جست‌وجوی استاد و پژوهشگر

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.

• High-Performance Integrated Circuit Design
• Artificial Intelligence Accelerators
• Digital Signal Processing Chips
• +۳ مورد دیگر

Dr. Fengwei An is an Associate Professor at the Shenzhen-Hong Kong Institute of Microelectronics , Southern University of Science and Technology (SUSTech). He earned his Ph.D. in Engineering from Hiroshima University (2013) , following a Master's (2010) and Bachelor's (2006) from Qingdao University of Science and Technology. Current Role : 2025-Present - Associate Dean and Associate Professor, SUSTech Shenzhen-Hong Kong Institute of Microelectronics Prior Academic Roles : 2017-2018 - Associate Professor, Hiroshima University; 2013-2017 - Assistant Professor, Hiroshima University Industry Experience : 2018-2019 - Chief Engineer, Panasonic Semiconductor Co., Ltd., Japan Research Interests focus on low-power edge artificial intelligence chip design for computer vision, including: Ultra-large-scale digital integrated circuit design System-on-Chip (SoC) integration Image processing and recognition Machine learning hardware Autonomous driving applications High-speed motion tracking systems Publications include over 80 top-tier journal/conference papers (e.g., TCAS-I/II, ESSCIRC, APCCAS) on AI accelerators, stereo vision processors, and sensor interfaces, with 15 recent articles highlighting advancements in stereo matching, video denoising, and reconfigurable coprocessors. Scientific Awards : 2023 - SUSTech Outstanding Teaching Award 2022 - APCCAS Best Paper Nomination 2022 - PrimeAsia Bronze Leaf Award 2020 - Wu Wenjun Artificial Intelligence Science and Technology Award (Second Prize) Patents : 9 Chinese and 3 Japanese inventions in AI chip design, stereo matching systems, and sensor interfaces.

• 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.

• Embedded Systems Design
• Low-Power Design
• VLSI Architecture for Image Processing
• +۴ مورد دیگر

Pasquale Corsonello is a Professor of Electronics at the Department of Informatics, Modeling, Electronics and System Engineering (DIMES) , University of Calabria. He has held academic positions at the University of Reggio Calabria and the University of Rochester (Adjunct Associate Professor). His career spans over three decades in digital electronics, VLSI design, and low-power systems. Education: Master's in Electronic Engineering, University of Naples “Federico II” (1988) Key Roles: Editor-in-Chief (Journal of Low Power Electronics), Senior Area Editor (IEEE Transactions on Circuits and Systems II), Steering Committee Member (IEEE Transactions on VLSI Systems) Research interests include: Embedded systems and low-power design for IoT VLSI architectures for image processing and neural networks FPGA-based accelerators for real-time applications Quantum-dot cellular automata (QCA) circuits His recent publications focus on energy-efficient FPGA implementations, approximate computing for imaging, and QCA-based arithmetic circuits. He has co-authored over 180 technical articles and holds three patents. Awards : BEST ASSOCIATE EDITOR IEEE CASS AWARD (2016) GOLDEN LEAF Certificate (PRIME 2019) Multiple BEST PAPER AWARDS at ICECS, CENICS, and PRIME Top 25 Downloaded Articles (IEEE Transactions on VLSI Systems) Leadership : Coordinated PhD programs in Information and Communication Technologies Directed research units in projects exceeding €8M in funding Member of editorial boards for IEEE Transactions and Electronics journal He leads the Nanoelectronics and Microsystems research group , which integrates material characterization, IC design, and system-level electronics for applications in power systems and photovoltaics.

• optimization
• non-classical architectures
• FPGAs
• +۱ مورد دیگر

Dr. Sándor Roland Major is an Assistant Professor at the University of Debrecen , Faculty of Informatics, Department of Information Technology. His office is located at room I129 on the 1st floor of the Faculty of Informatics building at 4028 Debrecen, Kassai Street 26., Hungary. Email: major.sandor@inf.unideb.hu Research Interests Optimization Non-classical architectures FPGAs (Field-Programmable Gate Arrays) Automata theory

• VLSI Design Automation
• Field-Programmable Gate Arrays
• Customizable Computing
• +۲ مورد دیگر

Jason Cong holds the Volgenau Chair for Engineering Excellence at UCLA's Samueli School of Engineering. With over 500 publications and leadership in 100+ research projects, he revolutionized FPGA design through polynomial-time logic mapping and High-Level Synthesis (HLS). His lab's AutoESL technology became the foundation of AMD/Xilinx's commercial tools. Education Peking University: Undergraduate Degree University of Illinois at Urbana-Champaign: MS in Computer Science University of Illinois at Urbana-Champaign: PhD in Computer Science Research Focus Cong pioneers domain-specific acceleration across deep learning, medical imaging, genomic sequencing, and data compression. His customizable computing architectures demonstrate orders-of-magnitude energy efficiency improvements over conventional CPUs. Quantum computing and scalable algorithm design constitute emerging research vectors. Honors and Impact ACM Breakthrough Award (2025) for FPGA automation IEEE Noyce Medal for semiconductor contributions Dual Fellow: ACM & IEEE National Academy of Engineering member Newton Award for EDA technical impact Commercialization Founded Aplus Design Automation (FPGA algorithms) and AutoESL (acquired by Xilinx/AMD). Current tools power industry-standard FPGA synthesis workflows enabling C/C++ programmability.

