Nikolaos Constantine Kavvadias was born in 1977 in Lamia, located in the Fthiotis prefecture of Greece. Following the Panhellenic university admission exams of 1995, he entered the Physics Department of the Aristotle University of Thessaloniki (AUTH) ranking 8th among 220 successful applicants from where he graduated in October 1999 with an overall grade of 8.22/10. In October 1999, he gave the corresponding examination and achieved the highest entry score (ranked 1st) for enrolling in the Electronic Physics graduate program at the Department of Physics, AUTH. He graduated in October 2002 with the [login to view URL]. degree and an overall grade of 9.41/10. From March 2003 to May 2008, he worked towards completing his Ph.D. thesis entitled "Development of an application-specific processor design methodology" within the Electronics and Computer Laboratory of the Physics Department, AUTH. Following his obligatory military service in the Greek army, he worked at the Department of Computer Science and Technology of the University of Peloponnese from September 2008 to June 2012 as an Adjunct Lecturer teaching the following courses: Compilers I, Computer Architecture II, Hardware Description Languages (Verilog HDL), Digital Circuit Design, Advanced Topics in Compilers (postgraduate course for Theoretical Infomatics [login to view URL]. programme), Compilers II, and Hardware Description Languages (VHDL). To date, Dr. Kavvadias has attended a significant number of seminars related to digital circuit design techniques. Further, he has participated as a researcher in five research programs (PENED'99-99ED501, PENED 2003-03ED730, FP5-IST-2000-30093 EASY, FP7-ICT-248821 ENOSYS, and FP7-ICT-287733 ALMA) in related disciplines. Dr. Kavvadias is a member of the ACM and the IEEE. Since January 2012, Dr. Kavvadias is the cofounding CEO of Ajax Compilers . His current research interests include high-level synthesis, application-specific processor design methodologies, hardware description languages, compilation for custom processors and energy consumption modeling for embedded processors.