جستجوی استاد راهنمای دانشگاهی

Carl Sechenمشاهده پروفایل

استاد

• Digital Integrated Circuits
• Analog Integrated Circuits
• Computer-Aided Design (CAD)
• +۵ مورد دیگر

Carl Sechen is a Professor in the Electrical & Computer Engineering Department at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. His research focuses on design and computer-aided design (CAD) of digital/analog integrated circuits, with a strong emphasis on secure ICs and transistor-level programmable fabrics. He leads projects like the TRAP fabric, which achieves 10X logic density over traditional FPGAs while enabling secure hardware through IC redaction. Education: Ph.D. (1987, UC Berkeley), M.S. (1977, MIT), B.E.E. (1975, University of Minnesota). Awards include IEEE Fellow (2002), UTD Distinguished Teaching Award (2014), and multiple Semiconductor Research Corporation awards. His work bridges theoretical CAD advancements with practical hardware security solutions. Research Highlights: Secure IC design, transistor-level programmability, FPGA architecture, hardware security. Key Projects: TRAP fabric development, anti-reverse engineering techniques, low-power design methodologies. Awards: Over 20+ honors including best paper awards at PRIME (2017) and DATE (nominated 2017). Publications span journals like IEEE Transactions on CAD and conferences such as DATE, ISCAS, and VTS. Current work emphasizes secure hardware through obfuscation and programmable logic innovations.

• 3D Silicon Devices
• Digital Design
• Digital Electronics
• +۶ مورد دیگر

Bjørn B. Larsen is an Associate Professor in High-performance Digital Systems at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Electronic Systems. His academic responsibilities include teaching and advising across multiple engineering programs. He serves as part of the teacher's guild for the five-year integrated master's program in Electronic Systems Design and Innovation (ELSYS). Key roles include coordinating the TFE4205 Student-defined Development Project and acting as an academic advisor for ELSYS, the international master's in Electronic Systems Design, and the Erasmus Mundus master's in Embedded Computing Systems (EMES), collaborating with institutions in Kaiserslautern, Southampton, and Turin. He also advises incoming exchange students in Electronics. Larsen's technical competencies span 3D silicon devices, embedded systems, FPGA design, microelectronics, and VLSI design. His work emphasizes practical applications in high-performance digital systems and self-test methodologies. Though no specific grants or labs are detailed, his involvement in international programs highlights a focus on collaborative and applied research in electronics and embedded systems.

Christos Papachristouمشاهده پروفایل

استاد

• Embedded Systems Design
• Parallel Computer Architectures
• Quantum Computing
• +۴ مورد دیگر

Christos Papachristou, PhD is a Professor in the Department of Electrical, Computer, and Systems Engineering at the Case School of Engineering , Case Western Reserve University. His academic career spans over four decades since earning his PhD in Electrical Engineering & Computer Science from Johns Hopkins University in 1975. Prof. Papachristou's research focuses on Embedded Systems Design , Quantum Computing Architectures , Reconfigurable Systems/FPGAs , and Hardware Security . His work addresses critical challenges in fault-tolerant systems , secure system design , and high-level synthesis . Notable contributions include innovations in radiation-hardened SRAM designs , hardware trojan detection , and quantum computing infrastructure . Key Achievements: Recipient of the Albert Nelson Marquis Lifetime Achievement Award (2019) IEEE Best Paper Award for Cognitive Communications for Aerospace Applications (2019) Invited NATO Summer School Lecturer (2008) in Spain/UK and Cleveland His publications reflect expertise in circuit reliability , embedded system security , and quantum computing . Recent work emphasizes electromigration mitigation and reconfigurable architecture kernels . Prof. Papachristou collaborates extensively on projects funded by NSF, DoD, and industry partners. Teaching specialties include Parallel Computer Architectures , Configurable Devices , and Quantum Computing , reflecting his dual focus on theoretical innovation and practical implementation in advanced technologies.

Robert Stewartمشاهده پروفایل

استاد

• Digital Signal Processing
• Software Defined Radio
• FPGA Implementations
• +۷ مورد دیگر

