Behnaam Aazhang received his B.S. (with highest honors), M.S., and Ph.D. degrees in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign in 1981, 1983, and 1986, respectively. From 1981 to 1985, he was a Research Assistant in the Coordinated Science Laboratory, University of Illinois. In August 1985, he joined the faculty of Rice University, Houston, Texas, where he is now the J.S. Abercrombie Professor in the Department of Electrical and Computer Engineering Professor and Director of Rice’s Neuroengineering Initiative. From 2006 till 2014, he held an Academy of Finland Distinguished Visiting Professorship appointment (FiDiPro) at the University of Oulu, Oulu, Finland. Dr. Aazhang is a Fellow of IEEE and AAAS, a distinguished lecturer of IEEE Communication Society. He received an Honorary Doctorate degree from the University of Oulu, Finland (the highest honor that the university can bestow) in 2017. He is also the recipient of the IEEE ComSoc CTTC Outstanding Service Award “For innovative leadership that elevated the success of the Communication Theory Workshop” in 2016 and Outstanding Technical Achievement Award “For consistent, fundamental contributions to multiuser communication theory for wireless networks” in 2017. He is a recipient of 2004 IEEE Communication Society’s Stephen O. Rice best paper award for a paper with A. Sendonaris and E. Erkip. In addition, Sendonaris, Erkip, and Aazhang received IEEE Communication Society’s 2013 Advances in Communication Award for the same paper. He has been listed in the Thomson- ISI Highly Cited Researchers and has been keynote and plenary speaker of several conferences.
His research interests are signal processing, information theory, and their applications to engineering with focus areas in (i) understanding neuronal circuits connectivity and the impact of learning on connectivity (ii) developing minimally invasive and non-invasive real-time closed- loop stimulation of neuronal systems to mitigate disorders such as epilepsy, Parkinson, depression, and obesity, (iii) building microelectronics with data analysis techniques to develop a fine-grained recording and modulation system to remediate language disorders, (iv) developing a patient-specific multisite wireless monitoring and pacing system with temporal and spatial precision to restore the healthy function of a diseased heart.
Can data analytics predict and prevent the onset of seizures in epileptic patients
A fundamental research objective in neuro-engineering is to understand the ways in which functionalities of the brain emerge from the organization of neurons into highly connected circuits. This goal is one of the most critical scientific challenges in medicine of our generation. It is also critical in our understanding of how these functionalities are disrupted because of trauma and diseases like depression, Alzheimer’s, or Epilepsy.
In this presentation, I will discuss how signal processing techniques and graph- and information-theoretic tools can unravel brain’s circuit connection that underlie the onset of a seizure in epileptic patients. These tools can also provide features to predict the onset and possibly prevent seizures.