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.

Tawachi Nyasuluمشاهده پروفایل

پژوهشگر

• Radio Spectrum Management
• Dynamic Spectrum Access
• Spectrum Sharing
• +۷ مورد دیگر

Tawachi Nyasulu is a Research Associate in the StrathSDR laboratory within the Department of Electronic and Electrical Engineering at the University of Strathclyde, United Kingdom. He holds a PhD in Electronic and Electrical Engineering from the same institution, awarded in 2022, and has a strong background in spectrum research and wireless communications. His educational background includes: PhD in Electronic and Electrical Engineering, University of Strathclyde (2016–2022) MSc (Eng) in Digital Communications Networks, University of Leeds (2014–2015) BSc in Electrical Engineering, University of Malawi - Polytechnic (1998–2003) His research focuses on efficient radio spectrum management , dynamic spectrum access , spectrum sharing , and heterogeneous wireless coexistence , with an emphasis on modeling techniques such as hypergraph theory. His work aims to improve wireless connectivity, especially in rural and developing regions, leveraging technologies like TV white space. The most recent publications reflect a consistent trend in applying advanced mathematical models to real-world spectrum challenges. His work bridges theoretical modeling with practical implementation in software-defined radio and policy analysis, particularly in the context of global connectivity and sustainable development. His scientific recognitions include: Fellowship of the Higher Education Academy (FHEA) Postgraduate Certificate in Learning and Teaching in Higher Education Nyasulu has served as a Teaching Assistant since 2016 on the Digital Electronics course at Strathclyde and has delivered international teaching at Shanghai University of Electric Power on Computer Architecture. He is completing the Strathclyde Supervisor Development Programme, which will allow him to co-supervise PhD students. He has contributed to major research projects such as the £12 million TUDOR project, where he led the spectrum sensing workstream, and has been involved in initiatives focused on rural connectivity and 5G innovation. His research aligns with UN Sustainable Development Goals, particularly through technology for development and education. He is an active member of the StrathSDR laboratory, a leading research group in software-defined radio and future wireless networks, contributing to both national and international collaborative efforts in telecommunications research.

Durai Arun Pannir Selvamمشاهده پروفایل

پژوهشگر

• Signal Processing
• Image Processing
• Medical Image Processing
• +۷ مورد دیگر

Durai Arun Pannir Selvam is a Research Associate in the Department of Electronic & Electrical Engineering at the University of Strathclyde, Faculty of Engineering. He is based in the Neuromorphic Sensor Signal Processing Lab within the Centre for Signal and Image Processing, under the supervision of Dr. Gaetano. He also volunteers as a Student Mental Health First Aider (SMHFA) in the department. Education: Doctor of Engineering (PhD), The University of Edinburgh (Nov 2018 – Feb 2023). Research focused on enhancing image processing techniques for organ contour delineation in adaptive radiotherapy. Masters in Medical Electronics, with specialization in signal processing, image processing, and biomedical instrumentation. His research interests lie at the intersection of biomedical engineering and artificial intelligence, particularly in medical image processing , neuromorphic computing , and signal processing . He applies advanced computational methods to improve medical diagnostics and treatment planning, especially in radiotherapy. His work integrates AI models with hardware-efficient implementations using FPGAs and embedded systems. His recent publication explores quantisation-aware training in spiking neural networks, highlighting his focus on efficient, low-power AI models for real-world applications. The work investigates bi-modal accuracy distributions, contributing to the robustness and reliability of neuromorphic systems. He is actively engaged in academic service, having organized the StrathWide 2024 Researcher Conference and delivered an invited talk at a PGR Social and Networking Session, demonstrating his commitment to research community building. Professional Activities: Organiser, StrathWide 2024: The University of Strathclyde Researcher Conference (April 2024) Speaker, PGR Social and Networking Session (September 2024) He has prior experience as a Project Engineer, Senior Research Engineer, and Junior Research Engineer at CSIR National Aerospace Laboratories and CPEES & NHHID, Anna University, contributing to various signal and image processing projects. His lab work centers on the development and application of neuromorphic sensors and their signal processing pipelines.

