جست‌وجوی استاد و پژوهشگر

• Embedded Machine Learning
• FPGA Design
• Neural Networks
• +۴ مورد دیگر

Leo Buron, M.Sc., is a Researcher and doctoral student at the Intelligent Embedded Systems Lab, part of the School of Computer Science at the University of Duisburg-Essen. He holds a Master's degree in Electrical Engineering and Information Technology with a focus on embedded systems. University of Duisburg-Essen (Master's in Electrical Engineering and Information Technology) Hochschule Düsseldorf (Dual studies in Electrical Engineering with Siemens) His research focuses on optimizing deep neural networks for resource-constrained hardware like FPGAs, with applications in brain-computer interfaces (BCIs) and time series analysis. Key areas include spike sorting, feature extraction, clustering, and AI implementation on sensors/smart devices to improve data privacy. Recent publications highlight his work on quantized neural network training, FPGA-based AI hardware for BCIs, and memristor applications in spike sorting. These works span computer science, biomedical engineering, and electrical engineering disciplines. Leo contributes to knowledge transfer initiatives like the ZaKI.D project, aiming to democratize AI adoption for regional companies. He collaborates with researchers including Gregor Schiele and Andreas Erbslöh on embedded machine learning and adaptive systems.

• Computing-in-Memory
• Resistive RAM (RRAM) Technology
• Neuromorphic Computing
• +۷ مورد دیگر

Dr. Moritz Joseph serves as Professor and Chair of Software for Systems on Silicon at RWTH Aachen University's School of Electrical Engineering and Information Technology. His research group operates within the Institute for Communication Engineering (ICE), focusing on cutting-edge hardware architectures for next-generation computing systems. The chair maintains laboratory facilities in the ICT Cube 1 building at Kopernikusstr. 16 in Aachen, Germany. Professor Joseph's research spans Computing-in-Memory architectures , Resistive RAM technologies , and neuromorphic computing systems . His work addresses critical challenges in hardware acceleration for deep learning, with particular emphasis on reliability, security, and energy efficiency of novel memory-centric computing paradigms. His research bridges computer architecture, hardware security, and machine learning acceleration. Analysis of his recent publications reveals a strong focus on RRAM-based compute-in-memory systems, with increasing attention to security implications of thermal effects and side-channel attacks. His work demonstrates progression from fundamental memory characterization to system-level integration and security analysis, showing consistent innovation in memory-centric computing architectures over the past five years. Professor Joseph actively contributes to the development of simulation frameworks and evaluation methodologies for emerging memory technologies, as evidenced by his work on platforms like CIM-Explorer, Ratatoskr, and gem5 extensions. His research has significant implications for energy-efficient AI hardware and secure computing systems.

• Speech Recognition
• Signal Processing
• Machine Learning
• +۴ مورد دیگر

Dr. Michael Mason is a Research Fellow at the Queensland University of Technology (QUT), affiliated with the School of Computer Science . His work bridges advanced signal processing, machine learning, and automotive speech systems, focusing on noise-robust speech recognition and speaker verification frameworks. Education: PhD in Hybrid Coding of Speech and Audio Signals (QUT, 2001) Research Interests span speech recognition, acoustic engineering, machine learning, and human factors in automotive environments. His projects address challenges in in-car speech enhancement, voice activity detection, and dialect mismatch compensation. Key Trends in Publications highlight innovations in i-vector modeling , FPGA-based audio processing , and likelihood-maximizing frameworks . Collaborations with experts like Sridharan and Vogt underscore his role in advancing speaker verification systems. Technical Contributions include developing the QUT-NOISE-TIMIT corpus and pioneering FPGA implementations for real-time speech enhancement.

