Assistant Professor @westernu.ca, Faculty Affiliate @vectorinstitute.ai. Probabilistic machine learning, decision-making, AI4Science. Bayesian + frequentist, etc!

PostDoc @ Uni Tübingen explainable AI, causality gunnarkoenig.com

University of Cambridge and Max Planck Institute for Intelligent Systems I'm interested in amortized inference/PFNs/in-context learning for challenging probabilistic and causal problems. https://arikreuter.github.io/

http://www.julian-rodemann.de | PhD student in statistics @LMU_Muenchen | currently @HarvardStats

Senior Lecturer and Researcher @LMU_Muenchen working on #ExplainableAI / #interpretableML and #OpenML

(Tab)PFNs, TrivialAugment etc.

Professor at ETH Zurich

PhD student sup. by Frank Hutter; researching automated machine learning and foundation models for (small) tabular data! Website: https://ml.informatik.uni-freiburg.de/profile/purucker/

Machine Learning Professor https://cims.nyu.edu/~andrewgw

Professor for AI/ML Methods in Tübingen. Posts about Probabilistic Numerics, Bayesian ML, AI for Science. Computations are data, Algorithms make assumptions.

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Full Professor of ML & #AutoML at Leibniz University Hannover. #ERC Grant Holder. Interested in: AutoML, ML, RL, iML, LLMs, foundation models and a lot more ;-)

Author of Interpretable Machine Learning and other books Newsletter: https://mindfulmodeler.substack.com/ Website: https://christophmolnar.com/

Subgroup Lead at the University of Freiburg researching generalizability of RL and Automated RL

Building AI systems that learn how to learn, grow and adapt continuously, and push humanity forward. Continual learning, meta-learning, open-endedness. Group Lead at TU Eindhoven, Founder of OpenML, NeurIPS D&B Track.

Researcher in machine learning

Faculty Fellow and Assistant Professor at NYU's Center of Data Science

Assistant Professor in CS + AI at USC. Previously at Stanford, CMU. Machine Learning, Decision Making, AI-for-Science, Generative AI, ML Systems, LLMs. https://willieneis.github.io

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. Web page https://users.aalto.fi/~ave/

PI at Helmholtz AI, Faculty at TU Munich, Fellow at Zuse School for reliable AI, Branco Weiss Fellow, ELLIS Scholar. Prev: Cambridge CBL, St John's College, ETH Zürich, Google Brain, Microsoft Research, Disney Research. https://fortuin.github.io/