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Leyla NazhandaliView profile

Professor

• Low Power Computing
• Hardware Security
• Computer Architecture
• +3 more

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 AmpaduView profile

Professor

• Reliable Systems-on-Chip (SoC)
• Secure Embedded Systems
• Low-Power VLSI Design
• +4 more

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
• +3 more

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
• +3 more

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 YuanView profile

Professor

• Cybersecurity
• Malware Analysis
• Computational Intelligence
• +3 more

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 FüggerView profile

Professor

• Computer Architecture
• Embedded Systems
• Digital Circuits
• +3 more

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 ŽilakView profile

Researcher

• Semiconductor Devices
• Integrated Circuits
• Microelectronics
• +3 more

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 TsoutsosView profile

Assistant Professor

• Information Security
• Applied Cryptography
• Computer Architecture
• +3 more

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. BazlamaçcıView profile

Professor

• Communication and Computer Networks
• Computer Systems Architecture
• Hardware Optimization
• +5 more

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.

Luca CassanoView profile

Associate Professor

• Hardware Security
• RISC-V Processors
• Deep Learning Reliability
• +3 more

Luca Cassano is an Associate Professor at the Department of Electronics, Informatics and Bioengineering (DEIB) at Politecnico di Milano, Italy. He leads the Hardware Forge research group, focusing on hardware security, RISC-V processors, and reliability of deep learning systems. He earned his Ph.D. in Information Engineering from the University of Pisa (2013), with prior postdoctoral research at CNR and Politecnico di Milano. His research spans hardware Trojans, microarchitectural attacks (e.g., Spectre/Meltdown), fault-tolerant design, and radiation-hardened systems. Notable achievements include winning the TTTC's E. J. McCluskey Doctoral Thesis Award (2014) and multiple best paper awards at IEEE conferences. He teaches courses on hardware accelerators and computer fundamentals, and collaborates with industry partners like TDS-Space and ESA on satellite systems and secure RISC-V cores. Research interests include: Hardware Security (Trojans, Side-Channel Attacks) Secure RISC-V Processor Design Deep Learning Reliability Fault-Tolerant Systems Selected articles highlight work on benchmarking deep learning resilience, transient execution attacks on RISC-V, and radiation effects mitigation. His work bridges theory and practice, addressing challenges in embedded systems, space computing, and cybersecurity. Grants and collaborations emphasize applied research in dependable and secure embedded systems.

• Power Electronics
• Renewable Energy Systems
• Optimization Algorithms
• +3 more

Abdul Moeed Amjad is a Visiting Professor at Queen Mary University of London's School of Electronic Engineering and Computer Science. His primary affiliation is with the university's engineering department, focusing on advanced power electronics and renewable energy systems. His research emphasizes optimization-based solutions for harmonic elimination in multilevel converters, particularly using algorithms like differential evolution and Levenberg-Marquardt. His work spans modular multilevel cascade converters (MMC), STATCOM systems, and FPGA implementations of PWM controllers. Key contributions include real-time harmonic suppression techniques and high-level inverter design for grid integration applications. He has consistently published in top-tier journals since 2013, with notable work on 15- and 23-level inverters. No specific awards or grants are listed in the provided information. His research trends show increasing focus on hybrid optimization algorithms and their application to renewable energy conversion systems. While no formal student advisees are mentioned, his publications suggest collaborative work with academic institutions in power electronics and control systems.

Franco CaspeView profile

Researcher

• Neural Synthesis
• Instrument Augmentation
• Sound Matching
• +5 more

Franco Caspe is a PhD researcher at Queen Mary University of London's School of Electronic Engineering and Computer Science, focusing on AI-assisted sound synthesis and embedded systems. His work bridges music technology, machine learning, and hardware design, with a particular emphasis on real-time audio generation and neural synthesizer development. Affiliations: Queen Mary University of London (PhD candidate), AIM CDT, C4DM Sound Synthesis and Augmented Instruments Research Theme Education: M.Sc. in Image Processing and Computer Vision (Erasmus Mundus), Electronic Engineering diploma (Argentina), with research internships in India (RF Metamaterials) and Italy (Tonewheel Organ Synthesizer development). Research Interests: Neural synthesis, instrument augmentation, sound matching, FM synthesis, FPGA-based neural networks, and embedded AI systems. His projects include real-time DNN serving frameworks, low-latency audio synthesis, and hardware-accelerated neural network implementations on embedded platforms like the Zybo-Z7 FPGA board. Publications span topics in music technology, signal processing, and embedded systems, with a focus on interdisciplinary approaches combining data science and engineering. He has contributed to open-source projects like BNN-PYNQ for FPGA-accelerated neural networks, demonstrating expertise in hardware-software co-design.

August ErnstssonView profile

Lecturer

• Parallel Programming
• Heterogeneous Computing Systems
• High-Performance Computing
• +3 more

August Ernstsson is a Lecturer at Linköping University’s Department of Computer and Information Science (IDA). He is affiliated with the Graduate School in Computer Science (CUGS) and research groups Programming Environments (PELAB) and Software and Systems (SAS). His research focuses on parallel programming models, heterogeneous computing systems, and optimizing software for FPGA and GPU architectures. Notable contributions include frameworks for high development productivity (EXA2PRO) and deterministic parallel algorithms. Ernstsson’s work emphasizes performance portability, compiler design, and abstraction layers for heterogeneous systems. He collaborates with international teams on projects like pattern-based programming abstractions and FPGA-accelerated systems.

Jan BroeninkView profile

Associate Professor

• Cyber-Physical Systems
• Systems Engineering
• Robot Software Architectures
• +10 more

Jan Broenink is an Associate Professor at the University of Twente, affiliated with the Robotics and Mechatronics group within the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). He serves as Programme Director of the MSc Robotics programme since July 2021 and previously chaired the Robotics and Mechatronics group (2017–2021). He holds a PhD and MSc in Electrical Engineering (EE) and biomedical degrees from the University of Twente. His research focuses on Cyber-Physical Systems, Systems Engineering, Robot Software Architectures, and Tools Development. Key interests include model-driven design, meta-modelling, simulation, co-simulation, and concurrent engineering. He develops software tools for robotics, emphasizing real-time computing and embedded control systems. Teaching encompasses Robot Software Design using Model-Driven approaches, Systems Engineering, and project supervision for MSc/BSc students. His work contributes to UN SDGs related to Industry and Future of Work, and Social and Daily Life. Broenink has supervised 9 student works and is active in conferences, presenting on topics like co-design methodologies and bond graph frameworks. His 162+ research outputs span embedded systems, robotics, and simulation tools.