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Antonio GonzálezView profile

Professor

• Computer Architecture
• Microarchitecture
• Compilers
• +7 more

Antonio González is a full Professor at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Architecture. He leads the Microarchitecture and Compilers (ARCO) research group, focusing on robust and energy-efficient computing systems, including general-purpose processors, GPUs, and cognitive computing architectures. His research spans computer architecture, microarchitecture, compilers, GPU design, and deep learning acceleration, with a strong emphasis on energy efficiency and memory optimization. His work integrates hardware and compiler techniques to enhance performance in modern computing systems. The recent publications highlight a strong trend in energy-efficient DNN acceleration, GPU microarchitecture, memory systems, and near-data processing. His team explores novel quantization methods, adaptive caching, and architectural extensions for vision and AI workloads, published in top-tier venues such as MICRO, ISCA, and IEEE/ACM journals. ACM Fellow (2020) ICREA Academia Award (2014, 2019, 2024) UPC Duran Farell Award (2008) HiPEAC 2024 Paper Award (twice) González has supervised several PhD students and leads competitive R&D+i projects, including those funded by ICREA and the European Research Council. His research group collaborates extensively within UPC and with international institutions. He is actively involved in advancing computer architecture through innovation in simulation, hardware design, and AI acceleration. He is a member of IEEE and ACM, and his work continues to influence both academic and industrial developments in high-performance and energy-efficient computing.

• In-memory computing for AI
• Neuromorphic computing
• Emerging resistive memory
• +3 more

Irem Boybat is a Researcher in the In-Memory Computing Group at IBM Research - Zurich, Switzerland, focusing on advanced AI hardware solutions. She holds a Ph.D. in Electrical Engineering from EPFL (2020) and prior degrees from EPFL and Sabanci University. Ph.D., Electrical Engineering, EPFL (2020) M.Sc., Electrical Engineering, EPFL (2015) B.Sc., Electronics Engineering, Sabanci University (2013) Her research bridges in-memory computing and AI, targeting energy-efficient hardware for deep learning and neuromorphic systems. Recent work explores analog AI accelerators, heterogeneous architectures, and scalable models for edge computing. Publications highlight cross-disciplinary innovation in materials, circuits, and system design. She has received the IBM Pat Goldberg Memorial Best Paper Award and EPFL PhD Thesis Distinction. Her invited talks span prestigious venues including the European Phase-Change Symposium, IEEE CICC, and HiPEAC. Collaborations include EU H2020 projects like MANIC and WiPLASH.

• Computational Neuroscience
• Spacetime Connectomics
• Neurotwin Models
• +5 more

Jakub Vohryzek is a postdoctoral researcher at the Computational Neuroscience (CNS) Group at University Pompeu Fabra in Barcelona, supervised by Prof. Gustavo Deco. His work focuses on spacetime connectomics and whole-brain modeling, particularly in neurodegenerative disorders and psychedelic neuroscience. He holds a DPhil from the University of Oxford, where he studied under Prof. Morten Kringelbach. Research Interests: Spacetime connectomics Psychedelic-induced brain state transitions Neurotwin models for personalized medicine Cognitive and clinical applications of whole-brain dynamics Current projects include developing neurotwin models under a European grant for neurodegenerative treatments, investigating brain state dynamics in mindfulness therapy, and modeling psychedelic effects on Alzheimer’s disease. His recent work emphasizes low-dimensional brain network interactions and functional hierarchy perturbations. His research has explored connectivity profiles, oscillatory restoration in dementia, and algorithmic agent approaches to neuropsychiatric disorders. He collaborates on open-science initiatives like Brainhack and advocates for inclusive conference design.

