معرفی
Ediz ŞAYKOL is an Assistant Professor and Department Head at Beykent University's Faculty of Engineering and Architecture, Department of Computer Engineering. He also served as Vice Dean from 2012-2015. Prior to his academic career, he worked as a Senior Software Engineer at HAVELSAN A.Ş. from 2004-2010.
His educational background includes a Doctorate (2001-2009), Master's degree (1999-2001), and Bachelor's degree (1995-1999), all from İhsan Doğramacı Bilkent University's Faculty of Engineering and Institute of Engineering and Science. His doctoral thesis focused on 'A scenario-based query processing framework for video surveillance'.
Professor ŞAYKOL's research spans computer vision, machine learning, and video database systems, with particular emphasis on surveillance applications, medical diagnostics using neural networks, and educational technologies for special needs populations. His work bridges theoretical computer science with practical applications across multiple domains including healthcare, security, education, and entertainment.
His publication portfolio shows a consistent trajectory from foundational work in video database management systems to contemporary applications of deep learning across diverse fields. The research demonstrates strong methodological continuity in content-based retrieval techniques while adapting to emerging technologies from early 2000s through present day.
- 2003 3. Best Paper Award, University, Türkiye
Professor ŞAYKOL has supervised over 50 master's and doctoral students, with thesis topics covering computer vision applications, machine learning implementations, and innovative computing solutions for accessibility challenges. His academic leadership extends to curriculum development in computer graphics, operating systems, and computer vision courses taught in both Turkish and English.
His laboratory work has focused on video processing systems, with applications in historical document analysis, security surveillance, and medical diagnostics. Current research directions include deep learning applications for behavioral analysis and specialized computing solutions for accessibility challenges.
