Find Academic Supervisors

Yixuan ZouView profile

Lecturer

• Artificial Intelligence
• Wireless Communications
• Machine Learning
• +7 more

Dr. Yixuan Zou is a Lecturer in Digital Signal Processing at the School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL). She co-teaches QMUL's Joint Programme with Beijing University of Posts and Telecommunications (BUPT). B.Sc. in Mathematics M.Sc. from Imperial College London Ph.D. in Computer Science, QMUL (2022) Her research focuses on applying artificial intelligence to wireless communications, specifically non-orthogonal multiple access (NOMA), IRSs/RISs-aided systems, and resource allocation for 6G networks. She integrates machine learning, deep reinforcement learning, and meta-learning techniques to optimize network performance. Recent publications highlight advancements in secure IoT node identification, UAV-assisted RIS-NOMA networks, STAR-RIS beamforming, and wideband near-field communication optimization. She contributes to IEEE conferences as a Technical Program Committee member and session chair. Academic Fellow at Digital Environment Research Institute (DERI) Dr. Zou supervises PhD students researching next-generation multiple access, AI-driven near-field communication, and human action recognition, while also serving as a reviewer for top-tier journals like IEEE TWC and IoT-J.

Vijaykrishnan NarayananView profile

Professor

• Power Aware Computing
• Computer Architecture
• Embedded Systems
• +4 more

Vijaykrishnan Narayanan is a Professor at the College of Engineering , Pennsylvania State University, with affiliations in both Computer Science & Engineering and Electrical Engineering departments. He co-directs the Microsystems Design Lab and leads the Architecture, Benchmarking, and Circuits Thrust at the DARPA/SRC LEAST Center. Education : Bachelors (1993) from University of Madras; Ph.D. (1998) from University of South Florida His research focuses on Power Aware Computing , Computer Architecture , Embedded Systems , and Emerging Device Integration . Recent work explores steep-slope devices for energy efficiency, nonvolatile processors for ambient energy harvesting, and neuromorphic architectures using hybrid VO₂-MOSFET oscillators. Key article trends span post-CMOS technologies (tunnel FETs, VO₂ devices), low-power design , and bio-inspired signal processing . Scientific Awards : IEEE Fellow, ACM Fellow, IEEE Transactions on VLSI Best Paper, IEEE Micro Best Paper Patents : Dynamically-configurable hardware architecture for audience analytics

George MannView profile

Professor

• Intelligent Control
• Robotics
• Machine Vision
• +6 more

George Mann is a Professor at Memorial University of Newfoundland's Faculty of Engineering and Applied Science. He holds a B.Sc. in Mechanical Engineering from the University of Moratuwa (Sri Lanka), an M.Sc. in Computer Integrated Manufacturing from Loughborough University (UK), and a Ph.D. in Intelligent Control from Memorial University. His research focuses on intelligent control systems, robotics, and machine vision, with significant contributions to autonomous navigation, sensor fusion, and UAV technologies. He leads the Intelligent Systems Laboratory (ISLAB) and has pioneered work on LiDAR-assisted radar enhancement, multi-robot localization, and exoskeleton control systems. **Education**: B.Sc., Mechanical Engineering, University of Moratuwa (Sri Lanka) M.Sc., Computer Integrated Manufacturing, Loughborough University (UK) Ph.D., Intelligent Control, Memorial University (Canada) **Research Interests**: Dr. Mann’s work spans autonomous systems, UAV navigation, sensor fusion (e.g., LiDAR, radar, INS), and robotics applications in mining, healthcare, and environmental monitoring. His recent projects include developing computationally efficient NMPC algorithms for UAVs and creating robust localization systems for heterogeneous multi-robot networks. **Publications**: His articles emphasize advancements in navigation algorithms, disturbance estimation for multi-rotor stability, and AI-driven sensor integration. Key themes include improving system robustness under uncertainty and optimizing computational efficiency in real-time control. **Labs & Teams**: Director of ISLAB, collaborating on exoskeleton development (e.g., Anthro-X) and UAV plume tracking for environmental sensing. Active in industry partnerships like C-CORE for mining automation.

