Intelligent Systems at Georgia Tech

Welcome to the Intelligent Systems area of the College of Computing at Georgia Tech. We are one of the largest IS research groups in the US. The IS faculty conduct research in AI, Cogntive Science, Computational Perception, and Robotics. We advise PhD and MS students in these areas, and we offer a broad set of undergraduate and graduate courses in these areas.

Intelligent Systems Area Coordinator:

Charles Isbell

Graduate and Undergraduate Programs of Study in Intelligent Systems

• Undergraduate Intelligent Systems curriculum
• PhD in Computer Science at Georgia Tech
• The Intelligent Systems qualifier for PhD students

Intelligent Systems Faculty

	Ronald Arkin, Ph.D., University of Massachusetts The Mobile Robot Lab Behavior-based robotics, action-oriented perception, multi-robot systems
	Tucker Balch, Ph.D., Georgia Tech The BORG Lab Multi-robot systems, modeling physical social systems (e.g., social insects)
	Aaron Bobick, Ph.D., MIT Computational Perception Lab Vision machine perception of movement, activity, and action.
	Henrik Christensen, Ph.D., Aalborg University Robotics and Intelligent Machines Center Mobile robotics, biologically-inspired autonomous systems, computer vision
	Frank Dellaert, Ph.D., CMU The BORG Lab and The Computational Perception Laboratory Machine learning, Monte Carlo inference in computer vision and robotics, 4D scene reconstruction, simultaneous mapping and localization.
	Irfan Essa, Ph.D., MIT Computational Perception Lab Analysis, interpretation, and synthesis of human activities, and behaviors using time-varying data streams.
	Ashok Goel, Ph.D., Ohio State Design Intelligence Lab Analogical reasoning, reflection and self-design
	Alex Gray, Ph.D., CMU. Scalable machine learning
	Charles Isbell, Ph.D., MIT The Laboratory for Interactive Artificial Intelligence Machine learning, (human) activity discovery and modeling, scalable ML and optimization, interactive AI
	Janet Kolodner, Ph.D., Yale Learning by Design and Learning Sciences and Technology, Editor in Chief of the Journal of the Learning Sciences Learning sciences & technologies, cognitive science, AI, case-based reasoning, and computational models of distributed & situated mind.
	Nancy Nersessian, Ph.D., Case Western Human creativity in science
	Ashwin Ram; PhD, Yale Cognitive Computing Lab and The Laboratory for Interactive Artificial Intelligence Artificial intelligence, cognitive science, machine learning, case-based reasoning, natural language, education.
	James M. Rehg, Ph.D., CMU. Computational Perception Lab Probabilistic graphical models, rare event detection, learning for computer vision, graphics, software engineering and distributed systems.
	Mark Riedl, Ph.D., NCSU Intelligent Narrative Lab Computational narrative, game AI
	Thad Starner, Ph.D., MIT Contextual Computing Group Wearable computing, augmented reality, on-body perception
	Mike Stilman, Ph.D., CMU Humanoid Robotics Lab Humanoid robotics, compliant motion planning,
	Andrea Thomaz, Ph.D., MIT Socially Intelligent Machines Lab Human-Robot Interaction, human-driven robot learning

Programs of interest at Georgia Tech

• Robotics at Georgia Tech

Seminars of interest at Georgia Tech

• Intelligent Systems Reading Group
• Computational Perception and Robotics Seminar

Email lists for Intelligent Systems students and faculty

• is-students for IS-students. It is critical for IS students to subscribe to this list. Look here for important information about qualifiers and so on.
• robotics-fac for faculty members. This is a low-bandwidth strictly moderated email list for announcements relevant to robotics faculty.
• robotics-all for for everyone. This is a low-bandwidth strictly moderated email list for announcements relevant to anyone interested in robotics at Georgia Tech.

Contact

• This website is located at www.cc.gatech.edu/is
• Please email isbell @ cc.gatech.edu with corrections.