• Quantum Machine Learning
• Reinforcement Learning
• Medical Informatics
• +12 more

Jose David Martin Guerrero is a Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His research is conducted within the Intelligent Data Analysis Laboratory (IDAL), focusing on the intersection of quantum computing, machine learning, and biomedical applications. His research interests span Quantum Machine Learning , Reinforcement Learning for Quantum Control , Deep Learning for Medical Image Analysis , and Long-COVID Symptom Trajectory Modeling . He applies advanced AI techniques to solve complex problems in physics, healthcare, and engineering, particularly in modeling prostate cancer, hemodialysis, and post-COVID neurological and functional impairments. The recent publications highlight a strong trend toward integrating quantum computing with classical machine learning, especially in developing quantum neural networks, quantum autoencoders, and reinforcement learning for quantum gate optimization. Simultaneously, a significant body of work uses clustering, deep learning, and Bayesian modeling to analyze longitudinal clinical data from multicenter studies like LONG-COVID-EXP, aiming to understand symptom persistence and recovery patterns in post-COVID patients. Dr. Martin Guerrero earned his PhD from the Universitat de València in 2004 with a thesis on unsupervised techniques for web trend detection and collaborative filtering-based recommendation systems, supervised by Dr. Emilio Soria Olivas and Dr. Paulo Jorge Gomes Lisboa. His work demonstrates active collaboration across disciplines, particularly in clinical research involving multicenter studies, and in quantum computing applications in physics and finance. While no specific grants are mentioned, his involvement in large-scale clinical studies and quantum computing research suggests significant project leadership and funding acquisition. He leads research within the Intelligent Data Analysis Laboratory (IDAL) , which focuses on self-organizing maps, clustering, learning vector quantization, and their applications in security, healthcare, and quantum systems.

Antonio Calomarde PalominoView profile

Associate Professor

• Low Power Digital Circuits
• Soft Error Resilient Circuits
• Integrated Circuit Design
• +4 more

Antonio Calomarde Palomino is an Associate Professor at the Department of Electronic Engineering, Polytechnic University of Catalonia (UPC), located at the Higher Technical School of Industrial Engineering of Barcelona. He holds a B.S. in Telecommunications Engineering (UPC, 1986), an M.S. in Electronic Engineering (Universitat Autònoma de Barcelona, 1993), and a Ph.D. in Electronic Engineering (UPC, 2007) with honors. His research focuses on low-power/high-performance digital circuits and soft-error resilient designs, addressing challenges in semiconductor technology and radiation-hardened electronics. Key research areas include FinFET-based memory cells, RRAM modeling, and radiation mitigation strategies for advanced nanoelectronics. He contributes to the High Performance Integrated Circuits and Systems Design (HIPICS) Group, advancing circuit design methodologies and educational initiatives such as integrating autonomous vehicle systems into undergraduate curricula. His work bridges theoretical advancements with practical applications in automotive electronics and embedded systems. Publications span topics from memristor-based associative memory to approximation techniques in object detection systems, reflecting a balance between fundamental research and applied engineering. His recent work emphasizes variability-aware design and energy-efficient architectures, as seen in 2023-2024 studies on RRAM models and automotive case studies. Calomarde actively organizes academic events like the 2022 ETS conference and develops educational materials for digital electronics and audiovisual systems courses. His contributions to both technical research and pedagogical innovation solidify his role as a key figure in electronic engineering education and innovation.

