جست‌وجوی استاد و پژوهشگر

• Healthcare Informatics
• Artificial Intelligence
• Cybersecurity
• +۳ مورد دیگر

José Amelio Medina Merodio is a Full Professor at the Universidad de Alcalá (UAlcala), leading research in Computer Science and Artificial Intelligence within the Department of Computer Science. His work focuses on healthcare informatics, cybersecurity, educational technology, and metaverse applications. He is affiliated with the MISKC (Healthcare Informatics Research) and TIFyC (Information Technologies for Training and Knowledge) research groups, previously contributing to the PMI (Intelligent Mobile Platforms) group. He holds two doctorates: from UAlcala (2017) with a thesis on quality improvement through ICT, and Universidad Rey Juan Carlos (2010) focusing on AI-driven quality systems. His research explores AI ethics in tourism, cybersecurity for hardware wallets, and gamification in collaborative learning environments. Recent publications address metaverse value creation, personalized MOOC feedback, and intergenerational leadership. He has contributed to frameworks for software quality evaluation and maintenance systems in industrial environments. Notable projects include ESCOGPT (AI-driven job search tool) and Triage Start (trauma classification system). His work emphasizes technology application in healthcare, education, and cybersecurity, with a focus on practical solutions for industry challenges. Despite no explicit mention of awards, his extensive publication record and active research groups reflect significant contributions to multiple fields.

• Artificial Intelligence
• Machine Learning
• Healthcare Technology
• +۶ مورد دیگر

Alberto Nogales Moyano is a Lecturer at the Department of Computer Science at the University of Alcalá. He holds a PhD in Computer Science from the same institution, completed in 2018, with a thesis titled A structural and quantitative analysis of the web of linked data and its components to perform retrieval data , supervised by Dr. María Elena García Barriocanal and Dr. Miguel Ángel Sicilia Urbán. His research focuses on AI applications in healthcare, data science, and cultural heritage preservation, with notable work on deep learning models for medical imaging, EEG analysis, and architectural restoration. Key research interests include artificial intelligence techniques for mental health assessment (e.g., lockdown impact studies during the pandemic), medical diagnostics using hybrid AI models, and optimizing deep learning frameworks for diverse domains like food safety and noise suppression. He also contributes to open-source tools such as EEGraph (for electroencephalogram analysis) and explores GAN-based approaches for virtual reconstruction of historical structures. His publications span topics such as self-organizing maps for data imbalance, BERT-based EEG analysis for Parkinson’s disease, and systematic reviews of deep learning’s role in physiotherapy and neurology. He actively engages in interdisciplinary projects combining machine learning with healthcare, sociology, and architecture, demonstrating a commitment to both methodological innovation and practical societal impact.

• Particle Physics
• Signal Processing
• Space Technology
• +۵ مورد دیگر

Alberto Regadío Carretero is a Lecturer in the Department of Automática at the University of Alcalá, affiliated with the Space Research Group (SRG-UAH). His research focuses on signal processing for particle detection, cosmic ray physics, and the integration of advanced computing techniques like neural networks and IoT technologies into experimental instrumentation. He holds a PhD in Digital Signal Processing applied to particle detection, awarded in 2014. Education: PhD in Digital Signal Processing, University of Alcalá (2014) Thesis: Procesamiento digital de señal aplicado a la detección de partículas energéticas , supervised by Dr. Sebastián Sánchez Prieto and Dr. Jesús Tabero Godino Research Interests: His work bridges particle physics, space technology, and computational methods. Key areas include: Design of radiation detectors and data acquisition systems using FPGAs and IoT Analysis of cosmic ray spectra and atmospheric effects Application of machine learning (e.g., GANs, reservoir computing) to pulse detection and unfolding Hardware optimization for precision signal processing in space and high-energy environments Key Contributions: Recent work includes: Quantum computing approaches for exoplanet discovery Development of neutron monitors and trajectory tracking systems (e.g., MITO) Unfolding techniques for particle spectra using deep learning Awards & Grants: No specific awards or grants are mentioned in the text, but his involvement in projects like ORCA and the Space Research Group suggests active grant-based research. Lab & Team: He is part of the SRG-UAH Space Research Group, collaborating on projects such as the Antarctic Cosmic Ray Observatory (ORCA) and FPGA-based instrument development.