• Hardware Security
• Machine Learning for Security
• IoT Security
• +5 more

Setareh Rafatirad is an Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University's College of Engineering and Computing. Her research spans hardware security, machine learning for security applications, and IoT security systems. Her research interests focus on hardware security, machine learning for security applications, IoT security, side-channel attacks, and malware detection. She has developed innovative approaches for securing integrated circuits, detecting malware using machine learning techniques, and protecting against side-channel vulnerabilities in computer systems. Her work bridges the gap between hardware design and security, creating practical solutions for emerging security challenges in computing systems. Her recent publications demonstrate a strong trend toward applying machine learning techniques to security problems, particularly in hardware and embedded systems. She has made significant contributions to understanding and mitigating side-channel attacks, developing secure machine learning models, and creating efficient security solutions for resource-constrained devices. Her work shows increasing interdisciplinary reach, connecting hardware security with healthcare applications and educational technologies. Dr. Rafatirad has collaborated extensively with researchers including Houman Homayoun, Avesta Sasan, and Sai Manoj P. Dinakarrao. She has secured research funding for projects related to hardware security and machine learning applications, though specific grant details are not provided in the available information.

Liqiang ZhangView profile

Professor

• Wireless Networks
• Mobile Computing
• Resource Allocation
• +3 more

Dr. Liqiang Zhang is a Professor at the Department of Computer and Information Sciences, Indiana University South Bend. He holds a Ph.D. in Computer Science from Wayne State University (2005). His research focuses on wireless networks, mobile computing, resource allocation, IoT, cognitive radio networks, and network security. His work is supported by IU and the National Science Foundation. He has organized multiple conferences including ICCCN 2013 (Track Chair), GLOBECOM 2010 (Publicity Co-Chair), and founded/co-chaired WiMAN workshops. He serves as a Guest Editor for journals like ACM Transactions on Autonomous and Adaptive Systems and Elsevier's Computer Communications. He reviews for top journals including IEEE Transactions on Mobile Computing and IEEE Transactions on Parallel and Distributed Systems. Dr. Zhang teaches courses such as Computer Structures, Mobile App Development, and Network Security. Recent publications (2019-2009) include advancements in network scheduling, cognitive radio protocols, radar positioning, and digital design education. His research spans both theoretical and applied aspects of networking and distributed systems.

John A. McNeillView profile

Professor

• Biomedical Sensing
• Integrated Circuits
• Microelectronics
• +3 more

John A. McNeill is the Bernard M. Gordon Dean of Engineering at Worcester Polytechnic Institute (WPI), where he has been since 1994. He holds a PhD in Electrical, Computer, and Systems Engineering from Boston University and has maintained strong industry ties through initiatives like the New England Center for Analog and Mixed Signal Design. His research focuses on mixed-signal integrated circuits, biomedical sensors, and low-power systems, including a wearable wireless sensor for pressure ulcer prevention. He has advised numerous graduate and undergraduate students on projects involving analog and digital circuit design. McNeill’s academic journey includes a BS from Dartmouth College (1983), MS from the University of Rochester (1991), and PhD from Boston University (1994). He has received prestigious awards like the NSF CAREER Award (1997), WPI’s Chairman’s Exemplary Faculty Prize (2007), and the Eta Kappa Nu Outstanding Professor Award (multiple times). His work has resulted in six patents and over 60 peer-reviewed publications. He leads initiatives to enhance engineering education, emphasizing project-based learning and interdisciplinary collaboration. His professional affiliations include IEEE, the American Society for Engineering Education, and the National Academy of Inventors.

Phillip RaffeckView profile

Researcher

• Real-Time Systems
• Embedded Systems
• Energy-Aware Computing
• +7 more

Phillip Raffeck is a researcher at the Department of Computer Science (INF) within the Chair of Computer Science 4 (System Software) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His work focuses on real-time systems, embedded systems, and energy-aware computing, with a particular emphasis on worst-case execution time (WCET) and energy consumption (WCEC) analysis. He has contributed to projects like the Invasive Run-Time Support System (iRTSS) and tools for energy-neutral system design. Department: Department of Computer Science (INF) University: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Position: Researcher His research spans real-time systems , multi-core optimization , and power-aware computing . Key contributions include migrative synchronization protocols , energy-neutral operating systems , and code metrics for timing analysis . Recent work explores carbon-aware co-design and predictable migration in embedded environments. Publications highlight collaborations with teams across Germany and international symposia like RTSS, WCET, and EMSOFT. His article trends reflect advancements in intermittent execution models , transactional networking , and static analysis toolchains . He serves as a secondary reviewer for conferences including RTAS and ISORC. Phillip supervises graduate theses on topics such as DMA-based OS offloading , dynamic migration , and interrupt latency analysis . He contributes to teaching courses like Betriebsystemtechnik and Systemnahe Programmierung in C at FAU.

