Csaba Rekeczky is an expert in CNN Array Computer based algorithm and system level architecture design for various application areas ranging from medical imaging to surveillance/tracking. He received the M.S. degree in electrical engineering from the Technical University of Budapest in 1993. After graduation he joined the Neuromorphic Information Technology interdisciplinary postgraduate program and continued his studies at the Analogical and Neural Computing Systems Laboratory of the Computer and Automation Institute of the Hungarian Academy of Sciences. In 1994 and 1995 he spent a year at the Tokushima University (Tokushima, Japan) as a visiting scholar working on cellular neural network projects related to medical image processing. In 1997 and 1998 he conducted research in nonlinear image processing and neuromorphic modeling of the vertebrate retina at the University of California at Berkeley (Berkeley, USA). He received the PhD degree in electrical engineering from the Budapest University of Technology and Economics in 1999. Recently, along with his co-authors, he has won the Best Paper Award for a contribution published in International Journal of Circuit Theory and Its Applications. In 2001 and 2002 he served as one of the associate editors for IEEE CAS–I.
Csaba Rekeczky has innovations in CNN algorithm design areas improving nonlinear diffusion and wave-type computing techniques and has significantly contributed to the design and implementation of novel active fovea vision systems combining both topographic and non-topographic computing. He has designed vision system architectures for multitarget tracking and discrimination and for UGV/UAV based surveillance/reconnaissance. He has also completed successful research investigations in computational neurobiology (CNN based retinal modeling) and in non-invasive medical diagnosis.