Elisa Rojas Sánchezمشاهده پروفایل

استاد

• Networking
• Software-Defined Networking (SDN)
• Edge Computing
• +۷ مورد دیگر

Elisa Rojas Sánchez is a tenured professor at the University of Alcalá, affiliated with the Department of Automation within the School of Telematics Engineering. Her primary research focuses on advanced networking technologies including Software-Defined Networking (SDN), edge computing, IoT integration, and network architecture optimization. She leads the NetIS research group (Networks and Intelligent Systems), exploring innovations in programmable networks and intelligent systems for future communication infrastructures. Her academic background includes a doctoral thesis on high-performance transparent Ethernet switch architectures. She has contributed significantly to protocols like ARP-Path and Torii-HLMAC, advancing scalable routing and fault-tolerant data center designs. Her work bridges theoretical networking research with practical implementations in 6G, industrial IoT, and cloud-edge continuum systems. Recent publications highlight breakthroughs in data-driven protocols (e.g., BareFlow), AI-driven fault prediction in smart grids, and topology-aware resource management in dense networks. She also explores educational innovations like gamification in engineering teaching and hybrid SDN methodologies. Key Research Themes: SDN protocols, edge computing frameworks, IoT scalability, network resilience, AI in networking Notable Achievements: Developed open-source tools like NetIDE, contributed to OpenFlow standards, and pioneered multi-path routing algorithms Her work frequently addresses real-world challenges such as latency reduction in programmable ASICs (Tofino P4), secure in-band control channels, and collaborative resource-sharing in edge environments. She actively participates in international conferences as a program chair and continues advancing the next generation of network architectures.

• Blockchain Technology
• Data Analytics
• Cybersecurity
• +۷ مورد دیگر

Salvador Sánchez Alonso is a Professor at the Department of Computer Languages and Systems, Universidad de Alcalá. He holds a PhD from Universidad Politécnica de Madrid (2005) under Dr. Miguel Ángel Sicilia Urbán. His research focuses on blockchain technology, cybersecurity, linked data, healthcare informatics, and educational technology. He actively contributes to the I4 research group (Intelligence, Innovation, Internet, and Information), exploring topics like privacy-preserving systems, social network analysis, and open data principles. His work bridges theoretical advancements with practical applications, such as predictive modeling for healthcare innovation, quality assessment of educational resources, and decentralized identity systems. Recent publications highlight innovations in quantum software measurement, KlimaDAO analysis, and ethical AI traceability. He has also explored the impact of political events on social networks and hospital resource management through predictive analytics. Key contributions include frameworks for metadata quality in digital repositories, interlinking educational data with the Web of Data, and applying blockchain for secure metadata deployment. His research often intersects interdisciplinary domains, emphasizing social data visualization and user-centric repository design.

• Electromagnetic Field Design
• Antenna Engineering
• Computational Intelligence
• +۳ مورد دیگر

Rocío Sánchez Montero is an Associate Professor in the Department of Signal Theory and Communications at the University of Alcalá. She holds a PhD from the same institution (2011), focusing on computational intelligence techniques for robust design of radiant devices. Her work is centered in the Radiation and Sensing Group (RSG), addressing challenges in antenna engineering, electromagnetic field optimization, and biomedical applications. Her research interests include antenna design, wireless systems, and bioengineering applications of electromagnetic fields. Notably, she has pioneered methods for exposure mapping using evolutionary algorithms and developed miniaturized antennas for medical and industrial use. Her work integrates computational intelligence with hardware design, emphasizing practical applications in telecommunications and healthcare. Recent publications highlight advancements in wearable antennas, cryogenic radio telescope front-ends, and wireless power transfer for implantable devices. She also contributes to data protection policies, particularly pseudonymization techniques for public administration. Though no formal awards are listed, her prolific output (over 50 publications since 2003) reflects sustained contributions to electromagnetic engineering and interdisciplinary research. She advises through her teaching roles and collaborates on innovative projects at the Yebes Observatory and biomedical engineering interfaces.