José María Guerrero RodríguezView profile

Professor

• Electronics
• Sensor Design
• Space Instrumentation
• +3 more

José María Guerrero Rodríguez serves as a Professor in the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cadiz, Spain. His research is anchored within the TIC138 Electronic and Electromagnetic Design group under the PAIDI Areas for Information and Communication Technologies, focusing on advanced instrumentation systems for space and industrial applications. He completed his doctorate at the University of Cadiz in 2009 with the thesis A contribution to reconfigurability in intelligent instrumentation based on sensors and programmable devices , supervised by Dr. Diego Gómez Vela. His educational background forms the foundation for his expertise in sensor reconfigurability and programmable device integration. Guerrero Rodríguez's research spans Electronics, Embedded Systems, and Space Instrumentation, with significant contributions in magnetic measurement subsystems for CubeSats, low-frequency noise reduction in orbital environments, and neuromorphic sensor design. His work bridges theoretical electromagnetic modeling with practical embedded implementations, particularly in spiking neuron-based movement classification and optical flow algorithms for real-time tracking. Educational innovation is a secondary focus, evidenced by flipped classroom methodologies in analog electronics instruction. Analysis of his 2020-2024 publications reveals three dominant trends: (1) Space instrumentation for CubeSats emphasizing magnetic field measurement accuracy, (2) Novel sensor architectures using asynchronous vision and spiking neurons for flame detection and movement tracking, and (3) Educational technology integration in engineering pedagogy. These areas demonstrate consistent progression from fundamental sensor design to in-orbit validation. No scientific awards were documented in the provided source material. While the source references thesis supervision and funding sections, specific student names, grant details, or advising methodologies remain undisclosed. His research direction suggests ongoing collaboration with space technology initiatives, particularly in low-technology-readiness-level subsystem validation. Guerrero Rodríguez operates within the TIC138 research group, which specializes in electronic and electromagnetic design for aerospace applications. The group's work centers on advancing the technological maturity of measurement systems through CubeSat platforms, with recent focus on in-orbit demonstrators for magnetic field characterization in low-Earth orbit environments.

• Microelectronics
• Image Sensors
• Bio-inspired Algorithms
• +3 more

Juan Antonio Leñero Bardallo is a Professor at the University of Seville, Faculty of Physics, Department of Electronics and Electromagnetism. His research focuses on bio-inspired microelectronics, event-driven vision sensors, and CMOS integration techniques. Research Group: MICROELECTRÓNICA ANALÓGICA Y DE SEÑAL MIXTA Key Projects: SAMANTA2 (robotic vision), CAVIAR (event-based vision), VULCANO (event-driven imaging) His work spans asynchronous image sensors, thermography for medical diagnostics, stacked diodes for energy harvesting, and neuromorphic engineering. Recent publications highlight low-power sun sensors, self-powered imaging systems, and thermographic applications in dermatology. He has contributed to books on analog electronics and radiation detection. Patents include solar position sensors and electron energy detectors for scanning electron microscopy. His teaching subjects cover experimental techniques, integrated sensor design, and bio-inspired algorithms.

Juan Andrade CettoView profile

Researcher

• Mobile Robotics
• Computer Vision
• Neuromorphic Systems
• +3 more

Juan Andrade Cetto is a Researcher at the Institute of Robotics and Industrial Informatics (IRI), part of the Spanish National Research Council (CSIC). He previously served as Director of IRI from 2014 to 2020. His expertise spans mobile robotics, computer vision, and neuromorphic systems. He holds a BSEE from CETYS University (1993), an MSEE from Purdue University (1995), and a PhD in Robotics from the Universitat Politècnica de Catalunya (UPC, 2003), recognized with the EURON Georges Giralt Best PhD Award in 2005. Research Interests: - Mobile Robotics and Autonomous Systems - Event-based Vision and Neuromorphic Sensors - Real-time Sensor Fusion and SLAM - Control Systems for Energy Conversion (e.g., PEM Fuel Cells) - Probabilistic Methods for Robotics and Computer Vision Recent Research Trends: His work emphasizes neuromorphic computing and event-based systems for robotics applications, including optical flow estimation, ego-motion tracking, and real-time SLAM. Collaborations include EU projects like ALLIES (AI for Sustainable Development Goals) and RAMON LLULL (AIRA Postdoctoral Programme). He leads the BOMBUS project (Perception and Navigation for Agile Robotics, 2024–present). Scientific Awards: EURON Georges Giralt Best PhD Award 2005 Grants & Leadership: Principal Investigator in multiple national/EU projects including BOMBUS (CSIC) and ALLIES (European). Advising: - Current Students: José Agustín Aguilar Plazaola (Fuel Cell Control), Raquel De Frutos Arranz (Event Camera-based Collision Avoidance) - Past Students: Not explicitly listed in provided text. Labs & Teams: Active in IRI’s Robotics and Industrial Informatics research groups, focusing on applied robotics and sensor systems.

