Dinesh Thangavel
Systems Software Engineer @ Nvidia, Winner TechCrunch Hackathon 2017, Masters from UW-Madison, CEG Alumni
@i80chains.bsky.social
This is an automated account, run by @toxic.sf.ca.us. It uses data provided by caltrans to post timely information about chain controls on Interstate 80 through the Sierra Nevada mountains. www.chainguy.com
@jskirzynski.bsky.social
PhD student in Computer Science @UCSD. Studying interpretable AI and RL to improve people's decision-making.
@haileyjoren.bsky.social
PhD Student @ UC San Diego Researching reliable, interpretable, and human-aligned ML/AI
@eml-munich.bsky.social
Institute for Explainable Machine Learning at @www.helmholtz-munich.de and Interpretable and Reliable Machine Learning group at Technical University of Munich and part of @munichcenterml.bsky.social
@zootime.bsky.social
I work with explainability AI in a german research facility
@juffi-jku.bsky.social
Researcher Machine Learning & Data Mining, Prof. Computational Data Analytics @jkulinz.bsky.social, Austria.
@juliusad.bsky.social
ML researcher, building interpretable models at Guide Labs (guidelabs.bsky.social).
@elglassman.bsky.social
Assistant Professor @ Harvard SEAS specializing in human-computer interaction. Also interested in visualization, digital humanities, urban design.
@chhaviyadav.bsky.social
Machine Learning Researcher | PhD Candidate @ucsd_cse | @trustworthy_ml chhaviyadav.org
@lesiasemenova.bsky.social
Postdoctoral Researcher at Microsoft Research • Incoming Faculty at Rutgers CS • Trustworthy AI • Interpretable ML • https://lesiasemenova.github.io/
@csinva.bsky.social
Senior researcher at Microsoft Research. Seeking good explanations with machine learning https://csinva.io/
@tmiller-uq.bsky.social
Professor in Artificial Intelligence, The University of Queensland, Australia Human-Centred AI, Decision support, Human-agent interaction, Explainable AI https://uqtmiller.github.io
@umangsbhatt.bsky.social
Assistant Professor & Faculty Fellow @ NYU. Responsible AI. Human-AI Collaboration. Interactive Evaluation. umangsbhatt.github.io
@stefanherzog.bsky.social
Senior Researcher @arc-mpib.bsky.social @Max Planck Hum. Developm. @mpib-berlin.bsky.social, group leader #BOOSTING decisions: cognitive science, hybrid collective intelligence, AI, behavioral public policy, misinfo; stefanherzog.org scienceofboosting.org
@fionaewald.bsky.social
PhD Student @ LMU Munich Munich Center for Machine Learning (MCML) Research in Interpretable ML / Explainable AI
@ryanchankh.bsky.social
Machine Learning PhD at UPenn. Interested in the theory and practice of interpretable machine learning. ML Intern@Apple.
@pedroribeiro.bsky.social
Data Scientist @ Mass General, Beth Israel, Broad | Clinical Research | Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering, Oberlin BA Computer Science
@gully.bsky.social
interpretable machine learning for atmospheric and astronomical data analysis, near-IR spectra, climate tech, stars & planets; bikes, Austin, diving off bridges into the ocean.
@harmankaur.bsky.social
Assistant professor at University of Minnesota CS. Human-centered AI, interpretable ML, hybrid intelligence systems.
@kgajos.bsky.social
Professor of computer science at Harvard. I focus on human-AI interaction, #HCI, and accessible computing.
@jennwv.bsky.social
Sr. Principal Researcher at Microsoft Research, NYC // Machine Learning, Responsible AI, Transparency, Intelligibility, Human-AI Interaction // WiML Co-founder // Former NeurIPS & current FAccT Program Co-chair // Brooklyn, NY // More at http://jennwv.com
@upolehsan.bsky.social
🎯 Making AI less evil= human-centered + explainable + responsible AI 💼 Harvard Berkman Klein Fellow | CS Prof. @Northeastern | Data & Society 🏢 Prev-Georgia Tech, {Google, IBM, MSFT}Research 🔬 AI, HCI, Philosophy ☕ F1, memes 🌐 upolehsan.com
@elenal3ai.bsky.social
PhD @UChicagoCS / BE in CS @Umich / ✨AI/NLP transparency and interpretability/📷🎨photography painting
@michaelhind.bsky.social
IBM Distinguished RSM, working on AI transparency, governance, explainability, and fairness. Proud husband & dad, Soccer lover. Posts are my own.
