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Prof. Baker Mohammad serves as Professor and Director of the System on Chip Lab in the Department of Computer and Information Engineering at Khalifa University. With over 15 years of industrial experience at Intel and Qualcomm designing microprocessors and DSP chips, he bridges academic research with real-world engineering challenges in high-performance computing and low-power systems. His educational background includes: Ph.D. in Electrical and Computer Engineering, University of Texas at Austin (2008) M.S. in Electrical and Computer Engineering, Arizona State University B.S. in Electrical Engineering, University of New Mexico Dr. Mohammad's research spans cutting-edge domains where VLSI design converges with AI acceleration and emerging memory technologies . His work pioneers Memristor applications in environmental sensing (radiation, vacuum, glucose) and neuromorphic computing, while advancing energy harvesting systems for wearable electronics. The integration of in-memory computing with security primitives represents a paradigm shift in hardware design, moving beyond traditional CMOS limitations. His publication trajectory reveals accelerating focus on self-powered neuromorphic systems and RRAM-based architectures, with recent work (2021-2023) emphasizing hardware-software co-design for edge AI. Over 75% of his recent publications involve cross-disciplinary collaborations spanning materials science, chemistry, and biomedical engineering. Notable scientific recognition includes: IEEE TVLSI Best Paper Award 2016 IEEE MWSCAS Myrill B. Reed Best Paper Award Qualcomm Qstar Award for Performance Leadership KUSTAR IP Excellence Award Multiple SRC Techon Best Session Papers As a dedicated mentor, he has supervised over 15 graduate students while securing competitive funding from Khalifa University, ADEK, Qualcomm, Tii, and UAE space agencies. His grant portfolio demonstrates exceptional translational impact, converting fundamental research in memristive devices into drone flight computers and medical sensors. Current projects integrate academic rigor with industrial deployment timelines. The System on Chip Lab operates as a multidisciplinary hub where semiconductor physicists collaborate with AI researchers to develop RISC-V-based secure processors and piezoelectric nanogenerator systems. Recent expansions include partnerships with Tii for aerospace applications and medical device startups for glucose monitoring technology.

• Very-Large-Scale Integration (VLSI)
• Hardware Accelerators for Artificial Intelligence
• Hardware Security
• +7 more

Dr. Sherif Moussa is a Professor and Dean at the Faculty of Engineering, Applied Science and Technology, Canadian University Dubai. He holds a PhD in Electrical and Computer Engineering from the University of Quebec and an MSc from the University of Waterloo, both in Canada. Before joining CUD in 2007, he served as a lecturer at Centennial College in Toronto. His research focuses on: Wireless Communication Computer Networks Machine Learning Digital Circuit Design His recent publications explore machine learning applications in cybersecurity, MIMO-OFDM systems, FPGA implementations, and routing protocols, reflecting a consistent emphasis on optimizing wireless and network technologies. Trends show increasing work in AI-driven solutions and intrusion detection since 2018. He received the 2015 CUD Research Excellence Award and founded the university's first robotics club. He actively contributes as a reviewer and technical committee member for international conferences.

• Wireless Communication
• Computer Networks
• Machine Learning
• +1 more

Professor Mahmoud Al Qutayri serves as Associate Provost for Academic Operations at Khalifa University and holds a faculty position in the Department of Computer and Information Engineering, College of Engineering. His work focuses on high-performance and energy-efficient electronic systems through the Khalifa University System-on-Chip Center and Center for Cyber-Physical Systems Research. Education : PhD in Electronic Engineering (University of Bath, 1992), MSc in Electronic Engineering (University of Manchester, 1987), BEng in Electrical Engineering (Concordia University, 1984) Research spans AI accelerators, wireless sensor networks, and IoT optimization. He pioneered mixed-signal circuit design and contributes to edge computing hardware architectures. Professional activities include editorial board service and organizing committees for conferences like GLOBECOM, ICIP, and ISSPA. Co-author of Digital Phase Lock Loops: Architectures and Applications and editor of Smart Home Systems , with multiple patents in embedded systems.

• Embedded Systems
• Computer Architecture
• In-Memory Computing
• +6 more

Professor Mahmoud Meribout is a faculty member at the Electrical Engineering Department of Khalifa University of Science & Technology, UAE. He holds a Ph.D. in Computer Engineering from the University of Technology of Compiegne, France, and has industry experience at NTT and NEC Japan, focusing on embedded systems and AI hardware. Education: Ph.D., Computer Engineering, University of Technology of Compiegne (France) M.Sc., Computer Engineering Research Interests: His work spans real-time imaging systems (THz, MPI, optical, electrical, and magnetic tomography), sensor systems, multiphase flow metering, and hardware accelerators/embedded systems for AI, machine learning, and machine vision. He is currently leading a project on a hybrid GPU-FPGA-based 3D Electrical Impedance Tomography system. Scientific Recognition: He received the NTT Best Award in 1998 for his contributions to parallel processor architecture design. Academic Supervision: He supervises M.Sc. students including Asma Najeeb , Mahfoudh Awadh Baobaid , Mohamed Tarek Tageldin Mohamed , and Juan Paul .

• Real-time Imaging Systems
• Sensor Systems and Instrumentation
• Hardware Accelerators
• +4 more