David Balcells
@BalcellsD
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Research Professor & PI at the Hylleraas Centre for Quantum Molecular Sciences | Doing ML for Chemistry and Materials Science | WATOC OSLO 2025 organizer
Oslo, Norway
Joined January 2015
In case you missed it, check out the video of my talk on OMol25, where I discuss how we built the dataset + how MLIPs trained on OMol25 are revolutionizing computational chemistry! https://t.co/4QuejTLbuc
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🧪🔬 Synthesis experts! Our team at Google DeepMind is hiring a scientist to establish and lead an AI-driven laboratory for materials discovery. The team is working to combine our AI capabilities with automated experimentation to discover novel functional materials. 1/
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Evolving Light Harvesting Metal Complexes with AI-Made Ligands! Now preprinted in the ChemRxiv 👉 https://t.co/tn4wpkwDPE
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🚀Exciting news! We are releasing new UMA-1.1 models (Small and Medium) today and the UMA paper is now on arxiv! UMA represents a step-change in what’s possible with a single machine learning interatomic potential (short overview in the post below). The goal was to make a model
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Nearly full room with Fernanda Duarte – ML session in WATOC Oslo 2025 🚀
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Boris Kozinsk on stage now in WATOC 2025 Oslo – MLIPs for catalysis!
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Back to Telluride, enjoying amazing science at high altitude!
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The time evolution of chemical space: https://t.co/eMGhuLbnam Now out in @JCIM_JCTC!
pubs.acs.org
It is well-known that the number of compounds (both synthesized and theoretical ones) is rapidly increasing. Hence, it would be obvious to affirm that the chemical space is expanding. However, is the...
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Inspired by @emollick's co-intelligence (CoI) concept, I explored CoI in the design of chemistry research with an example in computational catalysis. Trying to find some middle-ground between AI hype & denial, if such a place exists...👇 https://t.co/km9iYw0rB8 Feedback welcome!
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Very interesting work on ML representations for molecules
I’m thrilled to share our latest publication in Nature Machine Intelligence: “Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs” Led by @daniil_boiko, our work introduces stereoelectronics-infused molecular graphs (SIMGs),
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Last week to apply to this position in my group.
We are recruiting a PhD student in machine learning for photocatalysis! In this project, we will collaborate with the group of Frank Glorius @GloriusGroup to develop predictive tools for energy-transfer-catalyzed photocycloadditions. Reposts appreciated! https://t.co/JyOhlRk4yf
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New preprint from our group: Screening Diels-Alder reaction space to identify candidate reactions for self-healing polymer applications (1/5) https://t.co/Yq2EefBO1w
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Check out Lucía's @Lmoranglez Perspective now out in @ACSCatalysis on AI on homogeneous catalysis, with Arron, Ainara, and I. Awesome work already done, with many future exciting challenges!
🚀 From mechanistic insights to inverse catalyst design, our new Perspective maps the breakthroughs — and the hurdles ahead — in AI for homogeneous catalysis with transition metal complexes. Take a peek! 👀 @BalcellsD @hylleraas
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🚀 From mechanistic insights to inverse catalyst design, our new Perspective maps the breakthroughs — and the hurdles ahead — in AI for homogeneous catalysis with transition metal complexes. Take a peek! 👀 @BalcellsD @hylleraas
pubs.acs.org
Artificial intelligence (AI) is transforming research in chemistry, including homogeneous catalysis with transition metals. Over the past 15 years, the number of publications combining AI with...
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Want to see an estimate of the average UV-Vis spectrum of the known metal-organic chemical space? Here you have it for 74,281 transition metal complexes, including wavelengths & intensities, charge transfers, and solvatochromic effects. All ready for your ML projects. Have fun!
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For any who are interested in working on machine-learning driven simulations of battery electrolyes using path-integral techniques, I am opening a new postdoctoral position in my group. The Interfolio application site is here:
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Really happy to announce this today! We're launching a free platform and API to use our scientific agents for discovery 🔥
Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With
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Long & windy road of academic publishing! Few journal rejections and two years (!!!) after preprint, AIMNet2 paper was just published @ChemicalScience ! With 69 citations to it as of now, it's immediately part of 2025 HOT🌶️ Article collection. #compchem
https://t.co/zxo0UJqpeq
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