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Maxime Pelcat is a Full Professor at INSA Rennes, France, affiliated with the Department of Electronics, Computer Science and Systems within the College of Engineering. His research is conducted in the VAADER team at IETR, a CNRS research unit (UMR 6164), where he leads advanced work in sustainable, secure, and open embedded systems. PhD in Signal Processing, INSA Rennes, 2010 Habilitation (HDR), Université Clermont Auvergne, 2017 Researcher at Fraunhofer IIS, Germany Contractor at France Telecom R&D Faculty at INSA Rennes since 2011 Maxime Pelcat's research focuses on sustainable electronics, open hardware (especially RISC-V), hardware security against side-channel attacks, and machine learning at the edge. He emphasizes energy efficiency, system sovereignty, and end-of-life sustainability in electronic design. His work integrates models of computation, heterogeneous architectures, and reconfigurable hardware to improve system efficiency and design productivity in embedded signal processing and telecommunications. His publications and projects reflect a strong trend in sustainable computing, embedded AI, and secure system design. The work spans FPGA-based acceleration, MPSoC optimization, deep learning integration, and dataflow programming models, particularly applied to vision systems and signal processing. Scientific Awards and Honors: Best PhD Award 2016 (Fondation Rennes 1) - for advisee Erwan Nogues Chaire d’Excellence France-Nokia 2024 Maxime Pelcat has co-advised 11 PhD students in areas including deep learning on FPGAs, intrusion detection, eavesdropping exploitation, multi-view vision systems, and reconfigurable architectures. He has participated in major research projects including 1 H2020 ICT, 1 H2020 ITN, 1 NSF, 1 FUI, and 2 ANR projects. He leads the French PIA4 CMA project ESOS (Electronics: Sustainable, Open, Sovereign), funded by France2030. He has authored over 80 peer-reviewed publications and a Springer book on multi-core prototyping. He is a key member of the VAADER research team at IETR and leads the Sustainable Computing Workshop. He has held leadership roles in major conferences, including Program Chair of SAMOS-IC 2019 and General Chair of IEEE SiPS 2022 and GDR SOC2 2020. He was an elected member of CNRS CoNRS Section 07 (Information Science) from 2018 to 2021.

• Embedded Systems Design
• Sustainable Electronics
• Open Hardware
• +13 more

Jose Luis Abellan Miguel is a Ramón y Cajal Fellow and Tenure-Track Associate Professor at the University of Murcia's Department of Computer Engineering and Technology. He leads the EcoArTech team and is a European R3 researcher. Previously, he held roles at the University of Ferrara, Boston University, and Universidad Católica de Murcia. His research focuses on GPU architectures, accelerators for machine learning, and privacy-preserving computing, particularly Fully Homomorphic Encryption (FHE). He has authored over 70 peer-reviewed publications and contributed to conferences like ISCA, HPCA, and MICRO. Education: Bachelor's, Master's, and PhD in Computer Science and Engineering (University of Murcia, 2007–2012) Research Interests: Abellan's work emphasizes architectural enhancements for GPU systems, customized accelerators for ML and FHE, and efficient synchronization/communication in many-core architectures. His contributions include tools like MGPU-Sim and STONNE for simulation, and frameworks like FIDESlib for FHE on GPUs. Recognition: HiPEAC Paper Awards (2011, 2019–2024) Top Picks in Hardware and Embedded Security 2024 European R3 Certificate (2024) Editorial roles at ACM TACO and Frontiers in Electronics Grants & Leadership: Recipient of a Ramón y Cajal fellowship and a Consolidación Investigadora grant. He chairs sessions at conferences like ISPASS and serves on TPCs for venues including DATE, HPCA, and MICRO. His lab collaborates with institutions like Georgia Tech, Northeastern University, and Intel. Labs/Teams: He leads the EcoArTech team, focusing on next-gen computing systems via architectural simulators. Collaborators include researchers from MIT, Boston University, and industry partners like NVIDIA and Intel.

• Computer Architecture
• GPU Systems
• Accelerators for Machine Learning
• +4 more

Rosa Maria Badia Sala is a Research Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament d'Arquitectura de Computadors and the Barcelona Supercomputing Center (BSC-CNS). She specializes in distributed computing, heterogeneous systems, and task-based programming models. Her work focuses on advancing high-performance computing (HPC), cloud computing, and workflow management for large-scale scientific applications. She holds a Doctorat en Informàtica and has been actively involved in numerous research projects, including contributions to the COMPSs programming framework and the optimization of HPC workflows. Her collaborations span institutions like BSC-CNS and international initiatives such as JLESC. Recent research includes GPU-accelerated computing, quantum optimization algorithms, and digital twins for power networks. Badia's publications span journals like Future Generation Computer Systems and IEEE Transactions on Parallel and Distributed Systems, reflecting her expertise in parallel computing, distributed systems, and real-time data analysis. She has supervised multiple doctoral theses and contributes to research grants focused on HPC and AI integration.

