جست‌وجوی استاد و پژوهشگر

• Electronic systems
• Biomedical engineering
• Electronic instrumentation
• +۳ مورد دیگر

Eduardo Alonso Rivas is an Assistant Professor (Doctor Level 3) in the Department of Electronics, Automation and Communications at the Higher Technical School of Engineering (ICAI) , Comillas Pontifical University , Madrid. With 13 years of teaching experience and recent appointment as Professor in 2023, he specializes in electronic systems, biomedical engineering, and instrumentation. Education PhD in Industrial Engineering, Comillas Pontifical University, 2023 MSc in Engineering Systems Modeling, Comillas Pontifical University, 2015 Industrial Engineering Degree, Comillas Pontifical University, 2009 Degree in Automation & Industrial Electronics, Comillas Pontifical University, 2009 Research Interests Dr. Alonso Rivas focuses on the convergence of electronics and biomedical applications. His work spans intraoperative neurophysiological monitoring systems , fast-settling biosignal amplifiers , skin–electrode interface characterization , and portable impedance-based health monitors . He also investigates power-line communication strategies for smart-grid metering, illustrating a dual expertise in clinical electronics and industrial communications. Publication Focus Across seven peer-reviewed articles (2014-2022), his research follows two dominant threads: (1) biomedical instrumentation —designing wireless, low-noise devices for real-time neural monitoring and diagnostics; (2) power-line communications —optimizing latency and polling strategies in PRIME-based smart-meter networks. This duality underscores a commitment to both cutting-edge healthcare technology and sustainable energy systems. Scientific Awards No specific awards or fellowships are listed in the provided text. Teaching & Supervision Since 2010 he has taught Electronics , Digital Electronics , Microprocessors , Electronic Systems , and Biomedical Instrumentation , as well as supervising Master theses. He progressed from Assistant Collaborator to full Professor in 2023, demonstrating sustained pedagogical commitment. Laboratory & Team Affiliation While explicit laboratory names are not provided, his affiliation with the Department of Electronics, Automation and Communications and prior research at the Technological Research Institute suggests active participation in instrumentation and communications laboratories within ICAI.

• Robotics
• Control Systems
• Automation
• +۱۰ مورد دیگر

ABDERRAHIM FICHOUCHE, MOHAMED is an Associate Professor in the Department of Systems Engineering and Automation at the Carlos III University of Madrid (UC3M), where he also serves as Deputy Director of the Doctorate. He is affiliated with the Robotics Lab research group and the Pedro Juan de Lastanosa Institute of Technology Development and Innovation. His academic and research profile spans robotics, control systems, biomedical engineering, and power systems. His research interests include robotics , automation , control systems , biomedical signal processing , computer vision , and renewable energy integration . His work focuses on intelligent robotic systems, rehabilitation robotics, EEG-based brain-computer interfaces, fault detection in power systems, and advanced control strategies for industrial and autonomous systems. The recent publications reflect a strong trend in interdisciplinary research, combining machine learning with signal processing for applications in medical diagnostics , robotic control , and smart grid monitoring . His work increasingly integrates deep learning , wavelet analysis , and adaptive control across domains. He has led major research projects such as: HANDLE (EU and national funding): Focused on dexterous in-hand manipulation. SARAH: Enhancing robot autonomy with artificial hands. PAPREC: Automatic grasping of disordered parts. PROSAVE: Eco-efficient aircraft systems. GRAND-PA: Assistive technologies for the elderly. He currently participates in ongoing projects including: SEGVAUTO5G-CM (2025–2028): Future mobility innovation. RoboCity2030-DIH-CM (2019–2023): Madrid Robotics Digital Innovation Hub. HYPER: Neuroprosthetic and neurorobotic devices for rehabilitation. He has supervised several theses on topics such as transmission line fault detection , autonomous decision-making in robots , and 3D perception . His research is conducted primarily within the Robotics Lab at UC3M, a multidisciplinary team focusing on advanced robotic systems for industrial, medical, and service applications.

