جستجوی استاد راهنمای دانشگاهی

• High-Performance Computing
• Reconfigurable Computing
• FPGA Acceleration
• +۷ مورد دیگر

Carlos Alvarez Martinez is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture at the Barcelona School of Informatics (FIB). He is a key member of the Programming Models (PM) research group and collaborates closely with the Barcelona Supercomputing Center (BSC). His research focuses on high-performance computing, FPGA acceleration, task-based programming models like OmpSs, and hardware-software co-design for heterogeneous systems. His research interests center on advancing parallel computing through innovative programming models and hardware acceleration. He investigates efficient task scheduling, resource management in multicore and FPGA-based systems, and runtime support for dataflow models. His work enables high-performance execution of complex applications in domains such as scientific computing and cyber-physical systems. He actively contributes to European initiatives like TEXTAROSSA and AXIOM, aiming to develop next-generation exascale supercomputing technologies. The trend in his recent publications shows a strong focus on leveraging FPGAs for HPC, optimizing SpMV operations, improving task scheduling with hardware support, and developing frameworks for multi-FPGA clusters. His work consistently bridges theoretical models with practical implementations, emphasizing performance, scalability, and energy efficiency in heterogeneous computing environments. Scientific Awards: Premi UPC al Compromís Social 2019 Premi Disseny per al Reciclatge 2013 Alvarez Martinez has advised or collaborated with several doctoral students, including Jaume Bosch, Xubin Tan, and Fahimeh Yazdanpanah. He has been involved in numerous competitive R&D projects, often related to high-performance computing and parallel programming models. His work includes significant contributions to educational innovation, particularly in active learning methodologies and formative assessment using interactive systems. He leads and participates in research labs and teams focused on programming models and computer architecture, notably the PM group at UPC/BSC. These teams develop runtime systems, compilers, and hardware accelerators to push the boundaries of parallel computing efficiency and programmability.

Pere-Pau Vázquezمشاهده پروفایل

استادیار

• Information Visualization
• Scientific Visualization
• Medical Data Visualization
• +۶ مورد دیگر

Pere-Pau Vázquez is an Assistant Professor in AI for Visual Computing at the Computer Vision Lab, TU Wien, Austria . Previously, he held academic positions at the ViRVIG Group and Facultat d'Informàtica de Barcelona (UPC) , where he taught courses in Programming, Computer Graphics, and Visualization for over 20 years. His research focuses on Information Visualization, Scientific Visualization, Medical Data Visualization, Molecular Visualization, and AI applications to Visual Computing . Current Teaching : Data Visualization, Fast Realistic Rendering, Information Visualization, Medical Images, Scientific Visualization, Virtual Reality, and 3D Medical Visualization. Former PhD Students : Elena Molina, Alexandra Cortez, Jesús Díaz, Pedro Hermosilla, Eva Monclús. His scientific awards include the Best PhD Thesis Award (UPC, 2003), Best Student Paper Award (SPIE, 2012), and Best Paper Award (International Conference on Computer Graphics Theory and Applications, 2013). Recent publications explore AI integration in biomedical visualization, molecular data analysis, and interactive techniques for volume rendering. He serves on the EuroGraphics Executive Board as Secretary and is active in steering committees for EuroVis and Visual Computing for Biology and Medicine . His work bridges Computer Graphics, Artificial Intelligence, and Human-Computer Interaction , with applications in medical and molecular data analysis.

