau999.github.io/group/ RT appreciated!