Artificial Intelligence (AI)
Overview
Work in Artificial Intelligence in the EECS department at Berkeley involves foundational research in core areas of deep learning, knowledge representation, reasoning, learning, planning, decision-making, vision, robotics, speech, and natural language processing. For more information please see the Berkeley Artificial Intelligence Research Lab (BAIR). There are also significant efforts aimed at applying algorithmic advances to applied problems in a range of areas, including bioinformatics, networking and systems, search and information retrieval. There are active collaborations with several groups on campus, including the campus-wide vision sciences group, the information retrieval group at the I-School and the campus-wide computational biology program. There are also connections to a range of research activities in the cognitive sciences, including aspects of psychology, linguistics, and philosophy. Research in AI involves techniques and tools from statistics, neuroscience, control, optimization, and operations research.
Topics
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Learning and Probabilistic Inference:
Graphical models. Kernel methods. Nonparametric Bayesian methods. Reinforcement learning. Problem solving, decisions, and games.
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Knowledge Representation and Reasoning:
First order probabilistic logics. Symbolic algebra.
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Search and Information Retrieval:
Collaborative filtering. Information extraction. Image and video search. Intelligent information systems.
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Speech and Language:
Parsing. Machine translation. Speech Recognition. Context Modeling. Dialog Systems.
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Vision:
Object Recognition. Scene Understanding. Human Activity Recognition. Active Vision. Grouping and Figure-Ground. Visual Data Mining.
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Robotics:
Deep Learning, Perception, Manipulation, Locomotion, Human Robot Interaction, Motion Planning. Applications to Logistics, Healthcare, Home and Service Robots, Agriculture.
Research Centers
- Berkeley Artificial Intelligence Research Lab
- Berkeley Center for Responsible, Decentralized Intelligence (RDI)
- Berkeley Equity and Access in Algorithms, Mechanisms, and Optimization
- Berkeley Laboratory for Information and System Sciences
- Center for Human Compatible Artificial Intelligence
- Center for the Theoretical Foundations of Learning, Inference, Information, Intelligence, Mathematics and Microeconomics at Berkeley
- CITRIS People and Robots
- FHL Vive Center for Enhanced Reality
- International Computer Science Institute
- Sky Computing Lab
- Verified Human Interfaces, Control, and Learning for Semi-Autonomous Systems
- Video and Image Processing Lab
Faculty
Primary
- Pieter Abbeel
- Gopala Krishna Anumanchipalli
- Peter Bartlett
- Christian Borgs
- John F. Canny
- Serina Chang
- Irene Chen
- John DeNero
- Anca Dragan
- Alexei (Alyosha) Efros
- Ken Goldberg
- Joseph Gonzalez
- Nika Haghtalab
- Jiantao Jiao
- Michael Jordan
- Angjoo Kanazawa
- Kurt Keutzer
- Daniel Klein
- Aditi Krishnapriyan
- Sergey Levine
- Michael Lustig
- Yi Ma
- Jitendra Malik (coordinator)
- Song Mei
- Sewon Min
- Igor Mordatch
- Narges Norouzi
- Emma Pierson
- Gireeja Ranade
- Benjamin Recht
- Stuart J. Russell
- Anant Sahai
- S. Shankar Sastry
- Somayeh Sojoudi
- Dawn Song
- Jacob Steinhardt
- Jonathan Stray
- Alane Suhr
- Martin Wainwright
- Adam Yala
- Matei Zaharia
Secondary
- Venkat Anantharam
- Ruzena Bajcsy
- Alexandre Bayen
- Zaijun Chen
- Thomas Courtade
- Trevor Darrell
- Laurent El Ghaoui
- Richard J. Fateman
- Jerome A. Feldman
- Marti Hearst
- Nilah Ioannidis
- Preeya Khanna
- Jennifer Listgarten
- Ren Ng
- Pierluigi Nuzzo
- James O'Brien
- Kannan Ramchandran
- Jaijeet Roychowdhury
- Alberto L. Sangiovanni-Vincentelli
- Sanjit A. Seshia
- Yun S. Song
- Mengjie Yu
- Stella Yu
- Avideh Zakhor
Faculty Awards
- ACM Prize in Computing: Pieter Abbeel, 2021. Alexei (Alyosha) Efros, 2016.
- MacArthur Fellow: Dawn Song, 2010.
- National Academy of Sciences (NAS) Member: Jitendra Malik, 2015. Michael Jordan, 2010.
- National Academy of Engineering (NAE) Member: Jitendra Malik, 2011. Michael Jordan, 2010. S. Shankar Sastry, 2001. Alberto L. Sangiovanni-Vincentelli, 1998. Ruzena Bajcsy, 1997.
- American Academy of Arts and Sciences Member: Alberto L. Sangiovanni-Vincentelli, 2024. Jitendra Malik, 2013. Michael Jordan, 2010. Ruzena Bajcsy, 2007. S. Shankar Sastry, 2003.
- Berkeley Citation: Ruzena Bajcsy, 2023. S. Shankar Sastry, 2018. Jerome A. Feldman, 2009.
- UC Berkeley Distinguished Teaching Award: John DeNero, 2018. Daniel Klein, 2010. Alberto L. Sangiovanni-Vincentelli, 1981.
- Sloan Research Fellow: Nika Haghtalab, 2024. Preeya Khanna, 2024. Angjoo Kanazawa, 2023. Sergey Levine, 2019. Anca Dragan, 2018. Ren Ng, 2017. Michael Lustig, 2013. Benjamin Recht, 2011. Pieter Abbeel, 2011. Sanjit A. Seshia, 2008. Yun S. Song, 2008. Alexei (Alyosha) Efros, 2008. Dawn Song, 2007. Daniel Klein, 2007. Martin Wainwright, 2005. James O'Brien, 2003.
Related Courses
- CS 188. Introduction to Artificial Intelligence
- CS 189. Introduction to Machine Learning
- CS C280. Computer Vision
- CS C281A. Statistical Learning Theory
- CS C281B. Advanced Topics in Learning and Decision Making
- CS 287. Advanced Robotics
- CS 289A. Introduction to Machine Learning
- EE 290P. Advanced Topics in Electrical Engineering: Advanced Topics in Bioelectronics