• Signal Processing
• Acoustic Sensor Networks
• Machine Learning Applications
• +۵ مورد دیگر

Manuel Utrilla Manso is an Associate Professor at the Department of Signal Theory and Communications at the University of Alcalá. His research focuses on signal processing, acoustic sensor networks, and machine learning applications in audio-based systems. He leads the AES3 research group, specializing in smart acoustic and electromagnetic sensor networks and signal processing. His work addresses challenges in UAV acoustic detection, emotion recognition (e.g., anger detection), and speech processing for hearing aids. He holds a Ph.D. from the University of Alcalá with a thesis on finite-precision analysis in advanced digital filter structures. Key research interests include: Acoustic localization and source separation Machine learning for audio classification Optimization of microphone array configurations Non-destructive spectral analysis using sound Hearing aid algorithms and noise suppression Publications emphasize robust systems for noisy environments, computational efficiency, and interdisciplinary applications in healthcare and environmental monitoring. His work bridges theoretical signal processing with practical implementations in automotive, biomedical, and smart sensor domains. Notable contributions include development of benchmark datasets for sound event classification and optimization frameworks for waveform design in non-destructive testing. Research extends to educational technologies, including formative assessment methodologies for engineering students and interdisciplinarity in technical education.

• Procedural Law
• Legal Interdisciplinary Research
• Judicial Process
• +۳ مورد دیگر

Jose Martin Pastor is a Professor at the Universitat de València , affiliated with the Faculty of Law . His work spans Procedural Law and interdisciplinary legal research, with a focus on Biolaw and Judicial Process . PhD in Law (2000) from Universitat de València His research interests include Procedural Law , Legal Interdisciplinary Research , and Judicial Process . Recent work bridges Law and Physics (e.g., evacuation dynamics, granular flow), alongside legal studies on Mortgage Regulation and Public Prosecution . Publications reflect a mix of Procedural Law and Engineering Dynamics . Notable scientific awards are absent in the provided data. He has supervised at least one thesis and contributes to legal technology platforms like Iter Procesal .

Vicent Girbés Juanمشاهده پروفایل

دانشیار

• Robotics
• Human-Robot Interaction
• Intelligent Vehicles
• +۱۲ مورد دیگر

Vicent Girbés Juan is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His research is centered in the HRI Human-Robot Interaction Group, where he contributes to advanced robotics, intelligent vehicles, and human-centered automation systems. He earned his PhD from Universitat Politècnica de València in 2016 with a thesis on clothoid-based planning and control in autonomous and manual-assisted driving systems, supervised by Dr. Josep Tornero Montserrat and Dr. Leopoldo Armesto Ángel. His research interests span robotics, control systems, path planning for UAVs, visible light communication, haptic feedback in teleoperation, and educational innovation in engineering. He has published extensively on smooth trajectory generation, dual-arm robot control, sensor fusion, and V2V communications. His recent work shows a growing emphasis on integrating pedagogical innovation with engineering education, including flipped evaluation, peer assessment, and hackathon-based programming learning. His publications from 2021 to 2024 reveal a dual focus: advancing industrial robotics and intelligent transportation systems, while simultaneously innovating in teaching methodologies and student engagement in higher education. Key technical areas include clothoid-based 3D path planning, cautious Bayesian optimization, VLC positioning, and haptic-assisted teleoperation. He actively collaborates on interdisciplinary projects involving human-robot cooperation, industrial automation, and educational technology, reflecting a commitment to both technological advancement and pedagogical excellence. His email is vicent.girbes@uv.es .