Robert Stewart is a Professor in the Department of Electronic and Electrical Engineering at the University of Strathclyde, where he leads the 20-member StrathSDR engineering team. His research focuses on software-defined radio (SDR), dynamic spectrum access, FPGA-based implementations, and next-generation 5G private networks. He has played a pivotal role in major UK 5G testbed projects such as 5GRuralFirst, 5G NewThinking, and 5GRailNext, with a strong emphasis on rural and underground rail connectivity. His expertise spans digital signal processing, shared spectrum systems, and RFSoC-based designs. He was a founding partner of the Scotland 5G Centre in 2019 and co-founded Steepest Ascent Ltd, later acquired by MathWorks. He previously held the Xilinx Professor of DSP and Digital Logic chair and served as Head of Department (2014–2017) and Director of the Institute for Sensors, Signals and Communications. His recent publications (2024–2025) highlight advancements in intelligent resource management for shared spectrum networks, FPGA-based beamforming, 5G transmitter design on RFSoC platforms, and deep learning for modulation classification. These works reflect a strong integration of machine learning, hardware acceleration, and next-generation wireless systems. UCLA Extension Distinguished Professor Award 2010 Award for Digital Inclusion (2019) Xilinx Professor of Signal Processing (2006–2013) Stewart has led numerous EPSRC and industry-funded research projects and actively collaborates with AMD, MathWorks, and Cisco. He supervises research students and contributes to datasets and open-source tools. He also delivers technical short courses for industry professionals on RFSoC and PYNQ platforms. He has led the StrathSDR team in developing innovative solutions for private 5G networks and spectrum sharing, contributing to both academic knowledge and industrial applications through the Scotland 5G Centre and Neutral Wireless Ltd.

• Reconfigurable Computing
• FPGA
• Hardware-Software Co-Design
• +۹ مورد دیگر

Sharatchandra Varma Bogaraju is a Lecturer in Electronic Engineering and Embedded Systems at Ulster University's School of Engineering. His expertise spans Reconfigurable Computing , FPGA , and Hardware Accelerators , with applications in bioinformatics, satellite imagery, and neural networks. Doctoral research focused on FPGA accelerators for bioinformatics at Indian Institute of Technology, Delhi Active in hardware-software co-design and digital hardware design Contributor to UN Sustainable Development Goals (Education, Academic Qualification) Recent research includes low-latency image analytics and embedded DNN classifiers for cardiac diseases, emphasizing energy efficiency and performance optimization. Collaborations range from Queens University Belfast to Indian Institute of Space Science and Technology. Key projects: IoT-Driven Cybersecurity Framework and Women in Electronics Bridge Program . His work has been cited 107 times (h-index 6), with 25 research outputs and 20 academic activities documented.

• Machine Learning
• Field-Programmable Gate Arrays (FPGA)
• Network Traffic Classification
• +۵ مورد دیگر

Prof. Dr. Oğuzhan ERDEM is a faculty member at Trakya University Faculty of Engineering , Department of Electrical and Electronics Engineering since 2023. He earned his PhD in Electrical and Electronics Engineering from Middle East Technical University in 2011 and served at various academic roles across 22 years, including Department Head since 2021. PhD: Middle East Technical University (2011) Visiting Scholar: University of Southern California (2010-2011) His research focuses on machine learning applications in biomedical diagnostics and FPGA-based network processing . Recent publications explore Parkinson's disease detection through keystroke analysis, cough sound diagnostics, and hardware-accelerated network traffic classification. Key article trends show: 2023-2025: Deep learning for medical diagnostics 2016-2020: Hardware-optimized network processing 2010-2015: FPGA-based IP lookup architectures Awards: Middle East Technical University 2011 Doctoral Thesis of the Year He has supervised 6 graduate theses and led 2 major projects including Early Detection of Parkinson's Disease Using Multimodal Signals (2021). Patent co-inventor in systolic array architectures.

• Computer Science
• Hardware Security
• Machine Learning
• +۷ مورد دیگر

Jack Miskelly is a Research Fellow at the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on advanced hardware security mechanisms, leveraging machine learning and approximate computing techniques to analyze and enhance the robustness of digital systems. Expertise: Machine Learning, FPGA Security, Physical Unclonable Functions (PUFs), Side-Channel Analysis Key Collaborations: Dr. C. Gu, Prof. M. O'Neill, Y. Hao, J. Moore Research Trends: His recent work emphasizes vulnerabilities in modern DRAM systems (Rowhammer attacks), deep learning-based side-channel attacks on PUFs, and energy-efficient FPGA security methodologies. Contact: Email J.Miskelly@qub.ac.uk for collaboration or inquiries.

Guillaume Ducمشاهده پروفایل

دانشیار

• Embedded Systems Security
• Hardware/Software Interaction
• Side-Channel Attacks
• +۳ مورد دیگر

