He was born in Patras, Greece, in 1953. He received the B.Sc. degree in 1976 in Physics from Patras University and the M.Sc. degree in Telecommunications and Electronics from the University of Athens in 1981. A. Bezerianos entered the Department of Medical Physics in 1982 as a research assistant from which he received the Ph.D. degree in 1987. Since January 1998 he has been Associate Professor. He obtained his promotion as a Professor in January 2004.

He is member of:

• Union of Greek Physicists
• Hellenic Society of Biomedical Engineering
• IEEE, Society on Signal Processing and Medicine and Biology Society

2000/2001 Sabbatical at Johns Hopkins University From Sept 2000 to July 2001 Prof. Bezerianos visited in the sabbatical year the Biomedical Engineering Department of Johns Hopkins University. Member of the research group of Prof. N. Thakor he was involved in the project "Information Measures of Brain Injury".

Description: The overall goal of this project is to provide fundamental quantitative analysis of brain injury and recovery based on brain's electrical rhythms. Our central hypothesis is that brain injury, such as by ischemia from cardiac arrest, results in a reduction in the entropy of brain rhythm, and recovery is prognosticated by return of high entropy, high complexity rhythms.

Contribution: During his sabbatical Prof. Bezerianos is heading the Signal Processing Group, developing the mathematical formalism of entropy analysis and doing preliminary work on entropy analysis of EEG rhythms from patients.

Details: When dealing with brain dynamics, the classical signal processing of brain rhythms must be substituted by information processing approaches. The most innovative aspect is the theoretical attack on brain rhythm analysis from information theory and dealing with the fundamental principles of complexity, entropy and information flow. We hypothesize that brain injury directly affects the underlying complexity and information flow in brain. We predict that a good brain function would result in a higher entropy and complexity state and high levels of mutual information flow in the cellular structures in the cortical recordings. Our studies will provide mathematical signature of brain rhythm at various phases of injury and recovery. Not only will our research elucidate mechanisms, but will also provide guidance in the diagnosis of brain injury.