Andrew H. Fagg

Presidential Associates Presidential Professor and Associate Professor of Computer Science and Bioengineering

Email: andrewhfagg@gmail.com
Phone: (405) 325-8606
Office: Devon Energy Hall Room 243

Website: symbiotic-computing.org/fagg_html

Education
Postdoctoral Research Associate
University of Massachusetts Amherst
Ph.D., Computer Science
University of Southern California
M.S., Computer Science
University of Southern California
B.S., Computer Science
Carnegie Mellon University

Research Focus

Machine learning, robotics, computational neuroscience, brain-machine interfaces and interactive art.

Experience and Awards

Associate Professor, Biomedical Engineering Faculty, University of Oklahoma
Associate Professor, University of Oklahoma
Research Scientist, University of Massachusetts, Amherst
Senior Research Scientist, Department of Computer Science, University of Massachusetts, Amherst
Nominated for the university-level Outstanding Teacher Award for the 2002-2003 academic year (University of Massachusetts).
Smart Art Spaces course (co-taught with Artist Adam Brown) was selected as an OU Presidential Dream Course for Spring 2009.
Member: IEEE Robotics Society, IEEE Computer Society, Society for the Neural Control of Movement. Course Development: Empirical Methods, Embedded Systems (both CS and Aerospace versions), Neuro-Cognitive Robotics, and SM [ART] Spaces (cross-disciplinary with Art), Interactive Art Laboratory (introduction to engineering for freshmen).
Reviewer (recent): Machine Learning Journal; Systems, Man, and Cybernetics, Psychological Review; Systems and Control; International Conference on Intelligent Robots and Systems; International Conference on Humanoid Robotics (program committee); International Conference on Robotics and Automation; Epigenetic Robotics; Journal of Neurophysiology; Transactions on Robotics; Robotics: Systems and Science.

Biography

Dr. Andrew H. Fagg is an associate professor in the School of Computer Science at the University of Oklahoma. He holds a BS in Applied Mathematics/Computer Science from Carnegie-Mellon University, and a MS and a PhD in Computer Science from the University of Southern California. His research focuses on the computational issues surrounding the symbiotic relationships between humans and machines. In particular, he is interested in primate and robot learning of motor skills and task-oriented representations; reaching, grasping, and manipulation; brain-machine interfaces; and interactive art.

Selected Projects

NSF, “REU site on Embedded Machine Learning Systems,” Feb 2005-Jan 2008.

NSF, “REU site on Integrated Machine Learning Systems,” Feb 2009-Jan 2001.

National Institutes of Health, Northwestern University, “Development of a Bidirectional CNS Interface or Robotic Control,” May 2005-April 2009.

Selected Publications

“Kinetic Trajectory Decoding Using Motor Cortical Ensembles,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, to appear, 2009 (with Ojakangas, G., Miller, L., Hatsopoulos, N.).

“Toward a Biomimetic, Bidirectional, Brain Machine Interface,” Proceedings of the IEEE Engineering in Medicine and Biology Society, to appear, 2009 (with Hatsopoulos, N. G., London, B., Reimber, J., Solla, S., Wang, D., Miller, L. E.).

“A Switching Control Approach to Haptic Exploration for Quality Grasps,” Workshop on Robot Manipulation: Sensing and Adapting to the Real World at the 2007 Robotics: Science and Systems Conference, electronically published, 2007 (with Wang, D., Watson, B. T.).

“Biomimetic brain machine interfaces for the control of movement,” Journal of Neuroscience, 27(44), pp.11842-11846. 2007 (with Hatsopoulos, N. G., de Lafuente, V., Moxon, K. A. , Nemati, S., Rebesco, J. M., Romo, R., Solla, S. A., Tkach, D., Pohlmeyer, E. A., and Miller, L. E.).

“Grasp Affordances Through Human Demonstration,” Proceedings of the International Conference on Development and Learning (ICDL'06), electronically published, 2006 (with de Granville, C., Southerland, J.).