• Biomedical Signal Processing
• Embedded Systems
• FPGA Hardware Implementation
• +۷ مورد دیگر

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.

• Signal Processing
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Elias Marqués Valderrama is a Professor at the University of Seville in the Department of Signal Theory and Communications . His research is centered around radiocommunication systems and signal processing. Research focus: Signal Processing , Machine Learning , and Microwave Engineering Projects: Integration of statistical signal modeling and data-driven learning for brain-machine interfaces , and AI for emotion recognition . Fellowship: Arftg Roger Pollard Student Fellowship in Microwave Measurement . His publications highlight work on power amplifier modeling , digital predistortion , and EEG-signal databases using virtual reality . Collaborations include researchers like Juan Antonio Becerra González and Miguel Nogales González-Regueral . Key technical areas span nonlinear behavioral modeling , orthogonal matching pursuit , and virtual reality-based emotion analysis .

Jose L Contreras-Vidalمشاهده پروفایل

استاد

• Brain-machine interfaces
• Neurotechnology
• Biomedical Engineering
• +۴ مورد دیگر

Dr. Jose 'Pepe' L Contreras-Vidal serves as the Hugh Roy and Lillie Cranz Cullen Distinguished Professor and director of the U.S. National Science Foundation Industry-University Cooperative Research Center for Building Reliable Advances and Innovations in Neurotechnology (IUCRC BRAIN) at the University of Houston. An elected Fellow of both IEEE and AIMBE, his pioneering work bridges neuroscience, engineering, and art. His research focuses on developing brain-machine interfaces for controlling wearable exoskeletons for rehabilitation and mapping art-evoked brain activity. Dr. Contreras-Vidal's interdisciplinary approach explores the neural basis of human creativity while advancing understanding of arts as active neuromodulators of brain function, with applications to personalized arts prescriptions. His recent work includes leading the first comprehensive knowledge integration assessment of clinical trials of implantable brain-computer interfaces, published in Nature Reviews Bioengineering. His art-science team received the Chamber Music America's 2025 Interdisciplinary Collaboration of the Year award for 'Meeting of Minds', which was performed at the United Nations' 2024 AI for Good Summit in Geneva. Fellow of IEEE Fellow of AIMBE Chamber Music America's 2025 Interdisciplinary Collaboration of the Year Dr. Contreras-Vidal serves on the National Advisory Board for Medical Rehabilitation Research at the U.S. National Institute of Health. His career development in biomedical engineering was highlighted by the journal Science, underscoring his significant contributions to the field.

• Signal Processing
• Communications Engineering
• Biomedical Signal Processing
• +۴ مورد دیگر

Dr. Jesús Bernardino Alonso Hernández is a Professor in the Department of Signals and Communications at the University of Las Palmas de Gran Canaria , affiliated with the College of Engineering . His research spans signal processing, biomedical applications, and communications engineering, with a focus on real-time systems and acoustic analysis. Key research areas include: Speech processing for Alzheimer's detection Neural network design for hardware acceleration Biometric identification via neural signatures Acoustic methodologies for voice and machinery diagnostics Markovian transformations in shape recognition He has supervised doctoral theses in diverse topics such as: Reverse emission techniques for musical instruments Cellophane-based vocal emission analysis Vibration signal monitoring for preventive maintenance Task-independent brainwave identification Markovian contour transformation methodologies

José M. Azorínمشاهده پروفایل

استاد

• Brain-Machine Interfaces
• Neuro-robotics
• Rehabilitation Robotics
• +۵ مورد دیگر

