@maninekkalapudi.io
Plays with data and code. Data Engineer and infra enthusiast Socials: linktr.ee/maninekkalapudi
@khademinori.bsky.social
Postdoctoral Fellow, Deep Learning, @TorontoMet, PhD from @QueensU
@olgatticus.bsky.social
MSCA PhD student at AMLab with Erik Bekkers, interested in geometric deep learning, generative models and their intersection 🌐 ✨ K-hip hop scholar 🇰🇷 and dancer-in-the-making 💃 bit.ly/olga-zaghen
@sharvaree.bsky.social
PhD student at @amlab.bsky.social Geometric deep learning + Generative modeling. 🇳🇱🇺🇸🇮🇳 Organizer @gram-org.bsky.social workshop 📍 Amsterdam/SF
@ninamiolane.bsky.social
Assis. Prof. @ucsbece Affiliate @SLAClab Stanford Prev @Stanford @Inria @imperialcollege @Polytechnique PI @geometric_intel http://gi.ece.ucsb.edu, Pilot
@amlab.bsky.social
The official account of the Amsterdam Machine Learning Lab (AMLab) at UvA, co-directed by Max Welling and Jan-Willem van de Meent.
@s-azeglio.bsky.social
From Physics to Vision Neuroscience & AI | PhD Candidate @InstVisionParis & @ENS_ULM | Enjoyed my time @FlatironCCN, @CERN | co-organizer @neurreps
@algarciacast.bsky.social
PhD candidate at @amlab.bsky.social focusing on Geometry-informed Machine Learning 🤖 https://agarciacast.github.io
@maxxxzdn.bsky.social
PhD candidate at AMLab with Max Welling and Jan-Willem van de Meent. Research in physics-inspired and geometric deep learning.
@congliu.bsky.social
PhD student @ AMLab interested in Geometric Deep Learning, AI4Science, generative models on Molecules / Protein
@dafidofff.bsky.social
PhD candidate w/ @erikjbekkers & @egavves interested in Geometric Deep Learning and Generative Modelling at @AMLab & @ellogonai github.com/Dafidofff
@davidmknigge.bsky.social
PhD candidate at UvA in continuous signal modelling, geometric deep learning and dynamics.
@erikjbekkers.bsky.social
AMLab, Informatics Institute, University of Amsterdam. ELLIS Scholar. Geometry-Grounded Representation Learning. Equivariant Deep Learning.
@neribr.bsky.social
Technical Leader - Artificial Intelligence and Machine Learning Enthusiast - Senior Software Engineer https://www.linkedin.com/in/brunoneri
@eijkelboomfloor.bsky.social
PhD candidate at University of Amsterdam | Physics-Informed Generative Modeling
@artemmoskalev.bsky.social
Re-imagining drug discovery with AI 🧬. Deep Learning ⚭ Geometry. Previously PhD at the University of Amsterdam. https://amoskalev.github.io/
@gram-org.bsky.social
Geometry-grounded representation learning and generative modeling at ICML.
@sallyhines.bsky.social
Gender Studies & Sociology Academic, UK. Proudly deflecting from the nasty place. She/her
@meredithmeredith.bsky.social
President of Signal, Chief Advisor to AI Now Institute
@mioana.bsky.social
Senior researcher at Inria, Part-time professor at Ecole Polytechnique, France. ACM Senior Member. Working on BigData, AI, Fact-Checking, Disinformation https://pages.saclay.inria.fr/ioana.manolescu/
@karlrohe.bsky.social
“Overly optimistic” 🦮 in Statistics. Listening in statistics. Statistics Professor at UW Madison.
@csprofkgd.bsky.social
#CS Associate Prof York University, #ComputerVision Scientist Samsung #AI, VectorInst Faculty Affiliate, TPAMI AE, ELLIS4Europe Member, #CVPR2025 Publicity Chair on X 📍Toronto 🇨🇦 🔗 csprofkgd.github.io 🗓️ Joined Nov 2024
@nolovedeeplearning.bsky.social
human being | assoc prof in #ML #AI #Edinburgh | PI of #APRIL | #reliable #probabilistic #models #tractable #generative #neuro #symbolic | heretical empiricist | he/him 👉 https://april-tools.github.io
@archernikov.bsky.social
Michael Brin professor of mathematics at the University of Maryland. Mathematical logic, model theory - and connections to combinatorics, algebra, etc. chernikov.me
@laurentdinh.bsky.social
Internet pedestrian. ✨Content creator✨ (ML researcher). ᕕ(ツ)ᕗ (he/him/his) https://laurent-dinh.github.io/
@fxbriol.bsky.social
Associate Professor at UCL Statistical Science. Interested in computational statistics, machine learning and applications in the sciences & engineering.
@marvinschmitt.bsky.social
🇪🇺 AI/ML, Member @ellis.eu 🤖 Generative NNs, ProbML, Uncertainty Quantification, Amortized Inference, Simulation Intelligence 🎓 PhD+MSc CS, MSc Psych 🏡 marvinschmitt.github.io ✨ On the job market, DMs open 📩
@canaesseth.bsky.social
Assistant Professor of Machine Learning Generative AI, Uncertainty Quantification, AI4Science Amsterdam Machine Learning Lab, University of Amsterdam https://naesseth.github.io
@fragrisoni.bsky.social
Associate Prof | AI for drug discovery | Eindhoven University of Technology | Previously ETH Zurich & UniMiB | she/her 🏳️🌈
@glouppe.bsky.social
AI for Science, deep generative models, inverse problems. Professor of AI and deep learning @universitedeliege.bsky.social. Previously @CERN, @nyuniversity.
@yaringal.bsky.social
Associate Professor of Machine Learning, University of Oxford; OATML Group Leader; Director of Research at the UK government's AI Safety Institute (formerly UK Taskforce on Frontier AI)
@twkillian.bsky.social
Senior Research Scientist @MBZUAI. Focused on decision making under uncertainty, guided by practical problems in healthcare, reasoning, and biology.
@neuralnoise.com
Researcher in ML/NLP at the University of Edinburgh (faculty at Informatics and EdinburghNLP), Co-Founder/CTO at www.miniml.ai, ELLIS (@ELLIS.eu) Scholar, Generative AI Lab (GAIL, https://gail.ed.ac.uk/) Fellow -- www.neuralnoise.com, he/they
@avehtari.bsky.social
Professor in computational Bayesian modeling at Aalto University, Finland. Bayesian Data Analysis 3rd ed, Regression and Other Stories, and Active Statistics co-author. #mcmc_stan and #arviz developer. Also in Mastodon: https://bayes.club/@avehtari
@jmhessel.bsky.social
jmhessel.com NLP PhD; Seattle bike lane enjoyer; posts about machine learning, language processing, computer vision, transit
@ccanonne.github.io
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
@carl-allen.bsky.social
Laplace Junior Chair, Machine Learning ENS Paris. (prev ETH Zurich, Edinburgh, Oxford..) Working on mathematical foundations/probabilistic interpretability of ML (what NNs learn🤷♂️, disentanglement🤔, king-man+woman=queen?👌…)
@dholzmueller.bsky.social
Postdoc in machine learning with Francis Bach & @GaelVaroquaux: neural networks, tabular data, uncertainty, active learning, atomistic ML, learning theory. https://dholzmueller.github.io
@ergodicwalk.bsky.social
Randomly transitioning between information theory, ML, privacy, statistics, and other destinations. Not using \mathbb in a logo.