Felix Gomez Marmolمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Felix Gomez Marmol is an Associate Professor at the University of Murcia's Faculty of Informatics, Department of Information and Communication Engineering. His research focuses on cybersecurity, artificial intelligence, network security, and IoT security. He holds a PhD in Computer Science from the University of Murcia (2010), supervised by Dr. Gregorio Martínez Pérez. Key research interests include adaptive intrusion detection systems, dark web analysis, and AI-driven cybersecurity frameworks. He leads the Intelligent Systems and Telematics research group and previously contributed to the Sistemas Inteligentes group. His work emphasizes practical applications such as the SCORPION Cyber Range platform for cybersecurity training and gamification. Recent projects involve detecting hate networks on social media, optimizing malware defense using transfer learning, and developing SIEM systems for IoT environments. His contributions span technical papers on cybersecurity education, ethical hacking fundamentals, and blockchain-based security solutions. Prof. Gomez Marmol has collaborated on initiatives like the COBRA framework for simulating advanced persistent threats (APTs) and the COnVIDa dashboard for pandemic-related data analysis. His research bridges theoretical advancements with real-world cybersecurity challenges.

• Entrepreneurship
• 3D Scanning
• Additive Manufacturing
• +۴ مورد دیگر

Roger Uceda Molera is an Associate Professor at the Universitat Politècnica de Catalunya (UPC) in the Department of Mechanical Engineering, affiliated with the Barcelona Higher Technical School of Industrial Engineering (ETSEIB). He is a member of the DigiFACT research group, focusing on advanced manufacturing technologies. His expertise spans entrepreneurship, 3D scanning, additive manufacturing, 3D printing, Industry 4.0, IoT, and mechanization. He has contributed to over 25 research activities, including articles, patents, and awards. Roger’s research emphasizes innovative additive manufacturing techniques, such as hybrid multi-material 3D printing and applications in medical prototyping. His work includes developing materials for concrete additive manufacturing and optimizing ceramic sintering processes. He has collaborated with companies like BCN3D Technologies and led projects funded by public-private partnerships. Key awards include the 2019 Premi Nacional al Partenariat Publicoprivat en R+I and the World to NYC Global Industry Challenge (W2NYC). He holds a patent for extrusion systems in cementitious material manufacturing. His research group, DigiFACT, drives advancements in digital factory technologies and industrial innovation.

• Quantum Optics
• Photonics
• Nanotechnology
• +۳ مورد دیگر

Prof. Valerio Pruneri is an ICREA Professor and Group Leader at the Institute of Photonic Sciences (ICFO), holding the Corning Inc. Chair in Optoelectronics. He leads a research group focused on quantum optics, nanophotonics, and biomedical imaging. His academic background includes a PhD in Laser Physics from the University of Southampton (UK). Research interests span quantum communication technologies, plasmonic sensors, and nanomaterials for optical applications. Recent advancements include work on quantum key distribution systems, graphene-based devices, and super-sensitive phase imaging techniques. Articles highlight innovations in quantum-enhanced imaging, integrated photonic circuits, and hyperbolic metamaterials. His team collaborates on EU projects like NANO-GLASS ITN and FLIGHT, with a strong emphasis on translational research. Over 50 students and researchers are advised, many funded by national and international grants (e.g., Agencia Estatal de Investigación, CELLEX Foundation). Key lab facilities include state-of-the-art cleanrooms and optical characterization tools.

Mariano Cabezasمشاهده پروفایل

پژوهشگر

• computer vision
• medical imaging
• magnetic resonance imaging (MRI)
• +۵ مورد دیگر

Mariano Cabezas is a researcher in medical imaging and computer vision, currently affiliated with Macquarie University and as an affiliate at the University of Sydney . His work focuses on automating brain MRI analysis for pathologies like multiple sclerosis, Alzheimer's disease, and tumors, with additional contributions to UAV image analysis. PhD in Computer Science (2013), University of Girona MSc in Automation, Computation, and Systems (2010), University of Girona BSc in Computer Science (2009), University of Girona Research Interests : Specializes in magnetic resonance imaging , lesion detection , deep learning , and image processing , with applications in multiple sclerosis , hearing loss , and UAV-derived ecological data . His recent work includes federated learning frameworks for cross-site MS lesion segmentation and pseudo-labeling techniques for longitudinal brain volume estimation. Publication Trends : Over the past five years, his research has emphasized federated learning (4 articles), lesion segmentation (9 articles), and UAV image analysis (3 articles), with a strong focus on clinical validation and cross-institutional collaboration. Labs & Collaborations : Contributed to the NIC-VICOROB group at the University of Girona and maintains affiliations with the Research Institute of the Hospital Vall d'Hebron (VHIR) in Barcelona and Macquarie University in Sydney. Actively develops open-source tools hosted on GitHub.

