Dr. Rao is an Associate Professor in the UW Department of Computer Sciences and Engineering. The primary goal of Dr. Rao’s research is to discover the computational principles underlying the brain's remarkable ability to learn, process and store information, and to apply this knowledge to the task of building adaptive robotic systems and brain-computer interfaces (BCIs). How does the brain learn efficient representations of objects and events occurring in the natural environment? What are the algorithms that allow useful sensorimotor behaviors to be learned? What computational mechanisms allow the brain to adapt to changing circumstances and remain fault-tolerant and robust? How can the knowledge gained through computational studies of the brain be used in biomedical applications such as BCIs for the disabled?
In addition Rao’s lab is developing new methods that allow a humanoid robot to learn new actions and skills from a human teacher in much the same way that human infants and adults learn through observation and experimentation. Such an approach opens the door to a potentially powerful way of programming general-purpose humanoid robots--through human demonstration, obviating the need for complex physics-based models and explicit programming of behaviors.
Ph.D. University of Rochester, 1998
M.S. in Computer Science, University of Rochester, 1994
B.S. summa cum laude in Computer Science, Angelo State University, Texas, 1992
B.S. summa cum laude in Mathematics, Angelo State University, Texas, 1992
Associate Professor, Department of Computer Science and Engineering, University of Washington, 2005-Present
Assistant Professor, Department of Computer Science and Engineering, University of Washington, 2000-2004
Faculty Member, Neurobiology and Behavior Program, UW, 2001-present
ONR Young Investigator Award, 2003-2006
David and Lucile Packard Fellowship, 2002-2007
NSF CAREER Award, 2002-2007
Alfred P. Sloan Research Fellowship, 2001-2003
Alfred P. Sloan Postdoctoral Fellowship, Salk Institute for Biological Studies, 1997-2000
Probabilistic Models of the Brain: Perception and Neural Function, Rajesh P. N. Rao, Bruno A. Olshausen and Michael S. Lewicki (Eds.), Cambridge, MA: MIT Press, 2002.
David B. Grimes and Rajesh P. N. Rao. “A Bilinear Model for Sparse Coding” Advances in Neural Information Processing Systems 15, Cambridge, MA: MIT Press, 2003.
Aaron P. Shon and Rajesh P. N. Rao. “Learning Temporal Patterns by Redistribution of Synaptic Efficacy” Neurocomputing, Vol. 52-54, pp. 13-18, 2003.
Rajesh P. N. Rao and Terrence J. Sejnowski. “Complex Cell-Like Direction Selectivity through Spike-Timing Dependent Plasticity” IETE Journal of Research, Vol. 49(2), 2003.
Rajesh P. N. Rao, Gregory J. Zelinsky, Mary M. Hayhoe, and Dana H. Ballard. “Eye Movements in Iconic Visual Search” Vision Research, Vol. 42(11), pp. 1447-1463, 2002.
Rajesh P. N. Rao and Terrence J. Sejnowski. “Spike Timing Dependent Hebbian Plasticity as Temporal Difference Learning” Neural Computation, Vol. 13(10), pp. 2221-2237, 2001. Featured in a News and Views by Peter Dayan in Trends in Cognitive Science, Vol. 6(3), pp. 105-106, 2002.
Rajesh P. N. Rao and Terrence J. Sejnowski. “Predictive Coding, Cortical Feedback, and Spike-Timing Dependent Plasticity” in Probabilistic Models of the Brain: Perception and Neural Function, R. P. N. Rao, B. A. Olshausen and M. S. Lewicki (Eds.), Cambridge, MA: MIT Press, pp. 297-315, 2002.
Dana H. Ballard, Zuohua Zhang, and Rajesh P. N. Rao. “Distributed Synchrony: A Probabilistic Model of Neural Signaling” in Probabilistic Models of the Brain: Perception and Neural Function, R. P. N. Rao, B. A. Olshausen and M. S. Lewicki (Eds.), Cambridge, MA: MIT Press, pp. 273-283, 2002.
Rajesh P. N. Rao, David Eagleman, and Terrence J. Sejnowski. “Optimal Smoothing in Visual Motion Perception” Neural Computation, Vol. 13(6), pp. 1243-1253, 2001.
J. M. Fellous, A. R. Houweling, R. H. Modi, R. P. N. Rao, P. H. E. Tiesinga, and T. J. Sejnowski. “The Frequency Dependence of Spike Timing Reliability in Cortical Pyramidal Cells and Interneurons” J. Neurophysiology, Vol. 85(4), pp. 1782-1787, 2001.