Eugenio Miguel Isern RiutortView profile

Senior Lecturer

• Microelectronics
• Integrated Circuit Testing
• Sensor Design
• +5 more

Dr. Eugenio Miguel Isern Riutort serves as a Senior Lecturer in the Department of Electronic Technology within the School of Industrial Engineering and Construction at the University of the Balearic Islands (UIB). His academic profile shows active engagement across multiple degree programs including Automation and Industrial Electronic Engineering, Telematics Engineering, and the Master's Degree in Industrial Engineering, where he teaches core courses in Analogue Electronics, Electronic Instrumentation, and related subjects. Beginning his research career in January 1991 with a pre-doctoral scholarship from the Ministry of Education and Science at the Polytechnic University of Catalonia, Dr. Isern Riutort has established three primary research domains. His foundational work focuses on test and verification methodologies for integrated circuits, where he has developed techniques for fault detection through current consumption analysis (both static IDDQ and dynamic IDDT). This research has evolved to address challenges posed by technological parameter variations in modern microelectronics, leading to innovations in predictive testing, oscillation-based testing, and auto-tuning techniques. A second research stream involves designing radiation sensors using standard MOS integrated circuits, with recent work focusing on floating gate MOS transistors that produce outputs proportional to total ionizing dose. Most recently, he has been developing non-conventional computing methodologies accelerated in hardware to enable artificial intelligence applications for massive and highly complex problems. His publication record demonstrates consistent scholarly output across these domains, with particular emphasis on practical applications of theoretical concepts in microelectronics testing and sensor design. The articles reflect a progression from fundamental circuit testing techniques to specialized applications in radiation detection and, most recently, hardware acceleration for AI systems. His work bridges theoretical foundations with experimental validation, as evidenced by his focus on both fault modeling and sensor design with experimental measurements. Dr. Isern Riutort actively supervises Final Degree Projects and Master's Theses in Automation and Industrial Electronic Engineering while teaching across multiple programs. His teaching portfolio spans from foundational Analogue Electronics courses to advanced Electronic Instrumentation Systems, demonstrating comprehensive expertise across the electronics curriculum. He maintains a personal academic website (personal.uib.eu/eugeni.isern) and has established research profiles across major academic networks including ORCID, ResearcherID, Scopus, and Dialnet. As a member of the Electronic Engineering (GEE) Consolidated R+D+I Group at UIB, he participates in a collaborative research framework that supports his work in electronics and related technologies. His office is located in room F107 on the first floor of the Mateu Orfila i Rotger building (Physics building) at the university.

Víctor López DomínguezView profile

Assistant Professor

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

• Magnetism
• Nanomaterials
• Magneto-ionics
• +3 more

Enric Menendez Dalmau is a Professor in the Department of Physics at the University of the Balearic Islands, leading the Group of Smart Nanoengineered Materials, Nanomechanics, and Nanomagnetism (Gnm3). His research focuses on magnetism, nanomaterials, and magneto-ionics, with applications in energy storage, data security, and neuromorphic computing. He has been Principal Investigator on multiple EU-funded projects, including the ERC Proof of Concept grant for flexible substrate-based magneto-ionic devices and the NICKEFFECT initiative to develop nickel-based magnetic coatings. His doctoral thesis (2008) explored generating ferromagnetism in non-magnetic materials, a foundational work in his career. He has supervised 9 research projects and 75 publications, including high-impact works in Advanced Materials and Small Science . His current work emphasizes voltage-tunable magnetism, defect engineering, and optical control of magnetic properties in multiferroic systems. Key collaborations include international teams on magneto-ionics for synaptic devices and energy-efficient data storage systems. His projects aim to address UN Sustainable Development Goals related to affordable clean energy and industry innovation.