Fernando Sánchez-Figueroaمشاهده پروفایل

استاد

• Software Engineering
• Big Data
• Business Intelligence
• +۳ مورد دیگر

Fernando Sánchez-Figueroa is a Full Professor at the University of Extremadura's Department of Computer Systems Engineering and Telematics. He is a co-founder of Homeria Open Solutions, a spin-off engaged in R&D projects under EU frameworks. His research focuses on Software Engineering, Machine Learning, Data Visualization, and Ambient Intelligence. He has authored over 50 scientific articles and led numerous R&D contracts with public and private entities. Key roles include: Academic: Full Professor at University of Extremadura Entrepreneur: Co-founder of Homeria Open Solutions Research: Participation in EU-funded projects and development of AI-driven solutions for healthcare, smart cities, and education Research Interests: Machine Learning applications in healthcare, predictive analytics for education, and sustainable smart city technologies. His work bridges theoretical advancements with practical implementations, such as medical image segmentation using SAM models and cost-efficient UAV systems. Publications: Recent works include decision support systems for employability analysis, zero-shot learning in medical imaging, and recommender systems for education. He emphasizes data-driven approaches and model-driven engineering in software development. Impact: Developed tools like CompareML for preliminary data analysis and LiveSankey for advanced web visualization. His contributions span academia and industry, addressing challenges in healthcare, urban sustainability, and educational technology.

• Optics
• Visual Sciences
• Medical Optics
• +۳ مورد دیگر

Sergio Barbero is an Associate Researcher at the Visual Optics laboratory of the Instituto de Óptica (CSIC), Spain, under the supervision of Prof. Susana Marcos. He holds a BSc in Physics from the University of Zaragoza (1999) and a PhD in Visual Sciences from the University of Valladolid (2004), which earned him the Doctoral Thesis Extraordinary Award (2005). His research focuses on optical aberrations, intraocular lens design, wavefront measurement techniques, and gradient-index modeling of ocular structures. Barbero has collaborated with international groups at Indiana University (USA), University of Houston (USA), and Australian institutions. His work includes pioneering studies on crystalline lens tomography, corneal ablation algorithms, and novel wavefront sensing methods. He has authored 16 peer-reviewed publications and contributed to a US patent on wavefront reconstruction techniques. His research spans three core areas: (1) intraocular lens design using analytical tools, (2) gradient-index modeling of the human eye, and (3) in vivo measurement of crystalline lens aberrations. He has secured grants from the Spanish government (I3P-CSIC), NIH (USA), and Fulbright fellowships. Barbero has presented 33 scientific talks/posters, including invited lectures, and maintains an h-index of 9. His work bridges fundamental optics with clinical applications in ophthalmology.

