Yorgos Felekis
PhD student in Machine Learning and Causality @ University of Warwick | Enrichment student @ The Alan Turing Institute | These days thinking about Causal Abstractions, Optimal Transport, Information Theory, and Emergence.
Website: yfelekis.github.io
@officiallydac.bsky.social
Artist ~ Postdoc @ Sapienza University ~ Causality ~ Signal Processing ~ AI ~ Semantic Communication
@mmbronstein.bsky.social
DeepMind Professor of AI @Oxford Scientific Director @Aithyra Chief Scientist @VantAI ML Lead @ProjectCETI geometric deep learning, graph neural networks, generative models, molecular design, proteins, bio AI, 🐎 🎶
@warwickstats.bsky.social
Department of Statistics, University of Warwick. Home of MORSE, CRiSM, AS&RU and APTS. Top 20 QS World University Rankings in Statistics & Operational Research.
@agiamali.bsky.social
truthful not neutral | Anchor megatvofficial & realgroupgreece| Columnist in.gr |Feminist | LSE & City University Alumna
@mbalazs98.bsky.social
@sperez-vieites.bsky.social
Postdoctoral researcher at Aalto University and FCAI, Helsinki 🇫🇮 Previously in Edinburgh, Lille and Madrid. Working on Bayesian inference for state-space models, and Bayesian experimental design. https://sarapv.github.io/
@ema-ridopoco.bsky.social
Almost-PhD-completed in AI @ University of Trento and Pisa. I like #concepts, #symbols, and #representations, but I still don't know what they are. 📍 Trento, Italy 🧵 #identifiability, #shortcuts, #interpretability
@andrepugni.bsky.social
Research Fellow @ University of Trento. Studying ML models that know what they do not know. He/Him.
@causalclub.di.unipi.it
Causality Club proudly hosted at the University of Pisa and relying on strong assumptions since always. https://causalclub.di.unipi.it/
@jdijkman.bsky.social
Infusing statistical physics with machine learning to describe molecular fluids. PhD Candidate at UvA with Max Welling, Jan-Willem van de Meent and Bernd Ensing.
@adeelrazi.bsky.social
Computational Neuroscientist, NeuroAI, Causality. Monash, UCL, CIFAR. Lab: https://comp-neuro.github.io/
@dmachlanski.bsky.social
Research Associate in Causal AI at The University of Edinburgh (https://www.chai.ac.uk/). Causal AI for healthcare/medicine. CS PhD at the University of Essex. Former Software Developer.
@melodyyhuang.bsky.social
Currently @ Yale, working on causal inference & cutting down on caffeine. Website: melodyyhuang.com
@sherrirose.bsky.social
Stanford Professor | Computational Health Economics & Outcomes | Fair Machine Learning | Causality | Statistics | Health Policy | Health Equity drsherrirose.org Lab manual: stanfordhpds.github.io/lab_manual Personal account
@judithabk6.bsky.social
Researcher at Inria Saclay, team Soda working on machine learning and causal inference for health data
@valik-melnychuk.bsky.social
PhD Candidate at Institute of AI in Management, LMU Munich causal machine learning, causal inference
@osmanmian.bsky.social
www.sites.google.com/view/mian/ | Post Doc @ Institute for Artificial Intelligence in Medicine at Uniklinikum Essen | Previously Ph.D. Student. Causal Inference and Discovery @CISPA Helmholtz Center for Information Security
@dennisfrauen.bsky.social
(Ellis) PhD student at LMU Munich. Interested in causal machine learning and reinforcement learning
@harshparikh.bsky.social
(Incoming) Assistant Professor, Yale University Causal Inference and Machine Learning Postdoctoral Fellow -- Johns Hopkins University
@rickardkarlsson.bsky.social
PhD student working on causal inference and ML @ TU Delft rickardkarlsson.com
@urish.bsky.social
Machine learning researcher, working on causal inference and healthcare applications
@emrekiciman.bsky.social
causal ml; ai+society; social media, comp social science. having fun.. my opinions. he/him. http://hci.social/@emrek
@akumar03.bsky.social
<Causality | Ph.D. Candidate @mit | Physics> I narrate (probably approximately correct) causal stories. Past: Research Fellow @MSFTResearch Website: abhinavkumar.info
@awmsauter.bsky.social
All things causality, RL and generative models. PhD student in Amsterdam and Leiden.