• Distributed Computing
• Heterogeneous Computing
• Programming Models
• +5 more

Víctor Manuel Brea Sánchez is an Associate Professor at the Research Center on Intelligent Technologies (CiTIUS) within the University of Santiago de Compostela (Spain). His work focuses on hardware implementations for computer vision and CMOS-3D technologies . Research Areas : Computer Vision, Electronic Design, Low-Power Embedded Systems Projects : AZOR (Search, Location, Rescue), Power Management Unit Chip for Energy Harvesting His recent publications emphasize CMOS-based vision sensors , analog computing-in-memory , and spatio-temporal feature extraction . Trends include deep learning acceleration, event cameras, and hardware for real-time object detection. Scientific contributions include the Best Paper Award at the 2003 European Conference on Circuit Theory and Design. Collaborations with researchers like Manuel Mucientes and Paula López highlight interdisciplinary efforts in AI-driven hardware design.

• Computer Vision
• Electronic Design of Intelligent Devices
• CMOS-3D Hardware Implementation
• +2 more

Ana Maria Gomez Amador is an Assistant Professor in the Department of Mechanical Engineering at the University Carlos III of Madrid (UC3M). She is affiliated with the Experimental Mechanics, Calculations and Transport Group (MECATRAN) and the Duque de Santomauro Institute of Motor Vehicle Safety. Her research focuses on structural analysis, 3D printing applications, vehicle safety, and educational technology. Her academic work spans mechanical systems, including studies on T-stub connections, soil-structure interaction, and Roman engineering systems. She has contributed to advancements in low-cost mechanical ventilators, automotive braking efficiency, and aerodynamic device design. Her projects include leading studies on roadworthiness testing and developing educational tools for descriptive geometry and engineering design. Dr. Gomez Amador has collaborated on over 30 publications since 2016, with recent work emphasizing additive manufacturing, finite element analysis, and interdisciplinary applications of mechanical engineering. She maintains active roles in both teaching and applied research, addressing modern challenges in transportation safety and sustainable materials science. Her professional activities include patent development (e.g., driving style evaluation systems) and software tools like fBrake-TT for automotive analysis. She has advised on technical reports for organizations like AECA-ITV and Eiffage Energie, contributing to both academic and industrial innovation.

• Mechanical Engineering
• Vehicle Safety
• 3D Printing Applications
• +3 more

Jesús Fernando López Fidalgo is a researcher at the Institute of Data Science and Artificial Intelligence (DATAI) within the University of Navarra . His work focuses on optimal experimental design across diverse fields including statistics, numerical analysis, and biological modeling . Doctorate from University of Salamanca (1991) in Statistics Co-editor of multiple statistical analysis books Research spans discriminating between statistical models , optimal design theory , and application-driven designs for agricultural and biomedical systems. His recent publications emphasize Bayesian approaches , robust design , and partial likelihood information in survival analysis. Collaboration network includes 26 co-authors across 52 publications since 1992, with significant contributions to Computational Statistics and Data Analysis (7 papers), Test (7 papers), and Statistical Papers (3 papers).

• Statistics
• Numerical Analysis
• Biology
• +2 more

Víctor López Domínguez is an Assistant Professor and Principal Investigator at the Institute of Advanced Materials (INAM) of Jaume I University in Castelló, Spain, where he leads the Spintronics for Advanced Devices Lab (SPINAD Lab). His research focuses on developing next-generation spintronic devices for computing and sensing applications. His academic background includes: PhD in Nanoscience and Nanotechnology (2014) from University of Barcelona Physics Degree (2009) from University of Barcelona López Domínguez's research centers on electrical transport in magnetic materials, magnetization dynamics, and voltage-controlled spintronic devices. His work bridges fundamental physics with practical applications in neuromorphic computing, probabilistic systems, and nanoscale sensors. Key focus areas include antiferromagnetic spintronics, skyrmion manipulation, and energy-efficient computing paradigms that leverage spin-orbit torque and voltage control mechanisms. His 15 most recent publications reveal a strong emphasis on antiferromagnetic memory devices, voltage-controlled magnetism, and neuromorphic applications. The research spans from fundamental material studies to device integration, with significant contributions to silicon-compatible spintronic memory, probabilistic computing hardware, and magnetomechanical sensors. His scientific recognition includes: CIDEGENT grant (2022) from Generalitat of Valencia López Domínguez secured the CIDEGENT grant to establish his research group at INAM, supported by Jaume I University and INAM. His lab trains undergraduate, master's, and PhD students in experimental spintronics while collaborating with international clean rooms and industry partners. Current projects focus on implementing novel computing paradigms using spintronic devices. The SPINAD Lab maintains comprehensive facilities for material fabrication, device characterization, and nanofabrication through Spanish clean room networks. The group collaborates extensively with Northwestern University (where López Domínguez previously worked) and participates in international research consortia focused on next-generation computing technologies.