• Neuromorphic Engineering
• Edge AI
• Computer Architecture
• +۴ مورد دیگر

Dr. A. Yousefzadeh is an Assistant Professor in Edge AI at the University of Twente (joined February 2024), affiliated with the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) within the Department of Computer Architecture Design and Test for Embedded Systems. He holds a Ph.D. in Neuromorphic Engineering from IMSE (Instituto de Microelectrónica de Sevilla), where his thesis focused on bio-inspired vision processing. His research specializes in neuromorphic computing systems, with emphasis on: Designing ultra-low-power AI processors and event-based vision systems Developing hardware accelerators for spiking neural networks (SNNs) Edge AI deployment for sensor-based applications Hardware-software co-design for energy-efficient computing His publication trends (2015-2025) reveal core foci on neuromorphic processor architectures (e.g., SENECA, NeuronFlow), event-based vision processing, hardware-aware neural network optimization, and 3D integration techniques. Recent work explores activation sparsification in transformers and hybrid analog-digital neuromorphic systems. Prior to academia, he contributed to industry neuromorphic projects: Architected the NeuronFlow processor at GrAI Matter Labs (acquired by Snap) Led SENECA processor development at imec's Hardware Efficient AI group He currently leads research on next-generation edge AI processors at UT's Embedded Systems lab.

• Modeling of devices and components for engineering applications
• Modeling and analysis of dynamical systems and dynamical systems networks
• Design and implementation of digital embedded systems
• +۶ مورد دیگر

Matteo Lodi is an Assistant Professor at the University of Genoa , Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture (DITEN). His research focuses on modeling devices for engineering applications, dynamical systems analysis, and digital embedded systems design. He teaches courses such as Circuits and Systems , Electrotechnics , and Signal Processing in Robotics . Education: Laurea (B.Sc.) in Electronic Engineering from the University of Genoa (2015). Research Interests: His work spans power electronics, control systems, and synchronization dynamics. Key areas include inductor modeling (focusing on ferrite and amorphous-core materials), nonlinear model predictive control (NMPC), and grid stability solutions for renewable energy integration. He also explores cluster synchronization in complex networks and biologically inspired control systems for locomotion. Publications: Recent work highlights include FPGA-based NMPC implementations, virtual inertia controllers for wind turbines, and advanced inductor models accounting for saturation and thermal effects. His research bridges theoretical dynamical systems analysis with practical applications in power electronics and embedded systems.

Leyla Nazhandaliمشاهده پروفایل

استاد

• Low Power Computing
• Hardware Security
• Computer Architecture
• +۳ مورد دیگر

Leyla Nazhandali is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. Her research focuses on low-power computing, hardware security, and VLSI design with applications in embedded systems and cybersecurity. She has advised over 13 PhD and Master’s students, many of whom now work in leading tech companies like Intel, Samsung, and NVIDIA. Her work has been supported by NSF, SRC, NIST, and other agencies. Education: B.S. from Sharif University of Technology (2000), M.S./Ph.D. from the University of Michigan (2002/2006). She is a recipient of the NSF CAREER Award (2008) and the Bradley Faculty Fellow of Education (2024). Her teaching emphasizes cognitive disruptive techniques and threshold concepts in introductory courses, contributing to inclusive STEM education reforms. Research Interests: Low-power architectures, secure hardware design, and embedded systems for environmental monitoring. Notable projects include micro gas chromatography systems for hazardous air pollutant detection and fault-resistant cryptographic hardware. She co-leads initiatives integrating MEMS-based power-gating techniques for energy efficiency. Key Awards: 2025: W.S. 'Pete' White Innovation in Engineering Education Award 2024: Bradley Faculty Fellow of Education 2008: NSF CAREER Award 2008: IEEE Real World Engineering Project Contest Winner Outreach: Leads initiatives like the CEED Imagination Camp (middle school outreach) and Women in Computing Day, aiming to diversify STEM participation. Served as a NASA INSPIRE session chair and advisor for IEEE Women in Engineering programs. Grants & Labs: Active projects include NSF-funded work on fault-aware microprocessor extensions and NIST-supported cryptographic hardware evaluations. Her lab collaborates on implantable medical devices and secure embedded systems through Virginia Tech's ICTAS grants.