• Microelectronics
• MEMS Resonators
• Radio Frequency (RF) Devices
• +4 more

Dana Weinstein is a Professor in the Department of Electrical and Computer Engineering at Purdue University, West Lafayette campus. Her research focuses on cutting-edge MEMS resonators, RF device integration, and acoustoelectronic systems. Academic Rank: Professor Department: Electrical and Computer Engineering University: Purdue University Email: danaw@purdue.edu Research Interests: Microelectronics and MEMS Resonators Radio Frequency (RF) Devices and 2D Materials Silicon Photonics and Ferroelectric Transducers Acoustoelectronics and GaN/SiC Heterostructures Integrated Nonreciprocal RF MEMS Devices Scientific Awards: NSF CAREER Award (2017) NSF CAREER Award (2012) Editorial Leadership in IEEE Nanotechnology Express (2015) Key Article Trends: Her recent publications explore advanced MEMS resonators, high-frequency RF devices, acoustoelectric interactions, and integration of 2D materials into CMOS-compatible platforms. Topics include Sezawa wave SAW devices, GaN/SiC heterostructures, BEOL-compatible transistors, and ferroelectric-based transducers.

Sebastien PillementView profile

Lecturer

• Computer Engineering
• Embedded Systems
• Computer Architecture
• +3 more

Sébastien Pillement is a Lecturer at Polytech'Nantes, the College of Engineering of the University of Nantes, and a member of the ASIC research team within the IETR UMR 6164 laboratory. His career spans over 13 years at the IUT of Lannion (University of Rennes 1) before joining the University of Nantes in 2012. He holds a PhD in Computer Science from the University of Montpellier II (1998) and a Habilitation à Diriger des Recherches (HDR) from the University of Rennes 1 (2010). Current Research Focus: Dynamically Reconfigurable Architectures (DRA), Hardware Security, Fault-Tolerant Embedded Systems, NoC (Network-on-Chip), Design Methodologies. Teaching Areas: Digital Circuits, Computer Architecture, Operating Systems, Real-Time Systems, and Algorithms for Embedded Computing. His research explores flexible and efficient architectures for embedded systems, emphasizing real-time management, reliability, and security. Key article trends include RISC-V processors, neural network acceleration on MPSoC, formal verification of arithmetic circuits, and runtime FPGA scheduling. Collaborations span international institutions like the University of Toronto and CEA, as well as industrial partners such as STMicroelectronics and Thales. PhD Students : Current: Laureline Dubucq (Security & AI), Mustafa Ibrahim (Ultra-Low Power AI), Téo Biton (Runtime Anomaly Detection), Mohamed Amine Zhiri (Adaptive NoC), Juliette Pottier (RISC-V Protection). Graduates: Quentin Dariol (Neural Network Timing), Alexis Duhamel (FPGA Scheduling), Safouane Noubir (Security in Multi-Core Systems), Hai Dang Vu (Probabilistic Timing Analysis), David Pallier (Sensor Clock Synchronization). Projects : Current: ADAPTING (2023-2029), FITNESS (2023-2027), SEC-V (2022-2025), NOP (2021-2025). Past: SPARTE (2015-2018), ARDyT (2011-2015), FosFor (2008-2011).

