The American Epilepsy Society (AES) announces that Brian Litt, M.D., professor of neurology, neurosurgery and bioengineering at the University of Pennsylvania, is being honored with the AES Research Recognition Award for Clinical Science on December 7, 2015, at the Society's 69th annual meeting in Philadelphia.
Litt is a pioneer in the emerging field of neuroengineering and is praised for his research focusing on hardware development, machine learning and high-speed computing for implantable devices. He is also well known for his laboratory work translating basic science into new diagnostic and therapeutic technologies.
"Dr. Litt's steady, prominent scientific and innovative contributions are putting exciting new knowledge and therapies for epilepsy within our reach," says Marc A. Dichter, M.D., Ph.D., professor of neurology and pharmacology at the University of Pennsylvania. "Perhaps most importantly, Dr. Litt has established a new field, translational neuroengineering, bringing together neuroengineering science and technology to directly help patients, and delivering new models of training and research careers to our field."
Litt received an A.B. in Engineering and Applied Science from Harvard University, and his doctorate from Johns Hopkins University School of Medicine. He did a postdoctoral fellowship at the Hopkins Applied Physics Laboratory and has held faculty appointments at Johns Hopkins, Emory University and Georgia Institute of Technology prior to Penn.
His honors and awards include Dana and Klingerstein Foundation Fellowships in Neuroscience, a Whitaker Foundation Fellowship in Bioengineering, the American Academy of Neurology's Dreifuss-Penry Award for epilepsy research, a NARSAD Award from the Brain and Behavior Research Foundation, and others. He is the 2013 winner of Penn's Luigi Mastroianni Clinical Innovator Award.
The $10,000 Research Recognition Awards are given annually to active scientists and clinicians working in all aspects of epilepsy research. The awards are recognize a distinguished history of research that holds promise for improving our understanding and treatment of epilepsy.
The potential to optimize laboratory testing and operations with automation and AI