Paul Ampaduمشاهده پروفایل

استاد

• Reliable Systems-on-Chip (SoC)
• Secure Embedded Systems
• Low-Power VLSI Design
• +۴ مورد دیگر

Paul Ampadu is a Professor of Electrical and Computer Engineering at Virginia Tech and serves as the diversity lead at the Virginia Tech Innovation Campus. He leads the Embedded Integrated Systems-on-chip (EdISon) research group and is the associate director of the Advanced Research Institute (ARI). His work focuses on reliable, secure, and energy-efficient systems-on-chip (SoC), low-power VLSI design, and IoT security. He holds a Ph.D. from Cornell University (2004), an M.S. from the University of Washington (1999), and a B.S. from Tuskegee University (1996). Research interests span secure embedded systems design, low-power circuit architectures, and hardware security countermeasures against side-channel attacks. He is affiliated with the Center for Embedded Systems for Critical Applications and the Power and Energy Center. Recent contributions include scalable DC-DC converters, fault-resistant NoC designs, and neural network-based security analysis tools. Publications emphasize interdisciplinary approaches to hardware-software co-design for energy efficiency and security. His work addresses challenges in multicore systems, FPGA security, and IoT reliability through innovative circuit and system-level solutions.

• Quantum Cryptography
• Photonics
• Optical Communication Systems
• +۳ مورد دیگر

Ignacio López Grande is a Research Fellow at ICFO (Institut de Ciències Fotòniques), specializing in quantum technologies with a focus on quantum key distribution (QKD) and photonics. He holds a PhD in Physics from Universidad de Buenos Aires (Argentina). His research emphasizes integrated photonic systems, secure communication protocols, and the development of robust optical devices for quantum applications. Key contributions include advancements in CV-QKD transmitters, polarization-based QKD systems, and CubeSat platforms for spaceborne quantum communication. Education: PhD in Physics (Universidad de Buenos Aires, 2018) His work bridges fundamental quantum physics with applied photonics, addressing challenges in long-distance QKD, hybrid quantum-classical networks, and miniaturized optoelectronic components. Notable projects include the QUANGO CubeSat initiative for quantum-secured IoT connectivity and high-performance FPGA-based timing systems for optical communications. Collaborations focus on integrating QKD with existing fiber networks and enhancing signal robustness in multi-core fibers. Research interests also extend to photon indistinguishability in interferometry and adaptive transmitter designs for versatile quantum protocols. His experimental contributions include hardware innovations like gain-switched DFB lasers and autonomous open-source QKD apparatuses.

• Cybersecurity
• Underwater Acoustic Networks
• Hardware Security
• +۳ مورد دیگر

Zhijie Jerry Shi is an Associate Professor at the School of Computing, University of Connecticut. His research focuses on cybersecurity, underwater acoustic networks, hardware security, and blockchain technology. He leads projects such as Ocean-TUNE, a community testbed for underwater communication, and has contributed to secure firmware updates, cryptographic algorithms, and IoT security architectures. His work integrates hardware and software solutions for resilient systems. Key research areas include cryptographic side-channel attacks, underwater acoustic communication protocols, and blockchain scalability. He has developed innovative solutions for underwater sensor networks, including Aqua-Net and Aqua-Sim simulators, and explored secure metering systems using blockchain (SMChain). His hardware security research addresses vulnerabilities in embedded systems and trustable computing education. His publications span over 15 years, with recent emphasis on hardware trojan detection, diffractive optical neural networks, and secure IoT protocols. Collaborations involve experimental deployments in underwater environments and joint work on FPGA-based acoustic modems. He advises on secure wireless protocols, cryptographic implementations, and underwater network resilience.