Rajesh P. N. Rao and Terrence J. Sejnowski. “Predictive Learning of Temporal Sequences in Recurrent Neocortical Circuits” Novartis Foundation 2001 Symposium on Complexity in Biological Info. Processing, Vol. 239, pp. 208-229 (discussion: 229-240), 2001.
Chris Diorio and Rajesh P. N. Rao, “Neural Circuits in Silicon” Nature, Vol. 405, pp. 891-892, 2000.
Rajesh P. N. Rao and Terrence J. Sejnowski. “Predictive Sequence Learning in Recurrent Neocortical Circuits” Advances in Neural Information Processing Systems 12, Cambridge, MA: MIT Press, pp. 164-170, 2000.
Dana H. Ballard, Rajesh P. N. Rao, and Zuohua Zhang, “A Single-Spike Model of Predictive Coding” Neurocomputing, Vol. 32-33, pp. 17-23, 2000.
Rajesh P. N. Rao and Dana H. Ballard. “Predictive Coding in the Visual Cortex: A Functional Interpretation of Some Extra-Classical Receptive Field Effects” Nature Neuroscience, Vol. 2(1), pp. 79-87, 1999.
Rajesh P. N. Rao. “An Optimal Estimation Approach to Visual Perception and Learning” Vision Research, Vol. 39(11), pp. 1963-1989, 1999.
Rajesh P. N. Rao and Daniel L. Ruderman. “Learning Lie Groups for Invariant Visual Perception” M. S. Kearns, S. A. Solla and D. Cohn (Eds.), Advances in Neural Information Processing Systems 11, Cambridge, MA: MIT Press, pp. 810-816, 1999.
Rajesh P. N. Rao and Dana H. Ballard. “Development of Localized Oriented Receptive Fields by Learning a Translation-Invariant Code for Natural Images” Network: Computation in Neural Systems, Vol. 9(2), pp. 219-234, 1998.
Rajesh P. N. Rao. “Correlates of Attention in a Model of Dynamic Visual Recognition” M. I. Jordan, M. J. Kearns and S. A. Solla (Eds.), Advances in Neural Information Processing Systems 10, Cambridge, MA: MIT Press, pp. 80-86, 1998.
Dana H. Ballard, Garbis Salgian, Rajesh P. N. Rao and R. Andrew McCallum. “On the role of time in brain computation” L. R. Harris and M. Jenkin (Eds.), Vision and Action, Cambridge, UK: Cambridge University Press, pp. 82-119, 1998.
Rajesh P. N. Rao and Dana H. Ballard. “Dynamic Model of Visual Recognition Predicts Neural Response Properties in the Visual Cortex” Neural Computation, Vol. 9, pp. 721-763, 1997.
Rajesh P. N. Rao and Dana H. Ballard. “Efficient Encoding of Natural Time Varying Images Produces Oriented Space-Time Receptive Fields” Technical Report 97.4, National Resource Laboratory for the Study of Brain and Behavior, University of Rochester, August 1997. Rajesh P. N. Rao - 10 - July 2004
Rajesh P. N. Rao and Dana H. Ballard. “Cortico-Cortical Dynamics and Learning during Visual Recognition: A Computational Model” J. M. Bower (editor), Computational Neuroscience: Trends in Research 1997, New York, NY: Plenum Press, pp. 787-793, 1997.
Rajesh P. N. Rao and Dana H. Ballard. “A Computational Model of Spatial Representations That Explains Object-Centered Neglect in Parietal Patients” J. M. Bower (editor), Computational Neuroscience: Trends in Research 1997, New York, NY: Plenum Press, pp. 779-785, 1997.
Dana H. Ballard, Mary M. Hayhoe, Polly K. Pook, and Rajesh P.N. Rao. “Deictic Codes for the Embodiment of Cognition” Behavioral and Brain Sciences, Vol. 20(4), pp. 723-767, 1997.
Rajesh P. N. Rao, Gregory J. Zelinsky, Mary M. Hayhoe, and Dana H. Ballard. “Modeling Saccadic Targeting in Visual Search” D. Touretzky, M. Mozer and M. Hasselmo (Eds.), Advances in Neural Information Processing Systems 8, Cambridge, MA: MIT Press, pp. 830-836, 1996.
Rajesh P. N. Rao and Dana H. Ballard. “Learning Saccadic Eye Movements using Multiscale Spatial Filters” G. Tesauro, D.S. Touretzky and T.K. Leen (Eds.), Advances in Neural Information Processing Systems 7, Cambridge, MA: MIT Press, pp. 893-900, 1995.