Guillaume Duc is an Associate Professor (Maître de Conférences) at Télécom Paris , affiliated with the Information Processing and Communication Laboratory (LTCI) and the Department of Computer Science and Networks . His research focuses on embedded systems security, particularly hardware/software interaction, side-channel attacks, and resilient architectures. Education: PhD in Hardware, Software and Cryptographic Support for Secure Process Execution , École Nationale Supérieure des Télécommunications de Bretagne (2007) Master's (DEA) in CryptoPage – an architecture to run secure processes , Université de Rennes 1 (2004) Research Interests: His work spans embedded systems security , with a focus on: Hardware/Software Interaction: Exploring vulnerabilities and defenses at the intersection of hardware and software. Side-Channel Attacks: Investigating power analysis, electromagnetic attacks, and countermeasures, including organizing the DPA Contest . Resilient Architectures: Designing secure memory architectures, FPGA-based protections, and cloud-embedded system trustworthiness. Publications & Patents: He has published extensively in top-tier venues such as Journal of Cryptographic Engineering , ACSAC , and CARDIS , with recent works addressing AI-driven automotive security (2024) and system cost-optimization for security (2019). He holds multiple patents in non-intrusive fault detection and secure electronic component monitoring. Teaching & Leadership: Academic lead for the engineering program at Télécom Paris. Responsible for courses like INF107: From Logic Gates to Operating Systems and SE203: Microprocessor System Tools . Co-instructor for Rust programming modules in executive education. Labs & Teams: He leads research within the Autonomous Critical Embedded Systems (ACES) team at LTCI, collaborating on secure embedded systems for automotive and cloud applications.

• Computer Engineering
• Parallel Computing
• Field-Programmable Gate Arrays (FPGAs)
• +۵ مورد دیگر

Zuofu Cheng is a Teaching Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His research focuses on parallel computing, FPGA-based machine learning acceleration, GPU optimization, and innovative engineering pedagogy. He has contributed to curriculum development in computer engineering education and advanced mesh optimization algorithms for heterogeneous computing systems. Research interests include: Hardware acceleration for AI/ML systems Parallel algorithm design for multi-core architectures Interactive engineering education methodologies Real-time acoustic simulation engines Publications highlight trends in FPGA/GPU optimization, IoT applications of machine learning, and computational thinking integration in undergraduate curricula. Over 75 citations reflect notable impact in hardware-accelerated computing domains. Active collaborations include work with IEEE conferences and HPC training initiatives.

Andrew Boutrosمشاهده پروفایل

استادیار

• Reconfigurable Computing
• Field-Programmable Gate Array (FPGA) Architecture
• Computer-Aided Design (CAD) Tools
• +۴ مورد دیگر

Andrew Boutros is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on reconfigurable computing architectures, FPGA design, and domain-specific acceleration for deep learning and datacenter workloads. He holds a PhD from the University of Toronto (2024) and has worked at Intel Labs and MangoBoost. Education: PhD, Electrical and Computer Engineering, University of Toronto, Canada (2024) MASc, Electrical and Computer Engineering, University of Toronto, Canada (2018) BSc, Electronics Engineering, German University in Cairo, Egypt (2016) Research Interests: Developing efficient FPGA architectures and CAD tools for reconfigurable hardware, domain-specific acceleration, and application/hardware co-design. Specific areas include 3D-stacked acceleration devices, graph neural network acceleration, and FPGA-based smart NICs for AI training. Publications: Over 30 papers in top venues like IEEE FPL, FCCM, and FPGA conferences, with 4 best paper awards. Recent work includes 3D-stacked architectures, graph neural network inference, and FPGA optimization for deep learning. Awards: Best Paper Award (FPT 2023) Best Paper Award (ICM 2021) Stamatis Vassiliadis Best Paper Award (FPL 2018) Advising/Grants: Currently accepting graduate students. Collaborations include 84 co-authors and industry partnerships with Intel and MangoBoost.

Suhaib Fahmyمشاهده پروفایل

استاد

• Reconfigurable computing
• Field Programmable Gate Arrays (FPGAs)
• Compute acceleration
• +۳ مورد دیگر

Suhaib Fahmy is a Professor of Computer Science at KAUST, having previously held the position of Professor in the School of Engineering at the University of Warwick. He leads the Adaptive Reconfigurable Computing Lab and was previously the head of the Connected Systems Research Group (2016–2020) and a Turing Fellow at The Alan Turing Institute (2017–2021). He earned a First Class Honours MEng in Information Systems Engineering (2003) and a PhD in Electrical and Electronic Engineering (2008) from Imperial College London. His career includes postdoctoral research at Trinity College Dublin (2007–2009) and a role as Assistant Professor at Nanyang Technological University (2009–2015). His research focuses on reconfigurable computing, FPGAs, compute acceleration, automotive systems, and adaptive radio systems. Notable contributions include work on automotive cybersecurity, FPGA-based neural networks, and low-latency accelerator interfaces. He has received awards such as the IEEE High Performance Extreme Computing Conference Best Paper Award (2021) and ACM Transactions Best Paper Award (2019). Dr. Fahmy has supervised numerous students, including PhD candidates focusing on FPGA acceleration of HPC applications, edge ML, and automotive networks. His teams have pioneered frameworks like NAIL for FPGA offloading and developed security solutions for automotive E/E architectures. He actively contributes to conferences and holds senior memberships in IEEE and ACM.

