Directory

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.

Office
B204 Hamerschlag Hall
Phone
412.268.9658
Fax
412.268.6345
Email
byronyu@cmu.edu
Google Scholar
Byron Yu
Websites
Byron Yu's Website

Brain Computer Interfaces Helping People with Disabilities

Education

2007 Ph.D., Electrical Engineering, Stanford University

2003 MS, Electrical Engineering, Stanford University

2001 BS, Electrical Engineering and Computer Sciences, University of California, Berkeley

Media mentions


CMU Engineering

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.

CMU Engineering

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.

CMU Engineering

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.

CMU Engineering

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.

Axios

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.

CMU Engineering

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.”

Quanta Magazine

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.

CMU Engineering

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.

CMU Engineering

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.”

CMU Engineering

Final words

How will engineers advance technology to deepen our understanding of how the human brain works?