Speaker:  Dr. Babak Mahmoudi

Abstract:
The brain is the most complex information processing system that evolution has engineered. The orchestrated activity of billions of neurons lead to coordinated sensory, motor and cognitive functions which are the keys for survival in uncertain environments with limited resources. Neuropathological conditions, traumatic brain injuries and sensorimotor disabilities disrupt the natural flow of information within the nervous system. Over the past decade, neural interface systems have emerged as a promising technology to restore normal function in patients with neurological disorders by opening new information channels for the brain. Direct communication with the nervous system involves extracting information from neuronal activities (decoding), writing information into the nervous system (encoding), and/or modulating the neural states using neurophysiology techniques. Synergistic interaction with the brain is contingent upon developing hybrid in silico/biological systems that integrate the computational information processing into brain's natural neural computations. In this talk, Dr. Mahmoudi will discuss the design of synergistic neural interface systems using machine learning techniques.

Bio:
Dr. Babak Mahmoudi is an NIH NRSA postdoctoral fellow in the department of Neurosurgery at Emory University. He received his Ph.D. and masters degree in biomedical engineering from the University of Florida in 2010 and 2008, respectively. He also holds a masters and a bachelors degree in electrical engineering from the Iran University of Science and Technology and the University of Tehran, respectively. In 2004, Dr. Mahmoudi was invited to the Advanced Brain Signal Processing Laboratory, RIKEN, in Japan as a visiting scholar. He was a finalist in the student paper competition of the 31st IEEE Engineering in Medicine and Biology Conference and the recipient of the Howard Hughes Medical Institute Fellowship in 2009. His research on neural interface systems has led to more than 30 peer reviewed publications.