• Physical Geography
• Climate Change
• Meteorological Risks
• +۶ مورد دیگر

Juan Javier Miro Perez is a Professor in the Department of Geography at the Faculty of Geography and History, Universitat de València, Spain. His work is centered on physical geography with a focus on climate systems and environmental risks in the Mediterranean region. His research interests include climate change, meteorological hazards, and hydrological modeling, particularly through advanced statistical and computational methods. He specializes in statistical downscaling of climate data using neural networks, high-resolution temperature reconstruction, spatial interpolation techniques, and long-term trend analysis (1948–2011) in the Valencian Community. His expertise bridges climatology and geospatial analysis for environmental risk assessment. He is an active member of the CLIMAMET Research Group, which investigates climate change impacts, weather-related risks, and their implications for hydrological systems in Mediterranean environments. This group serves as a hub for interdisciplinary research on climate adaptation and resilience. Juan Javier Miro Perez completed his doctoral studies at the Universidad de Alicante in 2014. His Ph.D. thesis, supervised by Dr. Jorge Olcina Cantos and Dr. María José Estrela Navarro, was titled: "Statistical Downscaling of Climate Series Using Neural Networks: High-Resolution Reconstruction of Daily Temperature for the Valencian Community. Spatial Interpolation and Trend Analysis (1948–2011)." He advises graduate students and collaborates on research projects related to climate modeling and environmental risk, though specific names and grants are not listed in the current text. His work contributes to both academic understanding and practical applications in climate adaptation policy and water resource management in vulnerable Mediterranean regions.

• Internet of Things (IoT)
• Edge Computing
• Deep Learning
• +۱۲ مورد دیگر

Jesus Lopez Ballester is a faculty member at the Universitat de València, affiliated with the School of Engineering and the Department of Electronic Engineering. He is an active researcher in the fields of IoT, edge computing, and acoustic signal processing, contributing to both academic and applied research in smart environments and sustainable monitoring systems. His research interests lie at the intersection of artificial intelligence and physical sensing systems, with a strong emphasis on real-time, low-cost, and energy-efficient solutions. Key areas include sound event detection for driving safety, psychoacoustic annoyance modeling, urban soundscape monitoring, HRTF analysis, and room acoustic parameter estimation. His work integrates deep learning with embedded systems, particularly leveraging edge computing and IoT platforms to enable intelligent, distributed acoustic sensing in urban and industrial contexts. The recent publications reveal a consistent trend toward deploying AI models on resource-constrained devices for environmental and safety applications. His work frequently combines sensor networks with neural networks to achieve real-time, on-device inference, supporting applications in smart cities, transportation safety, and industrial monitoring. There is a strong focus on sustainability, cost-effectiveness, and practical deployment over theoretical exploration. He is actively involved in two research groups: the DSDC Communications and Digital Systems Design Group and the LSyM Simulation and Modeling Laboratory, where he contributes to projects involving wireless sensor networks, acoustic modeling, and IoT system design. While no formal students are listed, his role in supervising thesis work and leading technical developments indicates mentoring and advisory responsibilities. His research is supported by institutional affiliations and collaborative projects, though specific grants are not detailed in the provided text.

• Educational Technology
• ICT in Education
• Educational Innovation
• +۲ مورد دیگر

Dr. Maria Del Carmen Fernandez Morante is a full professor at the Department of Pedagogy and Didactics, Faculty of Education Sciences, University of Santiago de Compostela (USC). She specializes in Educational Technology and ICT integration in education. Key Research Areas: Educational Innovation, Digital Literacy, Technology-Enhanced Learning Teaching: Coordinates courses on ICT application in education for early childhood and primary education, e-learning research, and political communication technologies Her work focuses on digital competence frameworks for educators, emerging technologies in K-12 education, and equity in digital access for rural and chronically ill students. She contributes to European educational projects and gender equality initiatives in technology education. Notable contributions include: Co-developing the DigCompEdu digital competence framework Research on AI literacy in primary education Participation in the ABILITI project for telepresence systems in schools Leadership in DLAB2 health-promoting educational technology project She emphasizes hands-on, interactive learning methodologies and has published extensively on technology integration in education. Her evaluation methods combine continuous assessment with practical implementation in educational settings.

