Research Areas - Artificial Intelligence (AI)

Overview

Work in Artificial Intelligence in the EECS department at Berkeley involves foundational research in core areas of knowledge representation, reasoning, learning, planning, decision-making, vision, robotics, speech and language processing. 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. Work in this area also involves techniques and tools from statistics, neuroscience, control, optimization, and operations research.

Topics

• Learning and Probabilistic Inference:

  Graphical models. Kernel methods. Nonparametric Bayesian methods. Reinforcement learning. Problem solving, decisions, and games.

• Knowledge Representation and Reasoning:

  First order probabilistic logics. Symbolic algebra.

• Search and Information Retrieval:

  Collaborative filtering. Information extraction. Image and video search. Intelligent information systems.

• Speech and Language:

  Parsing. Machine translation. Speech Recognition. Context Modeling. Dialog Systems.

• Vision:

  Grouping and Figure-Ground. Object Recognition. Human Activity Recognition. Active Vision.

• Robotics:

  Motion Planning, Computational Geometry. Computer assisted surgical and medical analysis, planning, and monitoring. Unmanned Air Vehicles

Research Centers

• Berkeley Initiative in Soft Computing (BISC)
• Center for Intelligent Systems (CIS)

Research Projects

Faculty

• Pieter Abbeel
• Ruzena Bajcsy
• Peter Bartlett
• John F. Canny
• Trevor Darrell
• Alexei (Alyosha) Efros
• Laurent El Ghaoui
• Richard J. Fateman
• Jerome A. Feldman
• Ken Goldberg
• Michael Jordan
• Daniel Klein
• Jitendra Malik (coordinator)
• Lior Pachter
• Stuart J. Russell
• S. Shankar Sastry
• Lotfi A. Zadeh
• Avideh Zakhor

Related Courses

• CS 188. Introduction to Artificial Intelligence
• CS 280. Computer Vision
• CS 281A. Statistical Learning Theory
• CS 281B. Advanced Topics in Learning and Decision Making
• CS 287. Advanced Robotics
• CS 288. Artificial Intelligence Approach to Natural Language Processing
• CS 294. Artificial Intelligence Programming Techniques
• EE C125/C215A. Introduction to Robotics
• EE 128. Feedback Control Theory
• EE 227A. Introduction to Convex Optimization
• EE 290P. Advanced Topics in Bioelectronics
• EE/CS 298. Center for Intelligent Systems (CIS)