The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture
Identifying useful sorbent materials for direct air capture (DAC) from humid air remains a challenge. We present the Open DAC 2025 (ODAC25) dataset, a significant expansion and improvement upon ODAC23...
It was great to work on the ODAC25 paper with the Meta FAIR Chemistry and Georgia Tech. A leap forwards in modelling direct air carbon capture with metal organic frameworks, with much better data and larger models.
Paper: arxiv.org/abs/2508.03162
Data and models: huggingface.co/facebook/ODA...
07.08.2025 23:25 — 👍 8 🔁 3 💬 1 📌 0
Spending the Easter days prepping for #ICLR2025 in #singapore 😍🤩
If you want to meet/catch up on
#CuspAI
#AI4Science #MachineLearning and/or ML for #materials / #simulation ping me.!
DMs are open :)
My lovely colleagues Sina, @sindylowe.bsky.social and Govert are around too!
19.04.2025 20:04 — 👍 9 🔁 1 💬 1 📌 0
Singapore bound for #ICLR2025 next week! ✈️
Diving into foundation models for materials these days - would love to connect if you're in this space! Ping me for a chat ☕
Also excited to see the brilliant @takerumiyato.bsky.social present our paper as an oral. Don't miss it! 🌈
15.04.2025 14:48 — 👍 12 🔁 1 💬 1 📌 0
Synchronization is ubiquitous in nature and a key mechanism for information processing in the brain. We introduce AKOrN as a dynamical alternative to threshold units, which can be combined with MLPs, CNNs or Transformers. ICLR'25 Oral. Project page: takerum.github.io/akorn_projec...
12.02.2025 14:07 — 👍 47 🔁 11 💬 2 📌 2
As 2024 wraps up, sharing my biggest highlight of the year: defending my PhD in November! Five years of research condensed into one hour of intense discussion - and somehow it was very fun! Thankful, proud, and excited for the next chapter 🎓✨
31.12.2024 12:59 — 👍 17 🔁 0 💬 1 📌 0
Machine Learning at CuspAI - materials discovery for carbon capture
PhD student at @bifold.berlin, Machine Learning Group, TU Berlin.
Automatic Differentiation, Explainable AI and #JuliaLang.
Open source person: adrianhill.de/projects
NeuroAI PhD Candidate at McGill / Mila.
Loves: 🧠 🏕️ 🏔️ 🏊🏻♂️ 🚴🏻♂️ 🏃🏻♂️ 🎨📚☕
https://raymondchua.github.io
Natural and artificial general intelligence.
https://marcelbinz.github.io/
DPhil @ A2I, Oxford Robotics Institute
Research Scientist in the DINO team at Meta FAIR. Previously: PhD at Max-Planck Institute for Intelligent Systems, Tübingen. Representation learning, agents, structure.
Postdoc at SRON | Previously PhD at AMLab & AI4Science Lab, University of Amsterdam
Interested in AI for Earth science & ecology, hybrid modeling, geospatial machine learning
Neuroscience, Machine Learning, Computer Vision • Scientist at @unigoettingen.bsky.social & MPI-DS • https://eckerlab.org • Co-founder of https://maddox.ai • Dad of three • All things outdoor
Professor, University of Tübingen @unituebingen.bsky.social.
Head of Department of Computer Science 🎓.
Faculty, Tübingen AI Center 🇩🇪 @tuebingen-ai.bsky.social.
ELLIS Fellow, Founding Board Member 🇪🇺 @ellis.eu.
CV 📷, ML 🧠, Self-Driving 🚗, NLP 🖺
Head of Video & Image Sense Lab | University of Amsterdam | Scientific Director Amsterdam AI | https://www.ceessnoek.info/
Research Scientist at Sony AI, working on AI for Scientific Discovery.
Neurosymbolic Learning and Reasoning.
thiviyansingam.com
Learning in non-Euclidean spaces | ELLIS PhD student @ VIS Lab, University of Amsterdam | Board Member @ WiCVWorkshop | Open to internships for spring/summer 2025.
PhD candidate @amlab.bsky.social @ellis.eu
Probabilistic Machine Learning | Sequence Models
PhD Candidate Causal Machine Learning @AMLab @Adyen
NeurIPS workshop and digital community | 🌐 geometry, algebra, topology + 🤖 deep learning + 🧠 neuroscience | Join us on slack! http://tinyurl.com/nr-slack
Visit our website: https://www.neurreps.org/
Associate Professor & Co-Founder - Dynamical Deep Learning
