@skiandsolve.bsky.social
⛷️ ML Theorist carving equations and mountain trails | 🚴♂️ Biker, Climber, Adventurer | 🧠 Reinforcement Learning: Always seeking higher peaks, steeper walls and better policies. https://ualberta.ca/~szepesva
@christiansarabia.com
tech, people, & philosophy | in search of paradigm shifts this is my school (of life) notebook
@tszzl.bsky.social
@ruizheli.bsky.social
Assistant Professor at University of Aberdeen | Postdoc at UCL | PhD at University of Sheffield | mechanistic interpretability & multimodal LLMs | https://www.ruizhe.space
@romapatel.bsky.social
research scientist @deepmind. language & multi-agent rl & interpretability. phd @BrownUniversity '22 under ellie pavlick (she/her) https://roma-patel.github.io
@stellaathena.bsky.social
I make sure that OpenAI et al. aren't the only people who are able to study large scale AI systems.
@mimansaj.bsky.social
Robustness, Data & Annotations, Evaluation & Interpretability in LLMs http://mimansajaiswal.github.io/
@variint.bsky.social
Enjoy not enjoying ideals | Interpretability of modular convnets applied to 👁️ and 🛰️🐝 | she/her 🦒💕 variint.github.io
@mdlhx.bsky.social
NLP assistant prof at KU Leuven, PI @lagom-nlp.bsky.social. I like syntax more than most people. Also multilingual NLP, interpretability, mountains and beer. (She/her)
@stephaniebrandl.bsky.social
Assistant Professor in NLP (Fairness, Interpretability and lately interested in Political Science) at the University of Copenhagen ✨ Before: PostDoc in NLP at Uni of CPH, PhD student in ML at TU Berlin
@jbarbosa.org
Junior PI @ INM (Paris) in computational neuroscience, interested in how computations enabling cognition are distributed across brain areas. Expect neuroscience and ML content. jbarbosa.org
@kylem.bsky.social
Full of childlike wonder. Building friendly robots. UT Austin PhD student, MIT ‘20.
@jeku.bsky.social
Postdoc at Linköping University🇸🇪. Doing NLP, particularly explainability, language adaptation, modular LLMs. I‘m also into🌋🏕️🚴.
@sejdino.bsky.social
Professor of Statistical Machine Learning at the University of Adelaide. https://sejdino.github.io/
@panisson.bsky.social
Principal Researcher @ CENTAI.eu | Leading the Responsible AI Team. Building Responsible AI through Explainable AI, Fairness, and Transparency. Researching Graph Machine Learning, Data Science, and Complex Systems to understand collective human behavior.
@mdhk.net
Linguist in AI & CogSci 🧠👩💻🤖 PhD student @ ILLC, University of Amsterdam 🌐 https://mdhk.net/ 🐘 https://scholar.social/@mdhk 🐦 https://twitter.com/mariannedhk
@lasha.bsky.social
✨On the faculty job market✨ Postdoc at UW, working on Natural Language Processing 🌐 https://lasharavichander.github.io/
@anneo.bsky.social
Comm tech & social media research professor by day, symphony violinist by night, outside as much as possible otherwise. German/American Pacific Northwestern New Englander, #firstgen academic, she/her, 🏳️🌈 https://anne-oeldorf-hirsch.uconn.edu
@aliciacurth.bsky.social
Machine Learner by day, 🦮 Statistician at ❤️ In search of statistical intuition for modern ML & simple explanations for complex things👀 Interested in the mysteries of modern ML, causality & all of stats. Opinions my own. https://aliciacurth.github.io
@ovdw.bsky.social
Technology specialist at the EU AI Office / AI Safety / Prev: University of Amsterdam, EleutherAI, BigScience Thoughts & opinions are my own and do not necessarily represent my employer.