• Biometrics
• Biometric Systems
• Computer Vision
• +۵ مورد دیگر

Raul Sanchez Reillo is a Full Professor at Universidad Carlos III de Madrid (UC3M), affiliated with the Grupo Universitario de Tecnologías de Identificación (GUTI). His research focuses on biometric systems, mobile authentication, and security technologies. Key areas include presentation attack detection, vein recognition, and ECG biometrics. He leads projects involving smartphone-based biometric solutions, 3D printed markers, and standards development for biometric interoperability. Research interests span multiple modalities: fingerprint authentication, dynamic signature verification, gait recognition, and vascular biometrics. He emphasizes usability and accessibility in mobile environments, exploring ergonomics and user interaction challenges. His work integrates machine learning (transformers, RNNs) with hardware solutions like FPGA-based systems. Publications highlight innovations in spoofing detection, medical applications (ECG/vein analysis), and low-cost hardware implementations. He contributes to European standards (BioAPI, Hand Data Interchange Format) and evaluates security practices for R&D compliance with EU data protection regulations. Current initiatives include enhancing biometric systems for critical infrastructure security and improving accessibility for elderly users. Active in interdisciplinary collaborations, he leads the Mobile Pass project evaluating user interaction in biometric systems. His lab (GUTI) develops open testing methodologies for biometric performance under Common Criteria and environmental stressors. Recent work addresses vulnerabilities in mobile fingerprint sensors and the ethical implications of biometric-as-a-service models.

Andrea Meilán-Vilaمشاهده پروفایل

استادیار

• Nonparametric Estimation
• Directional Statistics
• Kernel Smoothing
• +۳ مورد دیگر

Andrea Meilán-Vila is an Assistant Professor in the Department of Statistics at Universidad Carlos III de Madrid since 2021, holding a Juan de la Cierva Fellowship since 2023. She earned her PhD in Statistics from Universidade da Coruña (2021) and previously served as a Postdoctoral Fellow at Universidade de Santiago de Compostela's Department of Statistics, Mathematical Analysis and Optimisation. Her research focuses on nonparametric methods for analyzing complex data types, including directional, spatial, and functional data. Key areas include kernel smoothing techniques, goodness-of-fit testing for regression models, and spatial trend estimation. She serves as an Associate Editor for the Journal of Nonparametric Statistics . Recent work emphasizes applications in climate science (temperature curve modeling), fluid dynamics (wake flow control), and biomedical imaging (hippocampus shape analysis). Her methodologies address challenges like sparse data estimation and spatial correlation in regression frameworks. Key Projects: STENED (Stein-based goodness-of-fit tests for non-Euclidean data) Awards: Juan de la Cierva Fellowship (2023) Publications span journals like Journal of Fluid Mechanics , Statistical Papers , and TEST , with a focus on methodological advancements in statistical modeling and computational validation.

Le Luمشاهده پروفایل

پژوهشگر

• Medical Imaging
• Artificial Intelligence
• Oncology Imaging
• +۳ مورد دیگر

Dr. Le Lu serves as Researcher & Senior Director leading global Medical AI R&D efforts at Alibaba DAMO Academy since August 2021. His career spans prestigious institutions including the National Institutes of Health, Clinical Center, Radiology and Imaging Science Department, NVIDIA AI-Infra division, and Siemens corporate research where he was a senior staff scientist from 2006 until 2013. Ph.D. in Computer Science from Johns Hopkins University (2007) Dr. Lu specializes in medical imaging AI with significant contributions to oncology imaging and computer vision applications in healthcare. His research bridges advanced AI techniques with clinical applications, particularly in cancer screening and diagnostic imaging. He has published over 250 peer-reviewed articles in top-tier journals including Nature Medicine, Nature Communications, and IEEE Transactions on Pattern Analysis and Machine Intelligence, with more than 23,880 citations as of January 2024. Dr. Lu has received numerous accolades including IEEE Fellowship and recognition for publishing the most cited papers in IEEE TMI and CVPR medical imaging categories over the past decade. His innovative work has resulted in over 100 patent filings across multiple jurisdictions. IEEE Fellow (Computer Society) for contributions to medical imaging, AI and oncology imaging IEEE Signal Processing Society Distinguished Industrial Speaker (2021-2023) Associate Editor for IEEE Trans. Pattern Analysis and Machine Intelligence (IF: 24.3) Associate Editor for IEEE Signal Processing Letters and Frontiers in Oncology MICCAI society board member Through his leadership at Alibaba DAMO Academy, Dr. Lu directs research initiatives focused on making AI-driven healthcare solutions accessible globally, with recent presentations on 'AI for Health for All' and cancer screening paradigms.