• Computer Engineering
• Network-on-Chip (NoC)
• Fault-Tolerant Systems
• +۳ مورد دیگر

Heikki Kariniemi is a Doctoral Researcher at the Faculty of Engineering and Natural Sciences (Tampere University). His work focuses on advanced computer architecture and fault-tolerant systems. Tampere University Research Interests: Network-on-Chip (NoC) design Fault-tolerant communication protocols Multiprocessor Systems-on-Chip (MPSoC) Field-Programmable Gate Arrays (FPGA) Globally Asynchronous Locally Synchronous (GALS) architectures Publication Trends (2001-2010): 21 total outputs, including 18 conference papers and 1 dissertation. Key themes: reconfigurable multiprocessor systems, fat-tree network topologies, and FPGA-based fault-tolerant communication mechanisms. Academic Activities: Session chair at SoC 2009 and SoC 2010 symposia Peer reviewer for journals: IEEE Transactions on Circuits and Systems, IEEE Transactions on Electronic Publishing Referee for conference articles at NORCHIP 2009

Oriod Maloمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Electronic Engineering
• +۳ مورد دیگر

Oriod Malo is a Lecturer at the Faculty of Computer Science and IT , University of Metropolitan Tirana, Albania. He is currently pursuing a PhD in Artificial Intelligence and contributes to technical development through open-source projects. Lecturer in Computer Architectures PhD Candidate in AI Education BSc in Electronic and Telecommunication Engineering, University of Bologna (2019) MSc in Electronic Engineering, University of Bologna (2022) Research Interests His research focuses on creating mathematical models using MATLAB and Python (including AI models) and designing electronic systems with Field-Programmable Gate Arrays (FPGA). His work bridges theoretical modeling with practical implementation in hardware-software co-design. Technical Contributions Through his GitHub repositories, Oriod has developed projects such as: DE10_Lite_SONAR : FPGA-based SONAR mini-project using HC-SR04 ultrasonic sensors and VGA display Spartan3ANDevelopmentBoard : Xilinx Spartan-3AN FPGA development tkinterCalculator : Python GUI calculator with symbolic math capabilities

Bill Ashmanskasمشاهده پروفایل

مدرس ارشد

• Instrumentation and readout electronics
• FPGA-based digital electronics
• Positron Emission Tomography (PET)
• +۳ مورد دیگر

Bill Ashmanskas is a Senior Lecturer in the Department of Physics and Astronomy at the University of Pennsylvania's School of Arts & Sciences. His roles include teaching undergraduate physics courses and developing curriculum, alongside research in instrumentation, FPGA-based electronics, and medical imaging technologies. He is affiliated with both the Physics department’s HEP Instrumentation Group and the Radiology department’s Physics and Instrumentation Group. Education includes a Ph.D. from UC Berkeley (1998) and an A.B. from Harvard University (1992). His research focuses on readout electronics for High Energy Physics and Positron Emission Tomography (PET), with notable contributions to waveform-sampling DAQ systems and ASIC testing for HL-LHC upgrades. Key research interests span instrumentation design, medical imaging innovations, and HEP detector technologies. Recent publications emphasize PET-DBT hybrid systems and radiation-tolerant electronics. Awards include the 2020 Provost’s Teaching Excellence Award and a 2005 PECASE for early-career scientific achievement. Grants/Advising: Active in CDF and ATLAS collaborations, with extensive contributions to Fermilab experiments and Penn’s HEP instrumentation projects. Labs/Teams: HEP Instrumentation Group (Physics), Radiology Physics Group (Penn Medicine).

Mohamed-Yahia Dabbaghمشاهده پروفایل

دانشیار

• Digital Signal Processing
• Image Processing
• Video Processing
• +۶ مورد دیگر

Mohamed-Yahia Dabbagh is an Associate Professor, Teaching Stream in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds a PhD from North Carolina State University (1989), an MSE from the University of Michigan (1981), and a BSE from the University of Aleppo (1976). His research focuses on digital signal processing, image/video processing, and VLSI multiprocessor implementation of algorithms for communication systems and computer vision. He has developed architectures for digital filters and explored video motion estimation, segmentation, and pattern recognition. Dr. Dabbagh has authored numerous articles in IEEE and other venues, including work on wireless sensor anomaly detection, smartphone application monitoring, and FPGA-based digital filter implementations. His teaching includes courses such as Signals and Systems (ECE 207), Linear Circuits (ECE 140), and Probability and Random Processes (ECE 316). His research has spanned VLSI environments, Bayesian classification for video processing, and real-time signal processing techniques. Notable contributions include multiprocessor filter implementations and adaptive motion estimation algorithms. Dr. Dabbagh is a Professional Engineer (PEng) registered in Ontario and has contributed to technical reports on imaging systems and geographic information systems during his tenure at Kuwait-based institutions.