• Spintronics
• Magnetic materials
• Electrical transport
• +5 more

Manuel Eugenio Acacio Sanchez is a Professor in the Department of Computer Engineering and Technology at the University of Murcia's Faculty of Informatics. His research focuses on computer architecture, parallel systems, cache coherence, and hardware transactional memory. He earned his Ph.D. from the University of Murcia in 2003 with a thesis on directory-based coherence protocols for distributed-shared memory multiprocessors. Doctorate: Universidad de Murcia (2003) Academic Rank: Professor Research Interests include Hardware transactional memory Cache coherence protocols GPU and DNN accelerators Energy-efficient computing Parallel architectures Recent Article Trends emphasize cycle-level simulation tools (e.g., STONNE), hardware transactional memory optimizations, and neural network accelerator design. His work bridges microarchitectural improvements and application-specific efficiency in multicore systems. Labs & Teams : Affiliated with the Computer Architecture and Parallel Systems research group, previously part of the Architecture and Parallel Computing group.

• Computer Architecture
• Parallel Computing
• Cache Coherence
• +5 more

Jorge Gallego Madrid is a Research Fellow at Universidad de Murcia's Faculty of Informatics in the Department of Information and Communication Engineering, affiliated with the Intelligent Systems and Telematics group. His research focuses on AI-driven network programmability for 5G/B5G infrastructures, IoT systems, and zero-touch management. Recent publications explore eBPF/XDP technologies, ML-powered traffic processing, and vehicular network architectures. He earned his PhD in 2024 with the dissertation 'Towards AI-based Network Programmability as an enabler for Zero-touch management and orchestration in B5G infrastructures'.

• 5G networks
• Artificial intelligence
• Network programmability
• +3 more

Álvaro Hernández Alonso is a Full Professor in the Department of Electronics at the University of Alcalá (UAH). He previously served as Secretary of the Electronics Department and coordinated the GEINTRA research group (2021–2023), which includes 24 researchers and over 25 active projects. His research focuses on mobile robotics, multisensor integration, ultrasonic systems, NILM techniques, FPGA implementations, and electronic technologies for transport. Education: PhD in Electronics and Systems (University Blaise Pascal & UAH) Electronics Engineering Degree (UAH) Research interests include positioning systems (infrared, ultrasonic, visible light), energy monitoring for assisted living, and embedded hardware architectures. He has secured €1.9M in funding (public and private) over the past decade, leading 4 projects as Principal Investigator. His work has produced 41 indexed journal papers (25 Q1), 6 patents, and 65 conference contributions. Awards: Best Thesis Awards at UAH for two doctoral students under his supervision. He has advised 30+ student theses and 9 doctoral dissertations, many in international co-supervision programs. Funding highlights: 19 public projects (€900k total) and 10 private projects (€1.1M total). His research has achieved 4 consecutive positive evaluations (1997–2020) from Spain's National Research Evaluation Commission.

• Mobile Robotics
• Multisensor Integration
• Ultrasonic Sensory Systems
• +5 more

Carlos Alario Hoyos is an Associate Professor in the Department of Telematic Engineering at Carlos III University of Madrid, affiliated with the School of Engineering. His work bridges telematics and educational technology, focusing on learning analytics, generative AI, and digital learning environments. Current role: Associate Professor Research groups: GAST (Telematic Applications and Services), NETTEC (Network Technologies) Research interests include: AI-driven educational tools MOOC analytics and quality assessment Chatbot-based programming assistance Behavioral modeling in online learning Automated literature review systems Recent publications (2025-2024) analyze: Student performance prediction models Generative AI integration in education Micro-credentials and digital recognition Hybrid learning environments Telepresence classroom impacts Real-time educational analytics

• Educational Technology
• Artificial Intelligence in Education
• Learning Analytics
• +3 more

