Reinforcement Learning for Brain Machine Interfaces

Jihye Bae PhD

Oct 17, 2019|12:30 PM – 1:30 PM

130 University Health Services Building

Bae j

There have been promising advances in brain machine interfaces. However, many challenges still remain before this technology can become practical. In this talk, we will discuss some of the main issues along with possible approaches to overcome them. In particular, methods to translate neural signals to control external devices using reinforcement learning will be introduced.

 

Pictures from the presentation

Dr. Bae introducing her research

Audience listening to Dr. Bae

Jihye Bae received her B.E. degree in Electrical Engineering and Computer Science from Kyungpook National University, South Korea, in 2007 and her M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Florida, USA, in 2009 and 2013, respectively. During her PhD, she worked at the Computational Neuro Engineering Laboratory under the supervision of Dr. Jose Principe. From 2013 to 2015, she was a Postdoctoral Associate in the Department of Biomedical Engineering at Florida International University working in Dr. Jorge Riera’s Neuronal Mass Dynamics Laboratory.  From 2015 to 2016, she was appointed as a Postdoctoral Associate in the Miami Project to Cure Paralysis at the University of Miami, where she worked with Dr. Monica Perez. From 2018 to 2019, she was a Postdoctoral Associate in Dr. Zachary Danziger’s Applied Neural Interfaces Laboratory in the Department of Biomedical Engineering at Florida International University. She joined in Electrical and Computer Engineering Department at the University of Kentucky as an assistant professor starting from 2019 Fall.