Research Areas : Artificial Intelligence

In the past decade, an abundance of data has become available, such as online data on the Web, scientific data such as the transcript of the human genome, sensor data acquired by robots or by the buildings we inhabit. Turning data into information pertaining to problems that people care about, is the central mission of AI research at Stanford.

Members of the Stanford AI Lab have contributed to fields as diverse as bio-informatics, cognition, computational geometry, computer vision, decision theory, distributed systems, game theory, image processing, information retrieval, knowledge systems, logic, machine learning, multi-agent systems, natural language, neural networks, planning, probabilistic inference, sensor networks, and robotics.

Faculty Research Focus
Russ B. Altman biomedical informatics, bioengineering, biophysics, genetics 
Russ Altman application of computing technologies to basic molecular biological problems, now referred to as bioinformatics 
Serafim Batzoglou computational genomics 
Gill Bejerano computational genomics 
Atul J. Butte biomedical informatics 
Atul Butte translational bioinformatics 
Ed Feigenbaum knowledge-based systems 
Richard Fikes knowledge representation 
Mike Genesereth computational logic, semantic web, computational law, enterprise management, general game playing 
Leonidas Guibas computational geometry, image processing, graphics, computer vision, sensor networks, robotics, discrete algorithms  
Daniel Jurafsky computational linguistics, speech recognition, natural language 
Oussama Khatib robotics, haptics, motion planning 
Daphne Koller probability theory, decision theory, game theory, probabilistic inference 
Jean-Claude Latombe robot-assisted surgery, integration of design and manufacturing, digital actors, molecular motions 
Jure Leskovec mining and modeling large social and information networks 
Michael Levitt biomedical informatics 
Fei-Fei Li computer vision 
Percy Liang modeling both natural and programming languages, and exploring the semantic and pragmatic connections between the two; analyzing learning algorithms, both theoretically and empirically 
Chris Manning natural language processing, information retrieval,  
John McCarthy formal reasoning 
Mark D. Musen biomedical informatics 
Clifford I. Nass language, speech 
Andrew Ng machine learning, reinforcement learning/control, broad-competence AI 
Nils Nilsson robotics 
Kenneth Salisbury robotics, haptics, computer-aided surgery 
Yoav Shoham logic, multi-agent systems, game theory, electronic commerce 
Sebastian Thrun robotics, machine learning, probabilistic methods 
'ImageNet: A Large-Scale Hierarchical Image Database'
3-D Sensing of Deformable Objects
Adaptive Dynamic Collision Checking
Alignment & Comparative Genomics
Autonomous Helicopter Project
Building and Using a Semantivisual Image Hierarchy
CAMPAIGN - Clustering Algorithms in Modular, Parallel, and Accelerated Implementation for GPU Nodes
Climbing Robots
Collaborative Haptic Environments
Computational Game Theory (NSF ITR)
Computational Law
Computational Neuroscience: Scene Classification
DARPA Grand Challenge
Design Methodologies of Hybrid Actuation for Human-Friendly Robot.
Digital Department
Ed Feigenbaum's Search for A.I.
Efficient Extraction of Human Motion Volumes by Tracking
Elastic Strip Framework
Extracting Moving People from Internet Videos
General Game Playing
Grouplet: A Structured Image Representation for Recognizing Human and Object Interaction
Haptic-Feedback Assistive Devices
Human Action Categorization
Human Motion Analysis via Whole-Body Marker Tracking Control
Human Motion Synthesis
Human-Friendly Robot Design
Humanoid Robots on Rough Terrain
Independent Component Analysis: Identifying Data-Driven Human Gene Modules
Learning Models of Biological and Medical Data
Learning To Make Textual Inferences
Logical Spreadsheets
Machine Learning for Control
Modeling Flexible Protein Loops
Modeling Mutual Context of Object and Human Pose in Human-Object Interaction Activities
Multi-finger Manipulation
Multi-goal Motion Planning
Multiple-Contact-Point Haptics
OPTIMOL: automatic Object (or online) Picture collecTion via Incremental MOdel Learning
Probabilistic Relational Models
Quadruped Robot
Quantifying the Influence of Online Media
Real-time Motion Capture using a Single Time-Of-Flight Camera
Romeo & Juliet - Stanford Assistant Mobile Manipulations
Rope Manipulation Planning
SAI - Simulation & Active Interfaces
Sampling Propagation Cascades
Serpentine Mechanisms
Shallow Semantic Parsing
Small-step Retraction in PRM Planning
SMS Text Normalization using Statistical Machine Translation
Soft Tissue Modeling - towards real time simulation
Speech Processing
STAIR: The STanford AI Robot
Statistical Linguistics
StatNLP models: Combining linguistic and statistical sophistication
Study of Protein Motion
Surgical Simulation
Tactile Interfaces for Tele-Dermatology
Towards Total Scene Understanding:Classification, Annotation and Segmentation in an Automatic Framework
Understanding the Human Genome
Unsupervised Language Learning