José L. Abellán is a Ramón y Cajal Fellow (Tenure-Track Associate Professor) and European R3 researcher at the University of Murcia's Department of Computer Engineering and Technology. He leads the EcoArTech research group and holds a Ph.D. in Computer Science from the University of Murcia (2012). His career includes postdoctoral positions at Boston University and previous faculty roles at Universidad Católica de Murcia. Dr. Abellán's research focuses on architectural enhancements for GPU systems and customized accelerators targeting machine learning and fully homomorphic encryption applications. His work spans hardware/software co-design, microarchitectural extensions for privacy-preserving computation, and efficient parallel processing. His extensive publication record demonstrates consistent contributions to GPU architecture, processing-in-memory, hardware acceleration for cryptography, and graph neural networks. Recent work has appeared in top computer architecture venues including MICRO, ASPLOS, and HPCA. Awards and Honors HiPEAC Paper Awards (2019, 2020, 2023, 2024) Best Paper Award at IPDPS 2011 Top Picks in Hardware and Embedded Security 2024 European R3 Certificate (2024) Dr. Abellán leads the EcoArTech research team and serves as Associate Editor for ACM Transactions on Architecture and Code Optimization (TACO) and Frontiers in Electronics. He is a Senior Member of IEEE and active in the HiPEAC European network.

• GPU Architecture
• Hardware Accelerators
• Machine Learning
• +3 more

Eduardo Corral Abad is an Associate Professor in the Department of Mechanical Engineering at Carlos III University of Madrid, specializing in multibody dynamics, railway systems, and contact mechanics. His research spans industrial heritage, vibration analysis, and educational technology. Railway axle monitoring and crack detection using advanced signal processing Dynamic modeling of mechanical systems with nonlinear contact and friction forces Development of interactive teaching applications for engineering education Use of parallel computing and GPU acceleration in mechanical simulations His contact email is eduardo.corral@uc3m.es . Recent work includes publications on railway diagnostics, helical gear transmissions, and Android-based educational tools.

• Mechanical Engineering
• Railway Systems
• Multibody Dynamics
• +3 more

Sebastián Sánchez Prieto is a Professor at the Department of Automatic Control, Universidad de Alcalá, Spain, affiliated with the Space Research Group (SRG-UAH). He holds a Doctorate from the same institution (1998) with a thesis on cosmic ion telescope control systems. His research focuses on space instrumentation, radiation detection systems, on-board data management, and embedded systems for space applications. He has contributed extensively to the Solar Orbiter mission, working on the Energetic Particle Detector (EPD) instrumentation and software validation. His technical expertise spans FPGA-based signal processing, RISC-V processor architectures, and model-driven engineering for space systems. Notable work includes advancing virtualization techniques for mixed-criticality space systems, digital beamforming architectures, and neural network applications in particle trajectory analysis. Publications emphasize cutting-edge topics like fault-tolerant computing in space environments, adaptive signal processing for space communications, and low-power positioning systems. He actively develops educational frameworks integrating on-board data management concepts across interdisciplinary university curricula. His contributions include over 50 peer-reviewed articles addressing hardware-software co-design, space software verification, and radiation effects mitigation. Current research explores AI-driven approaches for space instrumentation data analysis and next-generation on-board computing solutions.

• Space Instrumentation
• Radiation Detection
• On-Board Data Management Systems
• +5 more

Jose Vicente Frances Villora is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, University of Valencia, Spain. He is an active researcher in digital systems and biomedical signal processing, with a strong focus on real-time embedded systems and hardware acceleration. His research interests include: Biomedical Signal Processing, particularly ECG and microelectrode recordings FPGA-based hardware implementation of neural networks and real-time algorithms Machine learning applications in healthcare, including arrhythmia detection and Parkinson’s disease treatment Neuromorphic computing and spiking neural networks Digital signal processing in embedded and real-time systems The analysis of his recent publications (2017–2015) reveals a consistent focus on leveraging machine learning—especially KNN and neural networks—for clinical applications such as ventricular fibrillation detection and deep brain stimulation. A significant portion of his work emphasizes hardware implementation on FPGAs, aiming to achieve real-time performance and low resource consumption in medical and robotic systems. He has contributed to educational materials, including textbooks and OCW resources, and supervises academic theses. While no specific scientific awards are mentioned in the provided text, his sustained publication output and integration of theory with hardware systems underscore his technical expertise. He advises students in thesis work and has supervised doctoral research, though specific student names are not listed. His research is supported by practical applications in medical diagnostics and robotics, and he is affiliated with the GPDD (Group for Digital Design and Processing), which focuses on digital system design and processing. He is actively involved in laboratory development, including a remote laboratory for industrial robots, and his team works on co-design environments for neural network hardware, FPGA acceleration, and real-time biomedical systems.

• Biomedical Signal Processing
• Embedded Systems
• FPGA Hardware Implementation
• +7 more