PhD in Computational Biophysics. Biotechnologist by degree. CompChem, Machine Learning, Bioinformatics...everything with a pinch of Data Analysis.⌨️🖱️🖥️📊
Hey! 👋
I'm at the #CCPBioSim2025 conference in Southampton!
If you are here and interested in machine learning interatomic potentials (MLIPs) and transfer learning approaches to leverage foundational models (as GNNs) for producing molecular dynamics drop by poster num. 54! 😁
Hello Everyone!👋 It's been a while!
I've been working on our new approach "Franken" to leverage pre-trained GNN models through random Fourier features and make use of the learned representation to train data-efficient MLIPs.
Here's the preprint: https://t.co/WnO0JZXcXw
🚨Postdoc Opportunity in Scientific Machine Learning 🚨
Join us in designing cutting-edge learning algorithms for simulating physical systems! Focus on ML for dynamical systems. @ELLISforEurope@IITalk
Details: https://t.co/7RryN0IXBz 🌟 #postdocposition#postdoc
Finally put my poster up on the #FENS2024 !!!! It was an intense afternoon talking with a ton of colleagues and friends. In the end #EM seems to be interesting.
Thanks for coming by 🫰. Next time will be in form of a publicación for sure 😌 @FENSorg
Excited to share my 1st independent preprint on data-efficient #ML potentials for catalytic & chemical reactions with @perego98💥
➡️Uniformly accurate reactive MLPs with ~1k DFT calculations
How❓Enhanced sampling + on-the-fly selection+ GNNs
https://t.co/fOopkgVWBb
Short📜⤵️
I am happy to share our new preprint with @vkostic30@GroupParrinello and @MPontil .
We introduce a method based on the infinitesimal generator to learn dynamics from biased data.
https://t.co/wFIacvqdvJ
Dr. David L. Goodstein’s «States of Matter», a book published in January 1985, has a very remarkable opening passage.
[read more: https://t.co/blRzxDg4FN]
[book: https://t.co/aO2OkpLmXk]
RTs please ! 📢 I have a fully funded #phdposition (UK students) at @ucl@tyc_london ➡️
https://t.co/n4S59dB53J
on phase behaviours of nanoscale materials. Interested in #Quantum, statistical mechanics, #ML and excited to team up with my collaborators @ChemCambridge ?
PDRA vacancy in my group @EdinburghChem ''Developing Molecular Dynamics Simulations protocols with Machine Learning Potentials'' More information available at https://t.co/Tbpc8PGhXd