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Cecilia Clementi Profile
Cecilia Clementi

@CecClementi

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279

Scientist & Scuba Diver - I love theoretical physics, sharks, and pygmy seahorses - https://t.co/NWP7uoHg2a

Joined June 2016
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@CecClementi
Cecilia Clementi
5 months
Our development of machine-learned transferable coarse-grained models in now on Nat Chem! https://t.co/HGngd8Vpop I am so proud of my group for this work! Particularly first authors Nick Charron, Klara Bonneau, @sayeg84, Andrea Guljas.
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nature.com
Nature Chemistry - The development of a universal protein coarse-grained model has been a long-standing challenge. A coarse-grained model with chemical transferability has now been developed by...
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@CecClementi
Cecilia Clementi
28 days
Our latest paper on the interpretation on Neural Network Potentials is now published on Nature Communications: https://t.co/6mOkNhlfrO. Congratulations to Klara Bonneau, Jonas Lederer and all authors. In collaboration with Klaus-Robert Müller's group.
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nature.com
Nature Communications - Machine-learned force fields are becoming increasingly popular but suffer from their “black-box” nature. Here the authors adapt explainable AI techniques to...
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@CecClementi
Cecilia Clementi
5 months
Thanks to our collaborators: @FrankNoeBerlin @gdefabritiis. Thanks @PhysikFUBerlin @Einstein_Berlin DFG @BMBFSFJ for support!
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@FrankNoeBerlin
Frank Noe
5 months
BioEmu now published in @ScienceMagazine !! What is BioEmu? Check out this video: https://t.co/PAj96iKvR7
@MSFTResearch
Microsoft Research
5 months
Today in the journal Science: BioEmu from Microsoft Research AI for Science. This generative deep learning method emulates protein equilibrium ensembles – key for understanding protein function at scale. https://t.co/WwKjj5B0eb
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@QBI_UCSF
QBI
6 months
Meet Cecilia Clementi @CecClementi, Physics Prof at @FU_Berlin + speaker at the QBI/@rezo_tx “AI in Biology” symposium next week! She’ll share how machine learning can model protein dynamics, and why blending theory + experiment is more powerful than ever. Join us June 17–18
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@gklambauer
Günter Klambauer
9 months
Extending the RANGE of Graph Neural Networks: Relaying Attention Nodes for Global Encoding Virtual nodes introduced that pass information via attention; reduces oversquashing; improves GNN on molecules; MD22!! P: https://t.co/d9TMOqACx3
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@ELLISforEurope
ELLIS
10 months
Meet @CecClementi, Einstein Prof. of Physics at @PhysikFUBerlin 🇩🇪. An ELLIS Fellow, she pioneers #AI4Science & is a member of #ELLISProgram ML for Molecule Discovery. Her research spans Biophysics & Theoretical/Chemical Physics. #WomenInELLIS
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@CecClementi
Cecilia Clementi
10 months
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@CecClementi
Cecilia Clementi
10 months
In collaboration with @FrankNoeBerlin, great work by Alessandro Caruso and Jacopo Venturin in my group, with precious help from Lorenzo Giambagli and Edoardo Rolando. Thanks to @Einstein_Berlin, DFG , and BMBF for funding!
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@CecClementi
Cecilia Clementi
10 months
Our preprint is out: https://t.co/VRylYIZ9oN We present a new architecture to address the problem of "short-sightedness" of MLFF based on GNN, which outperform in speed and accuracy Ewald-based GNN.
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arxiv.org
Graph Neural Networks (GNNs) are routinely used in molecular physics, social sciences, and economics to model many-body interactions in graph-like systems. However, GNNs are inherently local and...
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@FrankNoeBerlin
Frank Noe
1 year
Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @MSFTResearch AI for Science. #ML #AI #NeuralNetworks #Biology #AI4Science https://t.co/yzOy6tAoPv
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@BiologyAIDaily
Biology+AI Daily
1 year
Scalable emulation of protein equilibrium ensembles with generative deep learning @MSFTResearch • BioEmu, a novel generative deep learning system, enables scalable emulation of protein equilibrium ensembles, achieving a 10,000-fold speed-up over molecular dynamics (MD)
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@ItalyinGermany
Italy in Germany
1 year
L’eccellenza scientifica italiana protagonista in Ambasciata in occasione del riconoscimento del network di scienziati 🇮🇹 SIGN come associazione no-profit, con un panel sulle applicazioni scientifiche dell’IA @G_Cuniberti @CecClementi @FrankNoeBerlin @DPasserone @SIGNnw @ItalyMFA
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@venkatkapil24
Venkat Kapil
1 year
Progress towards rigorous #quantum statmech from classical dynamics by #MachineLearning quantum corrections to potentials. In this collaboration with @CecClementi, we obtain exact statics (beyond a centroid description) for paradigmatic aqueous system https://t.co/MrYnNqBr7a
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@BioExcelCoE
BioExcel CoE
1 year
As the sun sets on our conference we take a look at the talks from the last day.. @CecClementi presented her group's work on developing a state-of-the-art machine learned coarse-grained #forcefield which will fold #PDB structures with 25% sequence similarity
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@RommieAmaro
Rommie Amaro
1 year
Career first! Girls night out with theoretical chem/biophysics profs in Brno!! 😍😍😍 @graeter_mbm @ppxasjsm @CecClementi @ElisaTelisa Thank you @BioExcelCoE @amjjbonvin for a wonderful conference! 🤓💕
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@FrankNoeBerlin
Frank Noe
1 year
Join us on our exciting mission to disrupt the molecular sciences with #MachineLearning #AI at @MSFTResearch AI for Science. Researcher and Engineering positions open, each can be in Berlin DE or Cambridge UK: https://t.co/mphLkeiOkz https://t.co/m9Zp0SQ7Eq
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@CecClementi
Cecilia Clementi
1 year
Another Clemeni/Noe collaboration: @FrankNoeBerlin flooded his camera so we worked together to try backlighting with remote strobes. A poor seahorse was the unwilling subject of our experimenting with lights. We need to improve on the strobe positioning, trying again soon.
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@CecClementi
Cecilia Clementi
1 year
Candy crab, red-lined coral shrimp, popcorn shrimp, and starfish shrimp. At the Liberty wreck dive site in Tulamben, with @FrankNoeBerlin.
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@CecClementi
Cecilia Clementi
1 year
Pinkeye goby. In Jemeluk Bay, Bali. With @FrankNoeBerlin.
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