@elianapastor.bsky.social
Assistant Professor at PoliTo 🇮🇹 | Currently visiting scholar at UCSC 🇺🇸 | she/her | TrustworthyAI, XAI, Fairness in AI https://elianap.github.io/
@rachel-law.bsky.social
Organic machine turning tea into theorems ☕️ AI @ Microsoft Research ➡️ Goal: Teach models (and humans) to reason better Let’s connect re: AI for social good, graphs & network dynamics, discrete math, logic 🧩, 🥾,🎨 Organizing for democracy.🗽 www.rlaw.me
@peyrardmax.bsky.social
Junior Professor CNRS (previously EPFL, TU Darmstadt) -- AI Interpretability, causal machine learning, and NLP. Currently visiting @NYU https://peyrardm.github.io
@jskirzynski.bsky.social
PhD student in Computer Science @UCSD. Studying interpretable AI and RL to improve people's decision-making.
@fionaewald.bsky.social
PhD Student @ LMU Munich Munich Center for Machine Learning (MCML) Research in Interpretable ML / Explainable AI
@simonschrodi.bsky.social
🎓 PhD student @cvisionfreiburg.bsky.social @UniFreiburg 💡 interested in mechanistic interpretability, robustness, AutoML & ML for climate science https://simonschrodi.github.io/
@angieboggust.bsky.social
MIT PhD candidate in the VIS group working on interpretability and human-AI alignment
@mariaeckstein.bsky.social
Research scientist at Google DeepMind. Intersection of cognitive science and AI. Reinforcement learning, decision making, structure learning, abstraction, cognitive modeling, interpretability.
@andreasmadsen.bsky.social
Ph.D. in NLP Interpretability from Mila. Previously: independent researcher, freelancer in ML, and Node.js core developer.
@butanium.bsky.social
Master student at ENS Paris-Saclay / aspiring AI safety researcher / improviser Prev research intern @ EPFL w/ wendlerc.bsky.social and Robert West MATS Winter 7.0 Scholar w/ neelnanda.bsky.social https://butanium.github.io
@amuuueller.bsky.social
Postdoc at Northeastern and incoming Asst. Prof. at Boston U. Working on NLP, interpretability, causality. Previously: JHU, Meta, AWS
@niklasstoehr.bsky.social
Research Scientist at Google DeepMind and PhD Student at ETH Zurich
@gsarti.com
PhD Student at @gronlp.bsky.social 🐮, core dev @inseq.org. Interpretability ∩ HCI ∩ #NLProc. gsarti.com
@nsaphra.bsky.social
Waiting on a robot body. All opinions are universal and held by both employers and family. Recruiting students to start my lab! ML/NLP/they/she.
@joestacey.bsky.social
NLP PhD student at Imperial College London and Apple AI/ML Scholar. My research is on model robustness and interpretability. #NLP #NLProc
@swetakar.bsky.social
Machine learning PhD student @ Blei Lab in Columbia University Working in mechanistic interpretability, nlp, causal inference, and probabilistic modeling! Previously at Meta for ~3 years on the Bayesian Modeling & Generative AI teams. 🔗 www.sweta.dev
@velezbeltran.bsky.social
Machine Learning PhD Student @ Blei Lab & Columbia University. Working on probabilistic ML | uncertainty quantification | LLM interpretability. Excited about everything ML, AI and engineering!
@ddjohnson.bsky.social
PhD student at Vector Institute / University of Toronto. Building tools to study neural nets and find out what they know. He/him. www.danieldjohnson.com
@amakelov.bsky.social
Mechanistic interpretability Creator of https://github.com/amakelov/mandala prev. Harvard/MIT machine learning, theoretical computer science, competition math.
@ajyl.bsky.social
Post-doc @ Harvard. PhD UMich. Spent time at FAIR and MSR. ML/NLP/Interpretability
@martinagvilas.bsky.social
Computer Science PhD student | AI interpretability | Vision + Language | Cogntive Science. https://martinagvilas.github.io/
@wordscompute.bsky.social
nlp/ml phding @ usc, interpretability & reasoning & pretraining & emergence 한american, she, iglee.me, likes ??= bookmarks
@apepa.bsky.social
Assistant Professor, University of Copenhagen; interpretability, xAI, factuality, accountability, xAI diagnostics https://apepa.github.io/
@fedeadolfi.bsky.social
Computation & Complexity | AI Interpretability | Meta-theory | Computational Cognitive Science https://fedeadolfi.github.io