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For operational updates and health guidance from the University, please visit the COVID-19 Resource Guide.
To learn more about our spring term, please visit the Updates for Students page.
363 Engineering Terrace
Qi Wang develops new technologies for restoring and enhancing sensory functions and cognition through brain-machine interfaces (BMI). He has been working on cracking neural codes underlying our perception and cognition, and has been developing new strategies for selectively activating neural circuitry.
Of particular interest to Wang is to understand how sensory information is processed in the brain to form perception and inform an optimal decision, and how this process is modulated by behavioral states, such as attention and arousal. He utilizes experimental and theoretic approaches to tackle these questions. More specifically, his group uses single-unit electrophysiology, optogenetics, and patterned microstimulation, in concert with behavioral tasks, to model interactions between different brain regions during sensory processing and engineer sensory percepts through patterned microstimulation in the nervous system.
Wang received a BS in mechanical engineering from North China University of Electric Power in 1992 and a Master and PhD in Robotics from Harbin Institute of Technology in 1995 and 1998, respectively. He earned his second PhD in Electrical and Computer Engineering from McGill University in 2006, and received postdoc training in neuroscience at Harvard University from 2006 to 2008. He received numerous awards, including the IEEE EMBS Early Career Achievement in 2014, the Sackler Convergence Award in 2015, the NARSAD Young Investigator award in 2014, and the Best Paper Award at 14th IEEE Haptics Symposium in 2006.