Hamed Tabkhi

Hamed Tabkhi serves as Associate Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte's William States Lee College of Engineering. He directs the Transformative Computer Systems and Architecture Research (TeCSAR) laboratory, focusing on real-time edge computing solutions for community safety and smart infrastructure.

• University: University of North Carolina at Charlotte
• School: William States Lee College of Engineering
• Department: Electrical and Computer Engineering
• Office: EPIC 2162
• Contact: htabkhiv@uncc.edu | 704-687-0291

His research spans Real-time Edge Intelligence, Domain-Specific Computing, and Cyber-Physical Systems with emphasis on privacy-preserving AI for public safety. Core projects include AI for Highway Work Zone Safety (NSF-funded), Real-time Edge Intelligence for Smart Communities, and Scalable Reconfigurable Architecture for Deep Learning. His work integrates computer architecture innovations with community-driven applications in transportation safety, healthcare diagnostics, and retail security.

Analysis of recent publications (2023-2025) reveals strong focus on human-centric video analytics, with 60% of works addressing anomaly detection through pose estimation and transformer architectures. Significant contributions appear in medical imaging (OCT-SelfNet frameworks) and transportation systems (real-time bus prediction, highway safety). His research consistently bridges hardware acceleration with real-world deployment constraints.

• NSF SaTC: $2M grant for community safety systems
• NSF CPS: $500K grant for highway work zone safety
• Collaborations with Leidos, AWS, Xilinx, and community stakeholders

As TeCSAR director, he mentors graduate students in hardware-software co-design for edge AI systems, emphasizing FPGA acceleration and real-time processing. His lab maintains active GitHub repositories with open-source tools for edge computing. Current projects address predictive road maintenance, digital twins for power electronics, and AI-driven policing technologies developed through community co-creation processes.