Bo Yuanمشاهده پروفایل

استاد

• Cybersecurity
• Malware Analysis
• Computational Intelligence
• +۳ مورد دیگر

Bo Yuan is a Professor in the Department of Cybersecurity at Rochester Institute of Technology (RIT), affiliated with the Golisano College of Computing and Information Sciences. He served as Department Chair from 2014 to 2022, leading significant growth in cybersecurity programs. His research focuses on computational intelligence applied to cybersecurity, including malware analysis, machine learning, and covert channel detection. Education: Ph.D. in Systems Science (1996, Binghamton University), MS and BS in Mathematics (Shanghai Normal University, China). Research Interests: Cybersecurity, malware detection, computational intelligence, and machine learning applications in security. He has secured over $23M in grants, including NSF CyberCorps® SFS (2015-2024, 2019-2024, 2024-2029) and DoD Cyber Scholarship Programs. His work includes developing covert channel detection methods, improving malware analysis via machine learning, and advancing cybersecurity education through game-based learning. Grants/Projects: Multiple NSF and DoD grants totaling millions, focusing on cybersecurity workforce development and research. He leads RIT’s CAE-CD and CAE-R initiatives. His research has been applied in competitions like the Northeast Collegiate Cyber Defense Competition (NECCDC). Teaching includes courses on cybersecurity analytics, machine learning, and authentication models. He advises students on topics like adversarial machine learning and network security.

• Computer architecture
• Computing with novel technologies
• Brain-inspired computing

Georgios Tzimpragos is a Professor in the Department of Electrical & Computer Engineering at the University of Wisconsin-Madison, with a focus on computer architecture and novel computing technologies. Previously, he was an Assistant Professor at the University of Michigan (2022–2025) and earned his PhD from UC Santa Barbara (2022), focusing on neuro-inspired temporal paradigms for superconducting computing. His research explores overcoming technology limitations in superconductors, quantum computing, and biological computing systems, aiming to bridge computation and verification for improved correctness and security. Education: PhD in Computer Science, University of California-Santa Barbara (2022) MS in Computer Science, University of California-Davis (2016) BS in Computer Science, National Technical University of Athens (2012) Research Interests: His work spans computer architecture, novel computing technologies (e.g., superconductors, flexible electronics), and brain-inspired computing. Recent projects include developing energy-efficient superconducting circuits, quantum computing hardware, and neuromorphic systems that integrate biological principles. His group emphasizes formal verification and semantic gap reduction in computing systems. Recent Publications Trends: His articles address topics like superconducting logic design, quantum circuit simulation, and neuromorphic hardware acceleration. Recent work highlights include clockless superconducting logic, evolutionary neural network optimization, and formal methods for circuit validation. Awards & Honors: James E. Smith Professorship (UW-Madison, 2025) ACM SIGARCH & IEEE CS TCCA Outstanding Dissertation Award (2023) Quantum Research Institute Fellowship (U-Michigan, 2024) Grants & Teaching: Teaches E C E 554 (Digital Engineering Laboratory) and has received grants supporting superconducting and quantum computing research. His lab collaborates with industry partners on low-power and scalable architectures.

Matthias Függerمشاهده پروفایل

استاد

• Computer Architecture
• Embedded Systems
• Digital Circuits
• +۳ مورد دیگر

Matthias Függer is a Professor at the Department of Technical Computer Science within TU Wien's Institute for Technical Informatics. His research focuses on digital circuit design, fault-tolerant systems, and distributed computing. He has contributed to advancements in metastability containment, clock synchronization, and consensus algorithms in dynamic networks. His work bridges theoretical computer science with practical applications in embedded systems and VLSI design. Education details are not explicitly provided, but his academic role suggests a doctoral background. Notable projects include the development of the Involution Tool for timing analysis and collaboration on resilient circuit models under adversarial conditions. His research has been published in prestigious conferences and journals, emphasizing interdisciplinary approaches to solving challenges in asynchronous systems and fault tolerance. Labs/Teams: Network Lab at TU Wien. Advising: Advised Markus Hofstätter on his thesis involving FPGA-based Byzantine fault tolerance.

