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I am thrilled to share that my paper on self-supervised learning for time series forecasting has been accepted by #ICASSP2024! 🙌 Big thanks to my collaborators and mentors in Krauthammer Lab!

🚀 Countdown: 2 Weeks to 'AI in Genomics' at AMLD EPFL 2024! 🧬 📅 March 25, 11 AM: Dive into cutting-edge ML research in genomics. 🌟 Speakers: Charlotte Bunne, Nicolas Mathis,Kim Fabiano Marquart, Bruno Correia , Manuel Schürch. Get tickets here: go.epfl.ch/AMLD #AMLDEPFL2024

Join us for the 'AI in Genomics' track/workshop at #AMLDEPFL2024 and connect with experts! Get tickets here ➡️ go.epfl.ch/AMLD

Our work "DDoS: A Graph Neural Network-Based Drug Synergy Prediction Algorithm" has been accepted at the Conference on Health, Inference, and Learning #CHIL2024! Congrats to Kyriakos Schwarz Alicia Pliego Amina Mollaysa and all co-authors 🎉 🗞️ arxiv.org/abs/2210.00802

Checkout our paper "Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Enhanced Goal-Directed Generation" at the AccMLBio workshop at #ICML2024! Paper Link:openreview.net/pdf?id=b1hoOXg…… #MachineLearning #MolecularDesign #AI #ICML2024

Our TnpB story has been published in Nature Methods 🚀 Check out the thread by Gerald Schwank to dive right in.

Bridging genome editing, protein engineering, and applied machine learning in biology: Great to see our latest study, spearheaded by Kim Fabiano Marquart, out in Nature Methods. Check out the paper! 🧬📷 nature.com/articles/s4159… Nicolas Mathis Gerald Schwank Krauthammer Lab