@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.
@henstr.bsky.social
Senior Research Scientist at IBM Research and Explainability lead at the MIT-IBM AI Lab in Cambridge, MA. Interested in all things (X)AI, NLP, Visualization. Hobbies: Social chair at #NeurIPS, MiniConf, Mementor-- http://hendrik.strobelt.com
@thomasfel.bsky.social
Explainability, Computer Vision, Neuro-AI.🪴 Kempner Fellow @Harvard. Prev. PhD @Brown, @Google, @GoPro. Crêpe lover. 📍 Boston | 🔗 thomasfel.me
@glima.bsky.social
PhD Researcher at #MPI_SP | MS and BS at KAIST | AI ethics, HCI, justice, accountability, fairness, explainability | he/him http://thegcamilo.github.io/
@asaakyan.bsky.social
PhD student at Columbia University working on human-AI collaboration, AI creativity and explainability. prev. intern @GoogleDeepMind, @AmazonScience asaakyan.github.io
@loradrian.bsky.social
RE at Instadeep, PhD in computational neuroscience, MSc in CS, interested in ML for life sciences.
@harrycheon.bsky.social
"Seung Hyun" | MS CS & BS Applied Math @UCSD 🌊 | LPCUWC 18' 🇭🇰 | Interpretability, Explainability, AI Alignment, Safety & Regulation | 🇰🇷
@martinagvilas.bsky.social
Computer Science PhD student | AI interpretability | Vision + Language | Cogntive Science. 🇦🇷living in 🇩🇪, she/her https://martinagvilas.github.io/
@mariaeckstein.bsky.social
Research scientist at Google DeepMind. Intersection of cognitive science and AI. Reinforcement learning, decision making, structure learning, abstraction, cognitive modeling, interpretability.
@alessiodevoto.bsky.social
PhD in ML/AI | Researching Efficient ML/AI (vision & language) 🍀 & Interpretability | @SapienzaRoma @EdinburghNLP | https://alessiodevoto.github.io/
@vedanglad.bsky.social
ai interpretability research and running • thinking about how models think • prev @MIT cs + physics
@vidhishab.bsky.social
AI Evaluation and Interpretability @MicrosoftResearch, Prev PhD @CMU.
@diatkinson.bsky.social
PhD student at Northeastern, previously at EpochAI. Doing AI interpretability. diatkinson.github.io
@peyrardmax.bsky.social
Junior Professor CNRS (previously EPFL, TU Darmstadt) -- AI Interpretability, causal machine learning, and NLP. Currently visiting @NYU https://peyrardm.github.io
@eberleoliver.bsky.social
Senior Researcher Machine Learning at BIFOLD | TU Berlin 🇩🇪 Prev at IPAM | UCLA | BCCN Interpretability | XAI | NLP & Humanities | ML for Science
@iislucas.bsky.social
Machine learning, interpretability, visualization, Language Models, People+AI research
@fatemehc.bsky.social
PhD student at Utah NLP, Human-centered Interpretability, Trustworthy AI
@besmiranushi.bsky.social
AI/ML, Responsible AI, Technology & Society @MicrosoftResearch
@begus.bsky.social
Assoc. Professor at UC Berkeley Artificial and biological intelligence and language Linguistics Lead at Project CETI 🐳 PI Berkeley SC Lab 🗣️ College Principal of Bowles Hall 🏰 https://www.gasperbegus.com
@apepa.bsky.social
Assistant Professor, University of Copenhagen; interpretability, xAI, factuality, accountability, xAI diagnostics https://apepa.github.io/
@lawlessopt.bsky.social
Stanford MS&E Postdoc | Human-Centered AI & OR Prev: @CornellORIE @MSFTResearch, @IBMResearch, @uoftmie 🌈
@e-giunchiglia.bsky.social
Assistant Professor at Imperial College London | EEE Department and I-X. Neuro-symbolic AI, Safe AI, Generative Models Previously: Post-doc at TU Wien, DPhil at the University of Oxford.
@qiaoyu-rosa.bsky.social
Final year NLP PhD student at UChicago. Explainability, reasoning, and hypothesis generation!
@sebastiendestercke.bsky.social
CS researcher in uncertainty reasoning (whenever it appears: risk analysis, AI, philosophy, ...), mostly mixing sets and probabilities. Posts mostly on this topic (french and english), and a bit about others. Personal account and opinions.