José M. Azorín is a Full Professor and Director of the Brain-Machine Interface Systems Lab at Miguel Hernández University of Elche (Spain) . He holds a Ph.D. in Robotics (2003) and a M.Sc. in Computer Science (1997). His research focuses on Brain-Machine Interfaces (BMIs), Neuro-robotics, and Rehabilitation Robotics, with over 200 publications and 3 patents. He leads the NSF IUCRC BRAIN UMH Site and serves as a Distinguished Lecturer for the IEEE Systems Council and Core Team member of the IEEE Brain Initiative. Education: PhD in Robotics: Summa Cum Laude (2003), Miguel Hernández University MSc in Computer Science (1997), University of Alicante Research Interests: Azorín pioneers BMI-driven robotic exoskeletons for mobility-impaired individuals. His work integrates EEG-based control systems, neurorehabilitation protocols, and bioinspired robotics. Key areas include lower/upper limb exoskeleton control, sensory-motor decoding, and EU-funded initiatives like the BioMot project. He emphasizes cross-border collaboration through networks like Reasiste and Iberada. Projects & Funding: Over 20 projects since 2000, including Horizon 2020-funded DECODED/REKINE (2021–2022) and Spanish Ministry grants like WALK (2019–2021). His work addresses clinical needs via wearable robots, multimodal interfaces, and low-cost solutions for neurorehabilitation. Awards & Leadership: Best Thesis Award (2003) IEEE Distinguished Lecturer (2013–) Core Team IEEE Brain Initiative Organized major conferences like ICNR and WeRob Grants & Labs: Coordinates the Brain-Machine Interface Lab and secured €10M+ in EU/Spanish funding. His team develops open-source BMI frameworks and collaborates with Imperial College London and University of Houston.

• Computer Science
• Medical Imaging
• Nuclear Medicine
• +۳ مورد دیگر

Mario Cañadas Castro is an Adjunct Professor at the University Carlos III of Madrid, with a multidisciplinary research portfolio spanning serious games, medical imaging technologies, and computational physics. His work includes the EU-funded RAYUELA project addressing cybercrime through gamification, development of the GAMOS simulation framework for nuclear medicine applications, and advancements in PET scanner technology using CdTe detectors. His research also intersects psychosocial studies in healthcare, analyzing nurse well-being in critical care settings and sleep patterns in university populations. Key contributions include pioneering frameworks for Geant4 simulations and optimizing PET imaging systems under NEMA standards. He has authored over 50 publications on topics ranging from ion-beam surface patterning to AI-driven serious games for social challenges. His interdisciplinary approach bridges computer science, biomedical engineering, and materials science. Notable projects include the H2020 RAYUELA initiative (2021) and foundational work on pixelated CdTe detectors for brain PET scanners (2013). His research trends emphasize computational tools for healthcare innovation and leveraging serious games for societal issues like cyberbullying prevention. No scientific awards are listed, but his extensive publication record reflects significant contributions to multiple fields. Advising and grant details are not specified in available records. His work has implications for both academic and applied domains, including EU policy initiatives and clinical healthcare technology advancements.

• Parallel Computing
• High-Performance Computing (HPC)
• Programming Models
• +۶ مورد دیگر

Maria Luisa Gil Gómez is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture and the Barcelona Higher Technical School of Telecommunications Engineering. She holds a PhD in Computer Science and leads research in parallel computing, high-performance computing (HPC), and programming models. Her work focuses on optimizing computational workflows, fault tolerance in distributed systems, and leveraging multi-GPU architectures for scientific simulations. She has contributed to projects like the Programming Models group (PM) at UPC and collaborates with the Barcelona Supercomputing Center (BSC-CNS). Affiliations: UPC Department of Computer Architecture, BSC-CNS, PM Research Group Research Interests: Parallel Programming Models, HPC, GPU Computing, Cellular Automata, Education Technology Her research spans over 147 documented activities, including journal articles, conference presentations, and funded projects. Notable contributions include studies on BCI in music education, distributed algorithms for ARM-based clusters, and the OpenCAL++ framework for parallel cellular automata simulations. She has also explored educational methods integrating creativity and game-based learning in engineering.

