Moritz Hardt

I'm a director at the Max Planck Institute for Intelligent Systems. Prior to joining the institute, I was Associate Professor for Electrical Engineering and Computer Sciences at the University of California, Berkeley. My research contributes to the scientific foundations of machine learning and algorithmic decision making with a focus on social questions.

Contact

Writing

• For papers and preprints, see: arXiv, Google Scholar, Lab page
• Books:
  • The emerging science of machine learning benchmarks (Princeton University Press, 2026)
  • Fairness and machine learning: Limitations and opportunities with Barocas and Narayanan (MIT Press, 2023)
  • Patterns, predictions, and actions: Foundations of machine learning with Recht (Princeton University Press, 2022)
• Expository articles:
  • The Future of Prediction: In Conversation with Oskar Morgenstern (International Congress of Mathematicians, 2026)
  • Performative Prediction: Past and Future with Mendler-Dünner (Statistical Science, 2025)
• Lecture notes:
  • Graduate optimization, UC Berkeley (EE 227C)
• Blog: Moody Rd (2013--2016)
• Software: folktables, folktexts, whynot, unbuch, PrivateMultiplicativeWeights.jl
  See the Social Foundations GitHub page for a more complete list.

Open positions

Prospective PhD students, please apply through one of the following programs:

• ELLIS PhD program
• International Max Planck Research School for Intelligent Systems (IMPRS-IS)
• Max Planck ETH Center for Learning Systems

The Tübingen AI Center is recruiting for professor positions with permanently reduced teaching load and significant permanent research funding.

Team

PhD students

• Nikhil Chandak, co-advised with Tim Rocktäschel, UCL
• André Cruz
• Florian Dorner, co-advised with Fanny Yang, ETH Zürich
• Mila Gorecki
• Vivian Nastl, co-advised with Nicolai Meinshausen and Peter Bühlmann, ETH Zürich
• Ricardo Olmedo, co-advised with Bernhard Schölkopf
• Mina Remeli, co-advised with Bob Williamson
• Irene Strauss, co-advised with Miri Zilka, University of Cambridge
• Cheng-Kuang (Brian) Wu, co-advised with Jakob Foerster, University of Oxford
• Jiduan Wu, co-advised with Niao He, ETH Zürich
• Sierra Wyllie, co-advised with Nicolas Papernot, University of Toronto
• Guanhua Zhang, co-advised with Martin Jaggi, EPFL

Postdocs and group leaders

• Yatong Chen
• Dingfan Chen
• Haiwen Huang
• Nastaran Okati
• Ana-Andreea Stoica

Alumni

PhD students

• Frances Ding (PhD 2024), Meta
• Chloe Hsu (PhD 2023), Isomorphic Labs (previously Safe Superintelligence)
• Lydia T. Liu (PhD 2022), Assistant Professor, Princeton University
• John Miller (PhD 2022), Anthropic
• Smitha Milli (PhD 2022), Meta Superintelligence Labs
• Juan C. Perdomo (PhD 2023), Assistant Professor, New York University
• Ali Shirali (PhD 2025), Voleon
• Yu Sun (PhD 2023), OpenAI (incoming Assistant Professor, University of Washington)
• Tijana Zrnic (PhD 2023), Assistant Professor, Stanford University

Postdocs and group leaders

• Kevin T. Baker, writer and historian of computing
• Celestine Mendler-Dünner, Associate Professor, ETH Zürich
• Ludwig Schmidt, Anthropic (previously Assistant Professor, Stanford University)

Interns

• Yair Carmon (2017), Safe Superintelligence and Tel Aviv University
• Sílvia Casacuberta Puig (2024), PhD student, Stanford University
• Gary Cheng (2022), Co-founder, Amplify Renewables
• Roy Frostig (2016), Google DeepMind
• Tengyu Ma (2015), Assistant Professor, Stanford University; Chief AI Scientist, MongoDB
• Olawale Salaudeen (2023), Microsoft Research (incoming Assistant Professor, University of Illinois Urbana-Champaign)
• Mary Wootters (2014), Associate Professor, Stanford University
• Chiyuan Zhang (2016), Google DeepMind

Service and affiliations

• NeurIPS 2023 program co-chair
• University of Tübingen, Honorary Professor
• University of Tübingen, University Council (Universitätsrat)
• Tübingen AI Center, Steering Committee
• ELLIS Society, Fellow
• Cluster of Excellence "Machine Learning: New Perspectives for Science", Member

Conflict of Interest Disclosure

Any corporate activity, involving employment, consulting, and funding in the last ten years:

• Co-founder: grubel (2026--present)
• Corporate research funding (unrestricted/gift): Twitter (2019 and 2020, administered through UC Berkeley)
• Consulting agreements: Google (20%, 2017--2019), Twitter (20%, 2019--2021)
• Full-time employment: Google 2015--2017