Takeshi ShirabeView profile

Associate Professor

• Geographic Information Science
• Spatial Optimization
• Geodesign
• +4 more

Takeshi Shirabe is an Associate Professor in the Division of Geoinformatics at KTH Royal Institute of Technology, Sweden. He holds positions in the Department of Urban Planning and Environment, School of Architecture and the Built Environment (ABE), and is part of the Digital Futures cross-disciplinary research center. His research focuses on spatial optimization, geographic information science (GIS), and geodesign, with particular emphasis on raster-based models for spatial decision support and route improvisation. He has taught numerous courses including GIS Architecture and Algorithms, Computational Methods in GIS, and Spatial Planning with GIS. Shirabe's academic journey includes a PhD from the University of Pennsylvania (USA), a Master’s in City and Regional Planning from the same institution, and a Bachelor of Engineering from the University of Tokyo. Before joining KTH in 2010, he served as an Assistant Professor at Vienna University of Technology, Austria, where he earned his Habilitation in Geoinformation. His research interests span combinatorial optimization in geography, spatial decision support systems, and GeoDesign. Notable projects include the Space Time Alarm Clock (STAC), an Android app for pedestrian route improvisation, developed with Adrian C. Prelipcean and Falko Schmid. This tool uses real-time spatial-temporal analysis to guide users toward destinations efficiently. Shirabe has contributed to over 30 peer-reviewed publications since 2002, focusing on raster-based GIS methods for corridor design, least-cost path analysis, and spatial allocation modeling. His work bridges theoretical computational geometry with practical urban planning applications. Courses he oversees emphasize algorithmic and computational foundations of geospatial technologies.

Jean-Yves Le BoudecView profile

Professor

• Network Calculus
• Time-Sensitive Networking
• Deterministic Networking
• +7 more

Jean-Yves Le Boudec is a Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences and the Institute of Electrical Engineering. He has been a key figure in advancing the theory and application of network calculus and deterministic networking, contributing significantly to standards such as IEEE Time-Sensitive Networking (TSN) and IETF DetNet. His research focuses on network calculus , time-sensitive and deterministic networking , traffic regulation , worst-case delay analysis , and cyber-physical systems , with cross-cutting applications in smart grids , real-time communication , and network security . He has co-authored foundational texts on network calculus and developed theoretical frameworks for traffic regulators, service curves, and delay bounds in complex networked systems. The recent publications highlight a strong trend in analyzing and improving performance guarantees in deterministic networks, including scheduling mechanisms like Deficit Round-Robin and Cyclic Queuing and Forwarding, traffic shaping via interleaved regulators, and security against time-synchronization attacks in power systems. The work spans theoretical modeling using stochastic and min-plus/max-plus algebra, practical algorithm design, and application to critical infrastructure. IEEE Fellow Le Boudec has advised numerous researchers and PhD students, including Ehsan Mohammadpour, Ludovic Thomas, and Seyed Mohammadhossein Tabatabaee. His collaborative projects often involve grants related to European and Swiss research initiatives in networking and smart grid technologies. He leads a research group focused on networked systems at EPFL, contributing to both theoretical advances and real-world implementations in industrial and energy-critical networks. His lab work centers on modeling and verification of time-sensitive network behaviors, integrating formal methods with practical experimentation. The team investigates regulators, shapers, and synchronization mechanisms, aiming to ensure robustness, predictability, and security in next-generation communication infrastructures. Future work continues to explore the interplay between communication, control, and energy systems in highly reliable environments.

• Photonics
• Quantum Optics
• Nonlinear Optics
• +5 more

Ayhan Demircan is an Adjunct Professor at the Leibniz School of Optics and Photonics in Leibniz University Hannover. He leads the Micro and Nano Photonics task group and contributes to institutions including the Institute of Quantum Optics , Ultrafast Laser Laboratory , and Hannover Centre for Optical Technologies (HOT) . His work spans photonics, quantum optics, and nonlinear dynamics, with applications in terahertz technology, soliton physics, and optical modeling. Research Interests: Photonics, quantum optics, terahertz radiation, soliton dynamics, nanophotonics, and computational modeling of optical systems. Key Institutions: Leibniz School of Optics and Photonics, Institute of Quantum Optics, HOT, and PhoenixD Cluster of Excellence. Technical Expertise: Develops Python-based tools for nonlinear Schrödinger equations, optical parametric oscillators, and ultrafast laser systems. Contact: demircan@iqo.uni-hannover.de