Lorenzo Montillaمشاهده پروفایل

پژوهشگر

• Neural Interfaces
• Neuroengineering
• Brain-Computer Interfaces
• +۳ مورد دیگر

Lorenzo Montilla serves as a Researcher at IMDEA Nanoscience Institute in Madrid, Spain, joining the institution in February 2024 as an Early Stage Researcher within the Neural Interfaces group. His work integrates nanotechnology with neural system interfacing under the institute's research programs. His primary research domains include Neural Interfaces, Neuroengineering, and Brain-Computer Interfaces, focusing on nanoscale device development for high-resolution neural recording and stimulation. This aligns with IMDEA's strategic emphasis on nanotechnology applications in neuroscience, leveraging advanced fabrication techniques to bridge electronic systems with biological neural networks. As part of the Early Stage Researchers cohort, Montilla utilizes the institute's Center for Nanofabrication and specialized laboratories to advance neural interface technologies, contributing to IMDEA's mission in nanoscience innovation.

• Machine Learning
• Computer Vision
• Affective Computing
• +۷ مورد دیگر

Antonio Fernández-Caballero is a Full Professor at Universidad de Castilla-La Mancha in the Departamento de Sistemas Informáticos , with a career spanning since 1996. His academic contributions focus on interdisciplinary research at the intersection of Computer Science, Neuroscience, and Human-Computer Interaction. Primary affiliation: Universidad de Castilla-La Mancha Department: Sistemas Informáticos Academic rank: Professor His research interests include affective computing, machine learning, computer vision, and applications in healthcare and smart cities. He has published extensively on emotion recognition using EEG/fNIRS signals, robot gesture interpretation for autism therapy, and domain-specific generative AI for medical simulations. Recent publications highlight his work in extended reality for rehabilitation, IoT solutions for elderly care, and systematic reviews on deep learning for defect detection and smart city societal aspects. Collaborations span institutions in Spain and Portugal, with cross-disciplinary applications in medical informatics, robotics, and smart environments.

• Rehabilitation Robotics
• Exoskeleton Design
• Stroke Rehabilitation
• +۴ مورد دیگر

Andrea Blanco Ivorra serves as Assistant Professor in the Department of Materials Science, Optics and Electronic Technology at Miguel Hernández University of Elche, where she teaches Strength of Materials across Electrical, Electronic, and Mechanical Engineering programs. She holds the position of Chair Secretary for the Chair of Advanced Technologies for Rehabilitation, focusing on developing innovative rehabilitation technologies. Her research centers on rehabilitation robotics and neuroengineering, with emphasis on exoskeleton design for upper limb motor rehabilitation, stroke recovery, and assistive technologies for aging populations. She integrates EEG monitoring, biomechanical analysis, and machine learning to create intelligent systems that enable longitudinal assessment and adaptive therapy protocols. Her work bridges clinical rehabilitation with engineering innovation to improve motor function outcomes. Recent publications reveal a cohesive research trajectory in developing and validating robotic rehabilitation systems, with particular focus on home-based solutions, brain-computer interfaces, and personalized therapy adaptation. Her 2024-2025 output demonstrates strong interdisciplinary collaboration across neuroscience, mechanical engineering, and gerontechnology, with consistent emphasis on practical clinical implementation and user-centered design. Dr. Blanco Ivorra's affiliation with the Chair of Advanced Technologies for Rehabilitation drives her work in translating engineering innovations into real-world rehabilitation applications, particularly through the ROAD tele-rehabilitation platform and bimanual exoskeleton systems for daily living assistance.

Tania Mondéjarمشاهده پروفایل

دانشیار

• Neuropsychology
• Educational Technology
• Cognitive Neuroscience
• +۵ مورد دیگر