Luis Jose Fuentes Meleroمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Attention Disorders
• Differential Outcomes Procedure
• +۳ مورد دیگر

Luis Jose Fuentes Melero is a Full Professor of Basic Psychology at the University of Murcia, Spain, affiliated with the Faculty of Psychology and Speech Therapy. His career includes leadership roles in research groups such as the Cognitive Neuroscience Laboratory and the former Neuropsychology of Attention group at the University of Almería (1988–2004). He holds a PhD in Psychology from the University of Granada (1987), supervised by Dr. Pío Tudela Garmendia. Research Focus: Cognitive neuroscience, attention mechanisms, differential outcomes procedure, neurodegenerative diseases, and educational psychology. Affiliations: Principal investigator in projects funded by the Spanish Ministry of Science and Innovation (Consolider Ingenio 2010, Plan Nacional I+D+i) and Fundación Séneca. His work combines experimental psychology with neuroimaging, focusing on attention deficits, aging, and applied behavioral interventions. He has supervised 17 doctoral theses and contributed to over 200 publications, with an h-index of 32. Collaborations include institutions like the Virgen de la Arrixaca Hospital and Oxford University. Notable achievements include developing the Differential Outcomes Procedure (DOP) to enhance learning and memory, and pioneering studies on electrical brain stimulation for attention and memory improvement (e.g., PID2021-125408NB-I00 project).

Belen Masiaمشاهده پروفایل

دانشیار

• Computational Imaging
• Applied Perception
• Virtual Reality
• +۴ مورد دیگر

Belen Masia is a tenured Associate Professor in the Computer Science Department at Universidad de Zaragoza , Spain. She is affiliated with the Graphics & Imaging Lab (part of the I3A Institute ) and the Vision, Image and Neurodevelopment Group (within the IIS Aragon Institute ). Her research bridges computational imaging , applied perception , and virtual reality , focusing on modeling human visual behavior and improving graphics/vision algorithms through perceptual insights. Education : Ph.D. in Computer Science (Eurographics PhD Award 2015), postdoctoral work at Max Planck Institute for Informatics . Research Highlights : Virtual Reality : Studying user behavior, saliency prediction, multimodal perception, and cinematography in VR. Appearance Modeling : Developing intuitive material representations and metrics for editing. Applied Perception : Leveraging human vision insights to diagnose defects in non-verbal patients. Computational Displays : Exploring HDR imaging and display optimization. Scientific Awards : Eurographics Young Researcher Award 2017 Eurographics PhD Award 2015 MIT Technology Review Top Ten Innovators Below 35 in Spain 2014 NVIDIA Graduate Fellowship 2012 Leonardo Fellowship from BBVA Foundation 2020 Leadership & Editorial Roles : Co-chair of Full Papers track at Eurographics 2026 Associate Editor for ACM Transactions on Graphics, Computers and Graphics, and ACM Transactions on Applied Perception Co-founder of DIVE Medical , a startup for automated visual function diagnosis PhD Students : Dario Lanza (2025, Modeling, Perception and Editing of Volumetric Materials ) Daniel Martin (2024, Computational Models of Visual Attention in VR , Best PhD Thesis Award EGSE) Julia Guerrero-Viu (2023, WiGRAPH Rising Star) Sandra Malpica (2023, VR Gaze Behavior ) Manuel Lagunas (2021, BBVA/SCIE Young Researcher Award) Ana Serrano (2019, Eurographics PhD Award & Unizar Outstanding Thesis) Collaborations & Grants : Involved in the EU-funded PRIME Innovative Training Network (predictive rendering and appearance reproduction) and leading projects on deep learning for pediatric visual diagnosis.