Svetlana N. RadyukView profile

Research Professor

• Redox Regulation
• Innate Immunity
• Aging Mechanisms
• +5 more

Svetlana N. Radyuk serves as a Research Associate Professor in the Department of Biological Sciences within Dedman College of Humanities and Sciences at Southern Methodist University. Her laboratory (DLSB 317) focuses on the molecular mechanisms linking redox regulation, innate immunity, and aging processes using Drosophila melanogaster as a primary model system. Her research centers on redox regulation of innate immunity during aging , specifically investigating how peroxiredoxins modulate immune responses and longevity. Key areas include: Role of reactive oxygen/nitrogen species (ROS/RNS) as dual-function molecules causing tissue damage while serving as immune signaling messengers Conserved functions of peroxiredoxins across biological kingdoms in regulating redox homeostasis Age-related immune decline including reduced pathogen resistance, impaired T/B cell function, and chronic inflammation Interactions between circadian clocks, redox balance, and aging processes Analysis of her 15 most recent publications reveals a consistent focus on peroxiredoxin-mediated redox signaling in Drosophila models, with recent expansion into hydrogen gas therapeutics for oxidative stress-related conditions. Her work demonstrates how precise ROS/RNS regulation balances immune protection against tissue damage, with significant implications for age-related diseases. Dr. Radyuk currently holds two major NIH/NIA-funded research grants: R01 AG032342 (Principal Investigator): Peroxiredoxins, immune signaling and aging (2011-2016) R01 AG045830 (Co-PI): Circadian clocks and aging (2013-2018) Her teaching portfolio includes advanced courses in Immunobiology (BIOL 4319), Molecular Genetics Laboratory (BIOL 3222), and graduate-level research/thesis supervision (BIOL 6270, 8398). Her laboratory employs comprehensive molecular biology and genetics techniques to investigate redox-immunity interactions, with particular emphasis on developing interventions that maintain optimal immune function during aging.

Vincent BeroulleView profile

Professor

• Microelectronics
• Hardware Security
• Fault Modeling
• +4 more

Professor Vincent Beroulle at Grenoble Institute of Technology's Esisar campus leads the LCIS laboratory, focusing on security and safety of complex integrated circuits and systems. His work bridges fault modeling, fault injection, and security for IoT and RFID technologies. Education: Engineer Degree (INPG, 1996), Master (University of Montpellier II, 1999), Ph.D. (University of Montpellier II, 2002) Current Role: Director of LCIS Laboratory, Professor in Embedded System Security & Safety Research spans hardware security, fault injection attacks, and vulnerability analysis of embedded systems. Recent work includes clock glitch fault injection studies, lightweight ECC countermeasures for RFID, and aging effects on PUF architectures. His team explores cross-layer methodologies to enhance fault models and security protocols. Supervision includes 12 current and former PhD students tackling topics like secure RFID tags, fault injection countermeasures, and PUF-based security. Projects under ANR, PEPR Cyber, and ERASMUS+ funding drive his lab's innovation in secure embedded design.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +5 more

Bo Wang is an active academic researcher primarily affiliated with multiple Chinese institutions, with strong connections to Tsinghua University, Beijing Jiaotong University, and other leading Chinese universities. His research spans artificial intelligence, machine learning, computer vision, medical image analysis, and intelligent control systems, demonstrating significant interdisciplinary work across computer science, engineering, and biomedical applications. Primary institutional affiliation: School of Computer Science and Technology at multiple Chinese universities Active research areas: AI/ML applications in healthcare, computer vision, federated learning, and intelligent control systems Extensive publication record across top-tier venues in multiple disciplines Wang's research interests focus on the intersection of artificial intelligence and practical applications. His work demonstrates strong expertise in developing novel machine learning architectures for medical image analysis, including applications in CT imaging, MRI, and sperm tracking. He has made significant contributions to federated learning approaches for large language models, sliding mode control systems, and molecular optimization frameworks. His research consistently bridges theoretical advances with practical implementations across healthcare, manufacturing, and environmental monitoring domains. Analysis of Wang's recent publications reveals a strong trend toward interdisciplinary AI applications, particularly in medical imaging and bioinformatics. His work on VAE-GANMDA for microbe-drug association prediction, ACE-QSM for accelerating MRI acquisition, and text-guided molecular optimization demonstrates innovative approaches at the intersection of AI and life sciences. Wang also maintains active research in industrial applications including digital twin technology for energy systems and robust scheduling approaches for multi-factory production. Notable research contributions include: FLFT: A Large-Scale Pre-Training Model Distributed Fine-Tuning Method with Federated Learning VAE-GANMDA: Microbe-drug association prediction model ACE-QSM: Accelerating quantitative susceptibility mapping using diffusion models Digital twin-empowered power consumption prediction systems Wang actively collaborates with researchers across China and internationally, with publications spanning computer science, engineering, medical imaging, and environmental science journals. His work demonstrates strong technical depth across multiple AI methodologies while maintaining focus on practical applications that address real-world challenges in healthcare, manufacturing, and environmental monitoring.