@idiaz.bsky.social
Statistician. Associate prof. at NYU Grossman Department of Population Health. Causal inference, machine learning, and semiparametric estimation. https://idiazst.github.io/website/
@cianeastwood.bsky.social
Senior Research Scientist at Valence Labs. Generative modeling (causal, multimodal) and generalisation for scientific discovery. PhD in ML from UofEdinburgh and MPI-IS, with time at Google DeepMind, Meta AI and Spotify. 📍London 🔗 cianeastwood.github.io
@spectral.space
PhD student at UCL. Working on Gaussian Processes. I love everything mathy, videogames, and language. 🇧🇷 He/Ele/Él Also as @spectraldani@sigmoid.social
@dagophile.bsky.social
Interested in all things causal modeling. Ongoing projects on causal analyses of discrimination and on causation in dynamical systems.
@ehudk.bsky.social
Causal Inference 🔴→🟠←🟡. Machine Learning 🤖🎓. Data Communication 📈. Healthcare ⚕️. Creator of 𝙲𝚊𝚞𝚜𝚊𝚕𝚕𝚒𝚋: https://github.com/IBM/causallib Website: https://ehud.co
@annaciaunica.bsky.social
Philosopher / Cognitive Scientist working on self consciousness and social interactions in humans and artificial agents/ Embodiment/ AI / Art & Science In Lisbon & London
@marcdotson.com
Causal Inference | Bayesian Statistics | Machine Learning // Husband, father, Latter-day Saint, assistant professor of data analytics, nerd. Blog: occasionaldivergences.com | GitHub: github.com/marcdotson
@arxiv-stat-me.bsky.social
Statistics -- Methodology (stat.ME) source: export.arxiv.org/rss/stat.ME maintainer: @tmaehara.bsky.social
@a-marx.bsky.social
Prof. at TU Dortmund and RC Trust | Chair for Causality | Research on Causality, Machine Learning and Information Theory | Prev. ETH Zürich, ETH AI Center, CISPA and MPI for Informatics | Website: https://www.a-marx.com
@zhuyuchen.bsky.social
Machine Learning PhD student @UCL. Interested in Causality and AI Safety. yuchen-zhu.github.io
@stratiss.bsky.social
🚨On the academic job market🚨 PhD student @ Max Planck Institute for Software Systems. Interested in machine learning, game theory and causality. Previously at Meta, Stanford, NTUA. 💻 https://stsirtsis.github.io/
@philosotim.bsky.social
researching causality and interactive AI at AIML Lab, TU Darmstadt | also interested in philosophy, logic, physics and vegan baking
@jakobrunge.bsky.social
Professor of AI in the Sciences at University of Potsdam // causalinferencelab.com
@sergei-imaging.bsky.social
I like using machine learning to solve problems in physics, from discovering physical laws from observational microscopy data, designing and making better materials, and moving atoms by electron beams. Currently my group build automated microscopes.
@chandlersquires.bsky.social
CMU postdoc, previously MIT PhD. Causality, pragmatism, representation learning, and AI for biology / science more broadly. Proud rat dad.
@guyvdb.bsky.social
🎓 CS Prof at UCLA 🧠 Researching reasoning and learning in artificial intelligence: tactable deep generative models, probabilistic circuits, probabilistic programming, neurosymbolic AI https://web.cs.ucla.edu/~guyvdb/
@willorchard.bsky.social
PhD student | Causality, ML, comp bio @Cambridge_Uni | ex-Applied Science Intern @AmazonScience | ex-Visiting researcher @HelmholtzMunich | opinions my own
@wulfdewolf.bsky.social
PhD student @edinburgh-uni.bsky.social NeuroRSE intern @flatironinstitute.org NeuroAI intern @cshlnews.bsky.social Trying to understand spatial computation and memory in biological neural networks. I run a lot. wolfdewulf.eu