جست‌وجوی استاد و پژوهشگر

Burak Acarمشاهده پروفایل

پژوهشگر

• Random Number Generation
• Hardware Security
• Cryptography
• +۳ مورد دیگر

Dr. Burak Acar is a Research Assistant at Istanbul Technical University's Department of Electronics and Communication Engineering within the College of Engineering. His work focuses on hardware security, random number generation, and cryptographic circuit design. Specializes in FPGA-based security systems Expertise in transient effect analysis for cryptographic applications Active participant in IEEE symposia and technical committees Research interests center around hardware security and digital circuit design, with specific emphasis on: Random number generation techniques Cryptanalysis of oscillator-based systems Transient effect utilization in security applications Reconfigurable hardware implementations Digital circuit resilience against attacks Irregular sampling methodologies His research outputs from 2018-2020 demonstrate consistent contributions to IEEE conferences and journals, particularly in the areas of hardware cryptography and digital circuit security.

Mirjana Stojilovicمشاهده پروفایل

پژوهشگر

• Field-Programmable Technology
• Electronic Design Automation (EDA)
• Hardware Security
• +۳ مورد دیگر

Mirjana Stojilovic is a researcher at EPFL's School of Computer and Communication Sciences and the Parallel Systems Architecture Laboratory (PARSA). She obtained her PhD in 2013 from the School of Electrical Engineering in Belgrade and has worked on projects like STRUCTURES (EU FP7) and ADHeS (armasuisse). Her research spans field-programmable technology, electronic design automation, and hardware security, with a focus on side-channel attacks and countermeasures in reconfigurable systems. Education: PhD in Electrical Engineering (2013), School of Electrical Engineering, Belgrade Research Areas: FPGA security, power analysis attacks, hardware acceleration, EDA optimization Her recent publications analyze vulnerabilities in shared cloud FPGAs, side-channel leakage, and routing architectures. She has supervised numerous PhD and MSc students and received awards for teaching and research. She also organizes workshops and serves on program committees for conferences like FPGA, DATE, and FPL. Scientific Awards: 2023 Best paper award nomination (DDECS) 2020 OMEGA Student Award (for supervised project) 2016 Young scientist award (ICLP), Best paper (EMC Europe) 2015 Teaching Award (EPFL) 2011 Blažo Mirčevski Young author award Committees: Program member for DATE, FPGA, FPL, and associate editor for ACM TRETS and IEEE ESL She teaches courses such as Fundamentals of Digital Systems, Computer Architecture, and Information, Computation, Communication (ICC) at EPFL.

Dina G. Mahmoudمشاهده پروفایل

استادیار

• Heterogeneous Computing
• Hardware Security
• Fault Injection Attacks
• +۳ مورد دیگر

Dina G. Mahmoud is an Assistant Professor at the Department of Computer Science and Engineering at The American University in Cairo (AUC). She earned her Ph.D. in Computer and Communication Sciences from EPFL, Lausanne, Switzerland (2019-2024), where she was a CYD Fellow and collaborated with Dr. Mirjana Stojilović and Dr. Vincent Lenders. Her academic activities include teaching Digital Design, Computer Organization, and Applied Data Structures at AUC. Ph.D. (2019-2024): School of Computer and Communication Sciences, EPFL B.Sc. (2014-2019): Electronics and Communications Engineering with minor in Mathematics, AUC Her research focuses on heterogeneous computing systems , emphasizing security and reliability at the hardware and electrical levels . She investigates fault injection attacks in FPGA systems, particularly in multitenant cloud environments, and has demonstrated the first FPGA-to-CPU fault-injection exploit. Recent publications highlight trends in FPGA security , including power-wasting attacks, hardware Trojans, undervolting exploits, and fault tolerance mechanisms. Her work bridges hardware-software co-design , cloud security , and reconfigurable computing . CYD Fellow (first doctoral recipient) Google Generation Scholarship (2022, EMEA) IC Doctoral Fellowship at EPFL She has served as Head/Teaching Assistant at EPFL for courses like Computer Architecture and Information, Calcul, Communication, and as Head Undergraduate Teaching Assistant at AUC for Digital Logic Design. She contributes to the technical program committee of IEEE Industrial Electronics Society’s ETFA conference.

• Embedded Systems
• Internet of Things
• Cyber-Physical Systems
• +۱۷ مورد دیگر

Kasim Sinan Yildirim is an Associate Professor in the Department of Information Engineering and Computer Science at the University of Trento, where he conducts research at the intersection of embedded systems, Internet of Things (IoT), and wireless communication technologies. His work focuses on developing innovative hardware and software solutions for resource-constrained and energy-limited environments. His research interests include: Hardware and software design for batteryless and intermittently powered embedded systems Energy harvesting and transient computing Wireless sensor networks and self-organizing networks Backscatter and visible light communication Edge learning and inference Distributed algorithms and real-time computing The absence of published articles in the provided text prevents analysis of publication trends. However, his research direction emphasizes sustainable, low-power computing paradigms essential for next-generation IoT deployments. There are no listed scientific awards in the provided information. Dr. Yildirim advises students and contributes to academic training, though specific advisees are not listed. There is no mention of external grants or funded projects in the provided text. He is involved in research related to advanced embedded and cyber-physical systems, particularly focusing on novel computing models for batteryless devices and sustainable IoT infrastructures.

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.

• 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.

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.

• 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.

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.

• 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.

• 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.