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

Sonia BuckleyView profile

Researcher

• Quantum communications
• AI measurement and evaluation
• Hardware for AI
• +5 more

Sonia Buckley is a Researcher at the National Institute of Standards and Technology (NIST) , affiliated with the Sources and Detectors Group . Her work bridges quantum communications , neuromorphic computing , and hardware for AI , focusing on measurement techniques and benchmarking services for emerging technologies. She received her academic training at Trinity College Dublin and Stanford University , where she earned advanced degrees in Physics and Applied Physics. B.A. in Physics (2009, Trinity College Dublin) M.S. in Electrical Engineering (2014, Stanford University) Ph.D. in Applied Physics (2014, Stanford University) Her research explores heterogeneous hardware for next-generation computing, including photonic integrated circuits and waveguide-coupled single photon detectors . She leads initiatives in quantum radiometry and contributes to neuromorphic technology benchmarking , aiming to align hardware design with commercial viability. Her work integrates NIST's metrology expertise with cutting-edge AI and quantum systems. Sonia has received prestigious awards, including the National Research Council RAP Award (2015) and National Science Foundation Graduate Fellowship (2009). She holds multiple patents for hardware innovations, such as optoelectronic neural networks and thermal impedance amplifiers. Her contributions emphasize the development of application-specific hardware for AI and quantum communication systems.

• Systems Engineering
• Automation
• Neuromorphic Artificial Intelligence
• +2 more

Salvador Cañas Moreno is a Lecturer at the University of Cádiz, affiliated with the School of Engineering and the Department of Automation, Electronics, Architecture and Computer Networks Engineering. His research focuses on Systems Engineering and Automation, with a particular emphasis on neuromorphic AI applications in real-time data collection and sports scouting. Research Interests: Systems Engineering Automation Neuromorphic Artificial Intelligence VLSI Design Sports Technology Education: Doctorate in Systems Engineering and Automation from the University of Seville (2025), thesis: "A VLSI-based contribution to real-time data collection using neuromorphic AI: an application to sports scouting" Supervision: Supervised by Dr. Elena Cerezuela Escudero and Dr. José Antonio Ríos Navarro.

Juan NúñezView profile

Research Professor

• Tunnel Field-Effect Transistors (TFET)
• Low-power electronics
• Emerging semiconductor technologies
• +6 more

Juan Núñez is a Research Professor at the Microelectronics Institute of Seville (IMSE-CNM), part of the Spanish National Research Council (CSIC). His primary research focus lies at the intersection of emerging semiconductor technologies and novel computing paradigms, with particular expertise in tunnel field-effect transistors (TFETs) and their applications in low-power circuit design. Institution: Spanish National Research Council (CSIC) Research Institute: Microelectronics Institute of Seville (IMSE-CNM) Specialization: TFET, Pipeline, Variability, Low-power, Emerging technologies, RTD, NDR, Emerging devices, Dynamic logic Professor Núñez's research portfolio demonstrates a strong evolution from traditional digital circuit design toward emerging computing paradigms. His early work focused on optimizing conventional CMOS circuits and exploring tunnel transistors as potential successors to traditional MOSFETs. More recently, his research has pivoted toward neuromorphic computing, particularly oscillatory neural networks and Ising machines implemented with emerging devices. His work bridges the gap between device physics, circuit design, and computational applications, with a consistent emphasis on energy efficiency. The trend in his recent publications (2020-2024) shows a significant shift toward neuromorphic computing applications, particularly using phase transition materials and oscillatory networks for solving complex optimization problems. His research on VO 2 (vanadium dioxide) based Ising machines represents cutting-edge work in non-von Neumann computing architectures that could potentially solve NP-hard problems more efficiently than conventional computers.