Gurel Chosen for NextProf Nexus Workshop
Nil Gurel has been selected to participate in the 2019 NextProf Nexus Workshop, sponsored by the University of Michigan, the University of California at Berkeley, and Georgia Tech. Gurel is a Ph.D. student in the Georgia Tech School of Electrical and Computer Engineering (ECE).
The NextProf Nexus Workshop is a three-day program that is part of a nationwide effort to strengthen and diversify the next generation of academic leaders in engineering. This preeminent event is designed to give participants the opportunity to explore and prepare for a faculty position in academia. The event will be held October 2-5, 2019 on the Georgia Tech campus.
Gurel joined the Georgia Tech School of ECE in 2016, where she has been a member of the Inan Research Lab for the last two years. Her advisor is ECE Associate Professor Omer Inan. Gurel completed her M.S. degree in ECE at the University of Maryland at College Park in 2016, and she earned her B.S. degree in Electrical and Electronics Engineering at Bogazici University (Istanbul, Turkey) in 2014.
Gurel's Ph.D. research focuses on physiological modulation, monitoring, and active sensing. She works on noninvasive vagus nerve stimulation to artificially modulate the brain function without requiring surgery. This technique could be used to possibly treat autonomic nervous system or mental disorders, such as post-traumatic stress disorder (PTSD). In particular, Gurel works on biomedical instrumentation, signal processing, and machine learning for mood and performance improvement and for understanding real-time noninvasive biomarkers to close the loop for treatment optimization and control.
- Nil Gurel
- graduate students
- School of Electrical and Computer Engineering
- Georgia Tech
- Inan Research Lab
- 2019 NextProf Nexus Workshop
- Omer Inan
- physiological modulation
- active sensing
- noninvasive vagus nerve stimulation
- autonomic nervous system disorders
- mental disorders
- post-traumatic stress disorder
- biomedical instrumentation
- signal processing
- machine learning
- mood improvement
- performance improvement
- real-time noninvasive biomarkers
- treatment optimization and control