Sameh Abdelazimمشاهده پروفایل

دانشیار

• Electrical Engineering
• Remote Sensing
• Atmospheric Sensing
• +۹ مورد دیگر

Sameh Abdelazim is an Associate Professor in the Department of Electrical Engineering at the Gildart Haase School of Computer Sciences and Engineering, Fairleigh Dickinson University. He teaches a range of core electrical engineering courses including Circuits, Electronics, Control Systems, and Microprocessor Design. His research focuses on remote sensing of the atmosphere , particularly using eye-safe All-Fiber Coherent Doppler Lidar for wind sensing applications. He also specializes in Field Programmable Gate Array (FPGA) programming and data acquisition systems , integrating hardware and software for real-time signal processing and control. Before joining FDU, Dr. Abdelazim worked as a developer and engineer at IBM, where he contributed to chip design and signal integrity for server machines. He completed his PhD in Electrical Engineering at The Graduate Center of The City University of New York, conducting research at the Remote Sensing Laboratory at City College. During that time, he also served as an adjunct lecturer across CUNY institutions. PhD, Electrical Engineering (2012), The Graduate Center of The City University of New York MPhil in Engineering (2011), The Graduate Center of The City University of New York MS, Electrical Engineering (2009), The City College of The City University of New York BS, Electrical Engineering (2001), The City College of The City University of New York Dr. Abdelazim has no listed scientific awards or publications in the provided text. There is no mention of graduate students he may have advised. He is not described as part-time, retired, or former staff, indicating an active full-time faculty role.

• Control Systems
• Automatic Control
• Embedded Systems
• +۳ مورد دیگر

Benoît Boivin serves as an Associate Professor in the Department of Automatic Control and Systems at the School of Engineering, University of Poitiers. He is an active member of the LIAS laboratory (Laboratory of Informatics and Automatic Control Systems), operating across dual sites at ENSIP in Poitiers and ISAE-ENSMA in Chasseneuil, where he contributes to the Automatic Control Team alongside Data Engineering and Real Time research groups. His research spans Control Systems , Embedded Hardware Implementation , and Industrial Sensor Applications , with specialization in multivariable PID control, FPGA-based real-time systems, and gyroscope stabilization. Key methodologies include output feedback stabilization under structural constraints and LMI optimization techniques for robust control solutions in industrial environments. Analysis of his 2002-2006 publications reveals consistent focus on bridging theoretical control design with hardware deployment, particularly for vibrating gyroscopes and asynchronous motors. His work demonstrates strong integration of Field-Programmable Gate Arrays (FPGAs) for real-time control, emphasizing industrial applicability in sensor systems and motor drives while addressing vibration challenges in precision instrumentation. Benoît Boivin operates within LIAS's collaborative framework, leveraging shared infrastructure across its three technical teams. The laboratory's dual-campus structure facilitates cross-disciplinary work between Poitiers' urban engineering hub and ISAE-ENSMA's aerospace-focused campus, supporting hardware prototyping and industrial partnership development in control system applications.

• Digital Signal Processing (DSP)
• Field-Programmable Gate Arrays (FPGA)
• Machine Learning Hardware Acceleration
• +۱۳ مورد دیگر

Gian Carlo Cardarilli is a researcher specializing in digital hardware design and machine learning acceleration. His work focuses on FPGA implementations, Residue Number System (RNS) architectures, and reconfigurable computing for applications in wireless communication, edge AI, and fault-tolerant systems. Key collaborations with institutions like IEEE and ACM through publications. Active in translating theoretical algorithms into practical hardware solutions for real-time systems. Research interests include: Optimizing deep learning models for heterogeneous platforms. Developing radiation-hardened memory systems. Creating energy-efficient signal processing architectures. Advancing reconfigurable functional units for embedded processors. His article analyses span fields like Quantum Cellular Automata , Variable Fractional Delay Filters , and RNS-Based Position Estimation , reflecting a trend toward adaptive, low-power, and domain-specific hardware.

Ana Isabel Silva Martinsمشاهده پروفایل

پژوهشگر

• CMB
• Gravitational Waves
• Machine Learning
• +۱ مورد دیگر

Ana Isabel Silva Martins is a Doctoral Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences , affiliated with the Department of Astrophysics. Her research focuses on cosmology, gravitational waves, and machine learning applications in high-performance computing. Education: MSc in Experimental Physics (2022-2024), Utrecht University BSc in Engineering Physics (2019-2022), Instituto Superior Técnico, University of Lisbon Research Interests: She explores early detection mechanisms for gravitational wave signals from binary neutron star coalescence, leveraging convolutional neural networks (CNNs) and field-programmable gate arrays (FPGAs). Her work bridges astrophysics, machine learning, and computational hardware optimization. Projects & Groups: Active in the CMB&CO group , Cosmoglobe , and CosmoglobeHD . Collaborates on cosmology and extragalactic astronomy research.