John A. White, Ph.D.
Chair (BME) Professor (BME)
- Primary Appointment Professor and Chair, Biomedical Engineering
- Education Ph.D., Biomedical Engineering, Johns Hopkins University
B.S., Biomedical Engineering, Louisiana Tech University
- Honors and Awards 2019 Elected Fellow of the International Academy of Medical and Biological Engineering
2019 Elected President of the Biomedical Engineering Society
2014 Meeting Chair, Biomedical Engineering Society Fall Meeting
2011 Distinguished Alumnus Award, Dept. of BME, La. Tech U.
2006 Elected Fellow, Biomedical Engineering Society
2005 Elected Fellow, American Institute for Medical and Biological Engineering
2003-2008 Co-Director, Methods in Computational Neuroscience, Marine Biological Lab
- Areas of Interest Mechanisms of Episodic Memory, Pathophysiology of Epilepsy, Computational Neuroscience, Design of Real-Time Instrumentation, Imaging of Activity in Neurons and Astrocytes
- Research Areas Professor White’s laboratory uses engineering approaches to understand how information is processed in the brain, with the goal of exploiting these findings to improve the human condition. Ongoing and future research questions include the following:
Why is coherent electrical activity of the cortex necessary for mental processes like learning and memory?
What factors control this coherent activity, and how can such knowledge be applied to help patients with memory disorders and epilepsy?
How can recent advances in computing technology be exploited to develop electronic devices that detect brain dysfunction in real time and react to restore normal function in neurological patients
Can we take advantage of nonlinear optical techniques to improve methods of measuring and controlling neuronal activity in reduced preparations and the intact brain?
How do calcium and other second messengers interact to influence short-term and long-term plasticity in synapses and in neurons?
How do glial cells contribute to epilepsy, and how can that knowledge be used to generate new therapies?
How can the principles of brain function be adapted to build novel “smart” devices?