PhD student in Computer Science @UCSD. Studying interpretable AI and RL to improve people's decision-making.
PhD Student @ UC San Diego
Researching reliable, interpretable, and human-aligned ML/AI
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
I work with explainability AI in a german research facility
Researcher Machine Learning & Data Mining, Prof. Computational Data Analytics @jkulinz.bsky.social, Austria.
ML researcher, building interpretable models at Guide Labs (guidelabs.bsky.social).
Assistant Professor @ Harvard SEAS specializing in human-computer and human-AI interaction. Also interested in visualization, digital humanities, urban design.
Machine Learning Researcher | PhD Candidate @ucsd_cse | @trustworthy_ml
chhaviyadav.org
Assistant Professor @RutgersCS • Previously @MSFTResearch, @dukecompsci, @PinterestEng, @samsungresearch • Trustworthy AI • Interpretable ML • https://lesiasemenova.github.io/
Seeking superhuman explanations.
Senior researcher at Microsoft Research, PhD from UC Berkeley, https://csinva.io/
Professor in Artificial Intelligence, The University of Queensland, Australia
Human-Centred AI, Decision support, Human-agent interaction, Explainable AI
https://uqtmiller.github.io
Incoming Assistant Professor @ University of Cambridge.
Responsible AI. Human-AI Collaboration. Interactive Evaluation.
umangsbhatt.github.io
Senior Researcher @arc-mpib.bsky.social MaxPlanck @mpib-berlin.bsky.social, group leader #BOOSTING decisions: cognitive science, AI/collective intelligence, behavioral public policy, comput. social science, misinfo; stefanherzog.org scienceofboosting.org
Machine Learning PhD at UPenn. Interested in the theory and practice of interpretable machine learning. ML Intern@Apple.
Data Scientist @ Mass General, Beth Israel, Broad | Clinical Research | Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering, Oberlin BA Computer Science
CS Prof at the University of Oregon, studying adversarial machine learning, data poisoning, interpretable AI, probabilistic and relational models, and more. Avid unicyclist and occasional singer-songwriter. He/him
interpretable machine learning for atmospheric and astronomical data analysis, near-IR spectra, climate tech, stars & planets; bikes, Austin, diving off bridges into the ocean.
Assistant professor at University of Minnesota CS. Human-centered AI, interpretable ML, hybrid intelligence systems.
Researcher @Microsoft; PhD @Harvard; Incoming Assistant Professor @MIT (Fall 2026); Human-AI Interaction, Worker-Centric AI
zbucinca.github.io
Professor of computer science at Harvard. I focus on human-AI interaction, #HCI, and accessible computing.
