Rajesh P.N. Rao

Timeline

1. 1992–2000

   Degrees and a Salk postdoc

   He graduates summa cum laude from Angelo State University in 1992 with a B.S. in Computer Science/Mathematics. A master's degree in 1994 and a Ph.D. in 1998, both in computer science, follow at the University of Rochester. After a Sloan postdoctoral fellowship at the Salk Institute for Biological Studies, he joins the University of Washington faculty in 2000.

2. 1999

   A predictive coding model of vision

   With Dana Ballard, he publishes "Predictive coding in the visual cortex" in Nature Neuroscience in 1999. In their model, feedback connections from a higher visual area carry predictions of lower-level neural activity and feedforward connections carry the residual errors between the predictions and the actual activity.

3. 2006

   Brain control of a humanoid robot

   In 2006, he and his students at the University of Washington show that a person can order a humanoid robot to move to specific locations and pick up specific objects through brain waves. The operator, a graduate student in his lab, wears a cap with 32 electrodes that picks up the signals by electroencephalography.

4. 2009–2011

   Statistics of the Indus script

   In 2009, he is lead author of a Science study that compares the order of Indus script symbols with linguistic scripts and with nonlinguistic systems, including DNA and a programming language, and finds that the inscriptions fall in the middle of the spoken languages. In March 2011, he gives the TED talk "A Rosetta Stone for a lost language" on using modern computation to read the script.

5. 2013

   Brain-to-brain link and a textbook

   In August 2013, he and Andrea Stocco, a UW research assistant professor in psychology, demonstrate what they believe is the first noninvasive human-to-human brain interface. Electrical recordings of Rao's brain send a signal over the Internet that makes Stocco's finger press a key across campus. Cambridge University Press publishes his textbook Brain-Computer Interfacing in 2013.

6. 2016

   A Guggenheim Fellowship

   In 2016, he receives a Guggenheim Fellowship for the project "The Computational Brain: Understanding and Interfacing with Neuronal Networks." He also leads the National Science Foundation's Center for Sensorimotor Neural Engineering.

7. 2021–2024

   Brain co-processors and cortical theory

   In 2021, he receives a two-year Weill Neurohub grant to develop a "brain co-processor," a brain-computer interface that couples artificial neural networks with their biological counterparts so that the two learn alongside each other. In June 2024, he publishes "A sensory-motor theory of the neocortex" in Nature Neuroscience, proposing that the neocortex implements active predictive coding.

8. As of October 2026

   Professor and center co-director

   He is the CJ and Elizabeth Hwang Professor in the Paul G. Allen School of Computer Science & Engineering and the Department of Electrical & Computer Engineering at the University of Washington, co-director of the Center for Neurotechnology, and director of the Neural Systems Laboratory. His research spans computational neuroscience, brain-computer interfaces and artificial intelligence, and he co-teaches the course Neural Engineering (BIOEN 460) with Azadeh Yazdan in the fall quarter.