Dana H. Ballard and Rajesh P. N. Rao. “A Computational Model of Human Vision Based on Visual Routines” (Invited Paper) Proc. of the DAGM (German Working Group in Pattern Recognition) Symposium, G. Sagerer, S. Posch, and F. Kummert (Eds.), Berlin: Springer-Verlag, 1995.
David B. Grimes, Aaron P. Shon, and Rajesh P. N. Rao. “Probabilistic Bilinear Models for Appearance-Based Vision” Proc. of the International Conference on Computer Vision (ICCV), 2003.
Rajesh P. N. Rao. “Dynamic Appearance-Based Recognition” Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’97), pp. 540-546, 1997.
Rajesh P. N. Rao. “A Kalman Filter That Learns Robust Models of Dynamic Phenomena” Proceedings of the 1997 Image Understanding Workshop, New Orleans, LA, 1997.
Rajesh P. N. Rao and Dana H. Ballard. “An Active Vision Architecture based on Iconic Representations” Artificial Intelligence, Vol. 78, pp. 461-505, 1995.
Rajesh P. N. Rao and Dana H. Ballard. “Natural Basis Functions and Topographic Memory for Face Recognition” Proc. of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 10-17, 1995. Rajesh P. N. Rao - 11 - July 2004
Rajesh P. N. Rao and Dana H. Ballard. “Object Indexing using an Iconic Sparse Distributed Memory” Proc. of the International Conference on Computer Vision (ICCV), pp. 24-31, 1995.
Rajesh P. N. Rao. “Top-Down Gaze Targeting for Space-Variant Active Vision.” Proc. of the ARPA Image Understanding Workshop, Monterey, CA, pp. 1049- 1058, November 1994.
Rajesh P. N. Rao and Dana H. Ballard. “A Multiscale Filterbank Approach to Camera Movement Control in Active Vision Systems.” Proc. of 1994 SPIE Conference on Intelligent Robots and Computer Vision XIII : 3D Vision, Product Inspection, and Active Vision, Vol. 2354, pp. 105-116, 1994.
Dana H. Ballard, Rajesh P.N. Rao, and Garbis Salgian. “Multiscale Spatial Filters for Visual Tasks and Object Recognition.” (Invited Paper) Proc. of the Second International Workshop on Visual Form, Capri, Italy, May, 1994.
Dana H. Ballard, and Rajesh P.N. Rao. “Seeing behind Occlusions.” Proc. of the Third European Conference on Computer Vision (ECCV), Stockholm, Sweden, May 1994, pp. 274-285.
Rajesh P. N. Rao and Olac Fuentes. “Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory” Autonomous Robots, Vol. 5, pp. 297-316, 1998 and Machine Learning, Vol. 31, pp. 87-113, 1998.
Rajesh P. N. Rao and Olac Fuentes. “Learning Navigational Behaviors using a Predictive Sparse Distributed Memory” From Animals to Animats: Proc. of the Fourth Int. Conf. on Simulation of Adaptive Behavior, pp. 382-390, 1996.
Olac Fuentes, Rajesh P. N. Rao, and Michael Van Wie. “ Hierarchical Learning of Reactive Behaviors in an Autonomous Mobile Robot” Proc. of IEEE International Conference on Systems, Man and Cybernetics, 1995.
Rajesh P. N. Rao and Olac Fuentes. “Perceptual Homing by an Autonomous Mobile Robot using Sparse Self-Organizing Sensory-Motor Maps” Proc. of World Congress on Neural Networks, pp. II380-II383, 1995.
Rajesh P. N. Rao. “A Note on P-Selectivity and Closeness” Information Processing Letters, Vol. 54, pp. 179-185, 1995. Rajesh P. N. Rao - 12 - July 2004
Rajesh P. N. Rao, J¨org Rothe and Osamu Watanabe. “Upward Separation for FewP and Related Classes” Information Processing Letters, Vol. 52, No. 4, pp. 175-180, 1994.
Gregory J. Zelinsky, Rajesh P. N. Rao, Mary M. Hayhoe, and Dana H. Ballard. “Eye Movements Reveal the Spatiotemporal Dynamics of Visual Search” Psychological Science, Vol. 8(6), pp. 448-453, 1997.
Gregory J. Zelinsky, Rajesh P. N. Rao, Mary M. Hayhoe, and Dana H. Ballard. “Adding Resolution to an Old Problem: Eye Movements as a Measure of Visual Search” G. Cottrell (editor), Proc. of the 18th Annual Conference of the Cognitive Science Society, June 12-15, La Jolla, CA, pp. 57-58, 1996.