Josip Žilakمشاهده پروفایل

پژوهشگر

• Semiconductor Devices
• Integrated Circuits
• Microelectronics
• +۳ مورد دیگر

Josip Žilak is a Post-Doctoral Researcher at the Faculty of Electrical Engineering and Computing (FER), University of Zagreb. He holds a Diploma Engineer (2009) and Ph.D. (2017) in electrical engineering from FER. Since April 2010, he has worked as a junior FPGA engineer at Xylon d.o.o., focusing on embedded systems based on FPGA technology. Since June 2011, he has been a Research and Teaching Assistant at FER's Department of Electronics, Microelectronics, Computer and Intelligent Systems. His research centers on advanced bipolar transistor structures, particularly the Horizontal Current Bipolar Transistor (HCBT), involving simulations, integrated circuit design, and testing environment setup for HCBT verification. Žilak has authored/co-authored 4 peer-reviewed journal articles, over 15 conference papers, and multiple technical reports for institutions like Asahi Kasei Microdevices, Delft University of Technology, and Laser Components DG. He is an active member of IEEE Electron Devices Society (EDS) and IEEE Solid-State Circuits Society (SSCS). His work contributes to semiconductor device innovation and solid-state electronics.

Nektarios Tsoutsosمشاهده پروفایل

استادیار

• Information Security
• Applied Cryptography
• Computer Architecture
• +۳ مورد دیگر

Nektarios Tsoutsos is an Assistant Professor at the University of Delaware, specializing in information security, applied cryptography, and hardware security. His research focuses on encrypted computation, homomorphic encryption, and secure hardware architectures. He holds a PhD from New York University, where he was previously a postdoc in the Modern Microprocessor Architectures laboratory. Education : PhD in Computer Science, New York University Research Interests : Homomorphic encryption frameworks and their acceleration Hardware-software co-design for secure computing Privacy-preserving technologies in additive manufacturing and distributed systems Cryptography for machine learning and IoT Awards : New York University Ph.D. Student Fellowship Pearl Brownstein Doctoral Research Award (NYU) Grants & Projects : CAREER Grant: Accelerating Encrypted Computation on Diverse Hardware (2023) CCRI Grant: Data-Driven Cybersecurity for Smart Manufacturing (2023) His work includes developing secure processors (e.g., Juliet), accelerating FHE algorithms (e.g., Ripple), and creating datasets for 3D printing security. He collaborates on frameworks like HELM and Mastic, addressing challenges in privacy, performance, and scalability.

Cüneyt F. Bazlamaçcıمشاهده پروفایل

استاد

• Communication and Computer Networks
• Computer Systems Architecture
• Hardware Optimization
• +۵ مورد دیگر

Prof. Cüneyt F. Bazlamaçcı is a Professor in the Computer Engineering Department at İzmir Institute of Technology (IZTECH). He holds a B.Sc. and M.Sc. from Middle East Technical University (1988, 1991) and a Ph.D. in Computing from the University of Manchester (1996). His academic career includes roles at METU (1992–2020) before joining IZTECH in 2020. His research focuses on Communication and Computer Networks, Computer Systems Architecture, Graph Algorithms, and Embedded Systems. Notable contributions include patents on IP lookup architectures and publications in journals like Microprocessors and Microsystems and IEEE Transactions . He has advised over 40 graduate students, with topics ranging from FPGA-based systems to network optimization. His work spans network-on-chip design, reconfigurable computing, and cloud resource allocation. Projects include TÜBİTAK-funded research on low-voltage distribution systems and METU DSIM benchmarking studies. Prof. Bazlamaçcı teaches advanced courses in optimization, computer networks, and architecture. His research integrates algorithm design, hardware/software co-design, and parallel computing for real-world applications.