Dr. Tania Mondéjar is an Associate Professor in the Department of Psychology at the University of Castilla-La Mancha (UCLM), Faculty of Education. She holds a PhD and postgraduate degree in Neuropsychology. As director of eSmile, a specialized psychology clinic for neurodevelopment and new technologies, she focuses on integrating digital tools into clinical practice. She also leads the MAmI Research Lab, contributing to eHealth, serious games, and neurosciences research. Her education includes degrees in Psychology from UCLM, with advanced studies in Neuropsychology. Her research interests span affective computing, autism spectrum disorder diagnostics, cognitive load analysis using EEG, and proactive robotics in healthcare and education. She collaborates internationally on projects like the holistic care system using affective robots and the mPLiCA conversational model. Her recent work emphasizes interdisciplinary approaches combining neurotechnology with education and healthcare. Key contributions include predictive autism models, empathy assessment frameworks, and augmented feedback systems for classrooms. Her research bridges clinical needs with technological innovations, addressing aging populations, neurodevelopmental disorders, and educational equity through digital solutions. Her lab’s MAmIoTie project exemplifies this fusion, developing sensorized toys for mood disorder support. Current initiatives focus on context-aware assistive systems and gamification mechanics for behavioral change. Despite no listed awards, her extensive publication record reflects impactful contributions to multiple fields.

• Machine Learning
• Approximate Inference
• Optimal Control
• +۶ مورد دیگر

Vicenç Gómez is an Associate Professor in the Department of Engineering at Universitat Pompeu Fabra (UPF), where he leads research in artificial intelligence and machine learning. He serves as Coordinator of the Erasmus Mundus Joint Master in Artificial Intelligence and the MSc program in Intelligent and Interactive Systems, and teaches in the BSc in Mathematical Engineering in Data Science. His research interests include machine learning, approximate inference, optimal control, and complex networks , with applications in social networks, robotics, brain-computer interfaces, and urban systems. He applies advanced AI techniques to model human behavior, network dynamics, and decision-making processes. The recent publications highlight a strong focus on graph-based learning, reinforcement learning, social network analysis, and health informatics . His work integrates theoretical advances in probabilistic modeling with real-world applications in digital platforms, environmental monitoring, and mental health. There is a consistent theme of modeling complex systems through structured AI and interpretable models. Scientific Awards and Recognition: Coordinator of the prestigious Erasmus Mundus Joint Master in Artificial Intelligence Local Chair of UAI 2024, a top-tier conference in AI Program Committee member for ICAPS 2024 Organizer of the EMAI Summer School in collaboration with UCL Advising and Grants: Vicenç Gómez actively supervises PhD and Master's students, including Nur Alvarez-Gonzalez, Roger Garriga, Emily Theophilou, and Sergio Calo. His advising spans topics in emotion detection, mental health modeling, air quality prediction, and representation learning. He has been involved in organizing major academic events and leading international educational programs, indicating significant leadership and collaborative grant activity. Labs and Research Groups: He is a key member of the Artificial Intelligence and Machine Learning group at UPF’s Department of Engineering, based at the Roc Boronat building in Barcelona. His team engages in interdisciplinary research combining AI theory with applications in social, health, and urban domains.

• Human-Computer Interaction
• Educational Technology
• Collaborative Systems
• +۶ مورد دیگر

Ana I. Molina is a Full Professor at the University of Castilla-La Mancha since February 2024, specializing in Information Technologies and Systems. She holds a PhD in Computer Engineering (2007) and a Computer Engineering degree (2002) from the same university, along with a Psychology degree (2019) from the National University of Distance Education (UNED, Spain). PhD in Computer Engineering (2007) Computer Engineering degree (2002) Psychology degree (2019) Her research focuses on Human-Computer Interaction , Educational Technology , and Collaborative Systems , with a strong emphasis on Eye Tracking and Usability . Recent work explores Augmented Reality and Mobile Applications for Autism Spectrum Disorder (ASD) and physical rehabilitation. She has contributed to frameworks like MultiTEA for ASD applications and Learn-CIAM for collaborative learning tools. Her publications (15 most recent) span journals like Multimedia Tools and Applications , Journal of Systems and Software , and Universal Access in the Information Society . Topics include Algorithmic Learning , Gender Bias in Computing , and Medical Gamification . While no formal awards are listed, her extensive peer review activity (Applied Sciences, Brain Sciences, Sensors) highlights her academic engagement.