• Cardiac Electrophysiology
• Biomedical Instrumentation
• Mechanoelectric Feedback
• +۷ مورد دیگر

Irene del Canto Serrano is a Researcher in the Department of Electronic Engineering at the School of Engineering, Universitat de València. Her work integrates biomedical engineering with cardiac electrophysiology, focusing on the interaction between mechanical forces and electrical activity in the heart. She is actively involved in two key research groups: GRELCA (Cardiac Electrophysiology group) and i2N (Electronic Instrumentation in Medical and Nuclear Physics), reflecting her dual expertise in physiology and instrumentation. Education: PhD in Biomedical Engineering, Universitat Politècnica de València (2015). Thesis: Estudio de las modificaciones farmacológicas de los efectos electrofisiológicos producidos por el estiramiento local miocárdico a partir de técnicas dinámicas de cartografía eléctrica, en un modelo experimental de corazón aislado de conejo , supervised by Dr. David Moratal Pérez and Dr. Francisco Javier Chorro Gascó. Her research interests center on cardiac electrophysiology , particularly mechanoelectric feedback , myocardial stretch , arrhythmia mechanisms , and pharmacological modulation using experimental models. She also explores cardiac imaging , especially cardiac MRI for strain and deformation analysis, and applies machine learning to improve detection and classification in myocardial infarction. Her recent publications highlight a strong trend toward integrating biomarkers (e.g., ferritin), iron therapy , and cardiac function recovery in heart failure, showing translational relevance. Her 15 most recent publications reflect a consistent focus on experimental cardiology using isolated heart models, pharmacological interventions (ranolazine, GS967, eleclazine), and advanced imaging techniques. She investigates how drugs affect stretch-induced arrhythmias, evaluates MRI-based strain changes post-iron therapy, and develops AI tools for cardiac image analysis. These works span basic science (e.g., CaMKII inhibition) to clinical applications (e.g., Myocardial-IRON trial analysis). Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: While no formal students or grants are listed, her role as a postdoctoral researcher and active publication record suggest involvement in mentoring junior researchers and contributing to funded projects, particularly within the GRELCA and i2N groups. She has co-authored numerous experimental studies, indicating strong collaborative and project-based research activity. Labs and Teams: Irene is affiliated with two prominent research groups at Universitat de València: GRELCA (Cardiac Electrophysiology group) , which studies arrhythmia mechanisms and therapeutic interventions, and i2N (Electronic Instrumentation in Medical and Nuclear Physics) , which develops advanced tools for medical diagnostics. These affiliations underscore her interdisciplinary approach, combining physiology, engineering, and data science.

Carlos Platero Dueñasمشاهده پروفایل

استاد

• Biomedical Engineering
• Neuroscience
• Medical Image Processing
• +۳ مورد دیگر

Carlos Platero Dueñas is a Full Professor at the Department of Electrical, Electronic and Automatic Engineering and Applied Physics at the Universidad Politécnica de Madrid (UPM), where he has served for 31 years. He leads the research group Tecnologías para Ciencias de la Salud since 2015 and contributes to interdisciplinary research at the intersection of biomedical engineering, neuroscience, and artificial intelligence. Department: Electrical, Electronic and Automatic Engineering and Applied Physics Research Group: Tecnologías para Ciencias de la Salud (Health Science Technologies) Teaching: 34 years of academic experience, including 128 final projects supervised His research focuses on applying computational methods to neurodegenerative diseases , particularly Alzheimer's and Parkinson's, through neuroimaging analysis, predictive modeling, and hippocampal segmentation. Recent work includes AT(N) profiles for dementia prediction and machine learning techniques for clinical data modeling. The 15 most recent publications reveal a strong emphasis on Alzheimer's disease progression , hippocampal segmentation , and predictive analytics using neuroimaging and clinical markers. Key methodologies involve graph cuts algorithms, longitudinal modeling, and label fusion techniques applied to MRI and CT scans. Teaching contributions include: 128 final projects supervised (undergraduate and master's) 2 doctoral theses directed Active participation in university governance through the School Council and Researcher Staff Committee