Llado Bardera, Xavierمشاهده پروفایل

استاد

• Medical Image Analysis
• Computer Vision
• Image Processing
• +۱۱ مورد دیگر

Xavier Lladó Bardera is a Full Professor and ICREA Academia at the University of Girona, affiliated with the Department of Computer Architecture and Technology and the Computer Vision and Robotics Institute (VICOROB). He holds a PhD in Computer Engineering from the University of Girona and completed postdoctoral research at Queen Mary, University of London. B.S. in Computer Science, University of Girona (1999) Ph.D. in Computer Engineering, University of Girona (2004) Post-doctoral Research Assistant, Queen Mary, University of London (2004–2006) His research centers on medical image analysis, particularly in brain MRI, multiple sclerosis, prostate imaging, and deep learning. He has made significant contributions to lesion segmentation, tissue classification, and image registration, with a focus on clinical translation. His work integrates advanced computer vision techniques with biomedical applications, leveraging deep learning, non-rigid modeling, and multimodal imaging. The recent publications reflect a strong trend in deep learning for medical image analysis, especially in stroke, multiple sclerosis, and neonatal imaging. Key themes include lesion segmentation, hematoma expansion prediction, brain atrophy quantification, and end-to-end deep learning frameworks. There is a clear emphasis on clinical applicability, model interpretability, and handling real-world imaging challenges. Scientific Awards and Recognition: Best Project Prize – MAIA Master (Mladen Rakic, 2019) Best Project Prize – VIBOT Master (Jose Bernal, 2017) Best Project Prize – EINF Degree Project (E. Roura, 2011) Best Project Prize – EINF Degree Project (M. Cabezas, 2009) Best Project Prize – ETIG Degree Project (C. Fontanella, 2009) Best Paper Prize – Pattern Recognition (J. Salvi et al., 2010) Dr. Lladó has supervised over 20 PhD and master’s students, many of whom have continued in academia or industry (e.g., Icometrix, Johns Hopkins). He has been involved in numerous research grants and technology transfer initiatives, particularly in CAD systems for breast imaging and MS monitoring tools. His group actively collaborates with clinical partners, ensuring translational impact. He leads the NIC group at the VICOROB Institute, focusing on neuroimage computing and deep learning applications in neurology. The team develops open-source tools and participates in international challenges (e.g., BraTS, WMH), contributing to standardized evaluation in medical image analysis.

• Computer Architecture
• Distributed Systems
• Computer Networks
• +۳ مورد دیگر

Ramon Fabregat Gesa is a Professor in the Department of Computer Architecture and Technology at the University of Girona, Spain. He is affiliated with the Institute of Computing and Applications and is an active member of the Communications and Distributed Systems Research Group. His work spans research, teaching, and academic management within the field of computing and technology. His research interests focus on core areas of computer science, including Computer Architecture , Distributed Systems , and Communications Networks . These fields reflect his engagement with both hardware and software systems, particularly in distributed and networked environments. His academic work supports advanced computing applications and system design. No recent publications were listed in the available text, so no trend analysis can be performed at this time. No scientific awards were mentioned in the provided information. Ramon Fabregat Gesa has been involved in academic management roles and contributes to teaching across multiple courses. While specific advisees and grants are not listed, his participation in research projects and supervision within the Communications and Distributed Systems Research Group suggests an active mentoring and collaborative research role. He is a key member of the Communications and Distributed Systems Research Group at the Institute of Computing and Applications, where he contributes to advancing research in networked and distributed computing systems.

• Computer Science
• Distributed Systems
• Computer Architecture

Ramon Fabregat Gesa is a University Professor in the Department of Computer Architecture and Technology at the Universitat de Girona , associated with the Institute of Computing and Applications . He leads the Communications and Distributed Systems Research Group . Office: Building P4, Room 210, Girona Contact: +34 680852215 (Ext. 5428) Research focuses on distributed systems and computer architecture , with applications in computing and communications. The research group specializes in networked systems, parallel computing, and distributed algorithms.