Dr. Theocharis Theocharides (male) holds a Ph.D. degree in Computer Science and Engineering from the Pennsylvania State University. He is currently an Assistant Professor at the Department of Electrical and Computer Engineering, at the University of Cyprus. His research focuses on the broad areas of intelli-gent embedded systems design, with emphasis on domain-specific architectures, evolvable and reconfigu-rable hardware, and design of reliable and low power embedded and application specific processors and circuits. Prior to joining the University of Cyprus, Theocharis has been a member of the Gigascale Systems Research Centre (www.gsrc.org) and a member of Penn State’s Embedded and Mobile Computing Research Centre. He directs the Embedded and Application-Specific System-on-Chip Lab at the KIOS Research Centre, which runs several projects related to embedded, mobile and reconfigurable systems, embedded computer vision, embedded pattern recognition and classification architectures, and intelligent system-level monitoring and dynamic reconfiguration for performance, energy and reliability of Systems-on-Chip. He has authored/co-authored more than 70 papers in internationally acclaimed scientific journals and conferences. He is a senior member of the IEEE and the IEEE Computer Society, a member of the HiPEAC Network of Excellence, and currently serves on the editorial boards of the ACM Journal on Emerging Technologies in Computing Systems, IEEE Design and Test magazine, and on several Organizational and Technical Program Committee boards of various IEEE/ACM Conferences. Theocharis and his students have extensive and pioneering work on hardware acceleration for computer vision applications, including object detection, pattern recognition and depth estimation from stereoscopic video, yielding real-time, high frame-rates and low-power, suitable for emerging embedded vision systems, mobile robotics, and cyber-physical systems (CPS). His present work focuses on the development of hardware-friendly machine learning algorithms for big-data processing and pattern recognition in CPS, visual information extraction, distributed embedded com-puter vision applications, and vision-based robotic collaboration for various monitoring and visual infor-mation extraction algorithms.