Byron Yu is a professor in the Departments of Electrical and Computer Engineering and Biomedical Engineering at Carnegie Mellon University. Yu received a B.S. degree in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 2001. He received M.S. and Ph.D. degrees in Electrical Engineering in 2003 and 2007, respectively, from Stanford University. From 2007 to 2009, he was a postdoctoral fellow jointly in Electrical Engineering and Neuroscience at Stanford University and at the Gatsby Computational Neuroscience Unit, University College London.
Yu joined the faculty of Carnegie Mellon University in 2010, where he is an associate professor in the Departments of Electrical and Computer Engineering and Biomedical Engineering and the Gerard G. Elia Career Development Professor. He is broadly interested in how large populations of neurons process information, from encoding sensory stimuli to driving motor actions. His group develops and applies novel statistical algorithms and uses brain-computer interfaces to study brain function.
Brain Computer Interfaces Helping People with Disabilities
American Institute for Medical and Biological Engineering
Engineering faculty named AIMBE Fellows
BME’s Adam Feinberg, ChemE’s Kathryn Whitehead, BME’s Byron Yu, and BME Associate Department Head Conrad Zapanta have been elected to the American Institute for Medical and Biological Engineering’s College of Fellows.
NIH-funded project will get your attention
Matt Smith and Byron Yu will simultaneously record multiple regions of the brain as subjects go through the process of preparing, establishing, and maintaining attention.
How the brain’s internal states affect decision-making
By recording the activity of separate populations of neurons simultaneously, researchers have gained an unprecedented insight into how the “waxing and waning” of our mental state influences the decisions we make.
Stabilizing brain-computer interfaces
New research will drastically improve brain-computer interfaces and their ability to remain stabilized, greatly reducing the need to recalibrate these devices during or between experiments.
Brain changes when mastering new skills
Mastering a new skill—whether a sport, an instrument, or a craft—takes time and training. While it is understood that a healthy brain is capable of learning these new skills, how the brain changes in order to develop new behaviors is a relative mystery.
CMU researchers read data from brains to help people learn
A group of CMU engineering researchers is working on connecting with brains to help people learn faster. They read data from volunteers’ brains as they learn to control a computer cursor with their minds.
Information bottlenecks between brain areas
ECE/BME’s Byron Yu and ECE postdoc João Semedo found that communication between brain areas occurs through an information bottleneck, which they’ve termed a “communication subspace.”
Yu and Chase quoted in Quanta on roadblocks to learning
Byron Yu and Steve Chase were quoted in Quanta Magazine about their research on how the brain reused old neural patterns when learning new tasks.
The learning brain is less flexible than we thought
New research from CMU and Pitt reveals that when learning a new task, the brain is less flexible than previously thought.
Yu receives NSF grant for brain research
The NSF recently awarded BME/ECE’s Byron Yu and Professor Matthew Smith from the University of Pittsburgh nearly $500,000 to conduct research on brain activity.
Professorships and fellowships
Congratulations to the CIT faculty members who were recently awarded fellowships and professorships.
Yu and Chase receive NIH grant for brain-computer interface research
ECE/BME’s Byron Yu and BME’s Steven Chase received a five-year renewal on their NIH grant entitled, “Shaping Neural Population Dynamics to Facilitate Learning.”