جستجوی استاد راهنمای دانشگاهی

Yolanda Vidal Segui is an Associate Professor in the Department of Mathematics at the Universitat Politècnica de Catalunya (UPC), affiliated with the Escola d'Enginyeria de Barcelona Est (EEBE). Her research focuses on wind energy systems, predictive maintenance, and structural health monitoring of wind turbines. She leads projects in the CoDAlab and WinTurCoM research groups, specializing in data-driven models, condition monitoring, and failure prognosis. Her work integrates machine learning, mathematical modeling, and sensor technology to enhance turbine reliability and energy efficiency. Dr. Vidal holds a PhD in Applied Mathematics and has authored over 350 publications. Her contributions include advancements in SCADA data analysis, vibration-based diagnostics, and AI-driven condition monitoring systems. She has received several accolades, including the WindEurope Technology Workshop recognition and the IFIT Distinction in Mechanism and Machine Science. Her research bridges academia and industry, addressing challenges in offshore wind turbine integrity and maintenance strategies. Active in professional service, she serves on conference committees and editorial boards (e.g., Mechanical Systems and Signal Processing, Wind Energy). Her work emphasizes sustainable energy solutions and has been applied in real-world scenarios like the Alpha Ventus wind farm. She also contributes to educational initiatives, developing innovative teaching materials for engineering students.

• Wind Turbines
• Autonomous Learning
• Deep Learning
• +۸ مورد دیگر

Marco Raiola is an Associate Professor at the Department of Aerospace Engineering , Universidad Carlos III de Madrid (UC3M). His research focuses on fluid dynamics, turbulence, and aerodynamics, with applications in flow diagnostics, heat transfer, and control systems. Research Interests: Turbulent flows, data-driven modeling, particle image velocimetry (PIV), convective heat transfer, and bio-inspired aerodynamics. Projects: Principal researcher in INFLUENTIA-CM-UC3M (2024-2026) and Diagnóstico del ruido de chorro (2022-2025). Collaborator in EU-funded initiatives like HumanIC and ODE4HERA . Contact: Email mraiola@ing.uc3m.es | ORCID: 0000-0003-2744-6347

• Aeronautics
• Mechanical Engineering
• Fluid Dynamics
• +۵ مورد دیگر

Alan Briones Delgado is a researcher at the La Salle School of Engineering , Universitat Ramon Llull , with a focus on Internet of Things , Cybersecurity , and Transport Protocols . His work spans projects funded by the European Commission and national grants, including EXCEL4HOUSING4.0 , WeB-Nimbus , and NG-SOC , addressing challenges in cloud computing education, ecological monitoring, and security operations. His research integrates Artificial Intelligence and Wireless Sensor Networks for sustainable solutions. Key research areas include Quality of Service in heterogeneous networks, Environmental Conservation via IoT, and Teaching and Learning strategies for Big Data. Projects like EcoSentinel and BTL-COP highlight his commitment to Environmental Monitoring and Community Policing applications. His collaborations extend to institutions in the UK , Albania , and Western Balkans . Contact: alan.briones@salle.url.edu

• Internet of Things
• Transport Protocol
• Cybersecurity
• +۸ مورد دیگر

Frank NIELSEN is a Professor at École Polytechnique with expertise in information geometry, data science, and machine learning. He holds a PhD (1996) and HDR (2006) in computer science and has established himself as a leading researcher in geometric approaches to information science. His educational background includes a PhD in computer science (1996) followed by a Habilitation à Diriger des Recherches (HDR) in 2006, the highest academic qualification in France that qualifies one to supervise doctoral candidates. Dr. NIELSEN's research focuses on the Geometric Science of Information , where he develops theoretical frameworks for understanding data through geometric and information-theoretic lenses. His work bridges Computational information geometry Statistical manifold theory Bregman divergences and their applications Machine learning with geometric foundations High-dimensional data analysis He aims to address the challenge of inappropriate data representation in current Data Science by building a theory of Computational Information Geometry to enable Intrinsic Data Science with principled distances. His extensive publication record shows a clear trend toward developing geometric frameworks for understanding statistical divergences, with recent work focusing on Bregman geometry, Fisher-Rao metrics, and their applications in machine learning. His research spans theoretical developments in information geometry to practical implementations like the pyBregMan Python library, demonstrating both theoretical depth and practical relevance. Dr. NIELSEN has made significant contributions through his teaching and publications. He has taught courses at École Polytechnique including INF442, INF517, and INF591. His authored textbooks include Introduction to HPC with MPI for Data Science (2016), A Concise and Practical Introduction to Programming Algorithms in Java (2009), and Visual Computing: Geometry, Graphics, and Vision (2005). He has also edited influential volumes such as Computational Information Geometry for Image and Signal Processing (2016) and Geometric Theory of Information (2014). He actively organizes and participates in academic events, serving on program committees for major conferences including GSI (Geometric Science of Information), CVPR, and ICCV. His work has established him as a key figure in the growing field of geometric approaches to information science.

• Data science
• Geometric science of information
• Information geometry
• +۴ 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.

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

Julian Fierrez is a Full Professor at the School of Engineering, Universidad Autonoma de Madrid. With an h-index of 74 and over 20,000 citations, his work spans biometrics, signal/image processing, artificial intelligence, and human-computer interaction. Key research areas include: Biometric anti-spoofing and DeepFakes detection Mobile and behavioral biometrics Bias/fairness in AI systems Biometric applications in e-health and education Security in multimodal biometric systems His recent publications show strong focus on deep learning applications for biometric security, with specific subfields including fake detection, keystroke authentication, facial analysis for Parkinson detection, and privacy-preserving AI. He serves as Associate Editor for multiple IEEE and Elsevier journals. Scientific distinctions include: IAPR Young Biometrics Investigator Award (2017) Miguel Catalan Award to Best Researcher under 40 (2017) EURASIP Best PhD Award (2012) EBF European Biometric Industry Award (2006) Prof. Fierrez leads the BiDA Lab and supervises students like Ruben Tolosana and Aythami Morales. Current projects include BBforTAI (Biometrics and Behavior for Unbiased & Trustworthy AI) and PRIMA (Privacy Matters). He also contributes to standardization efforts in biometric evaluation.

• Biometrics
• Signal and Image Processing
• Artificial Intelligence
• +۶ 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.

• Quantum Optics
• Photonics
• Nanotechnology
• +۳ 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.

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

Javier Gomez Fernandez is a researcher at the Nanobioengineering Group within the Institute for Bioengineering of Catalonia (IBEC), affiliated with the University of Barcelona. His work bridges nanotechnology and biomedical applications, focusing on advanced bioimaging and sensor development. Research Focus: Nanoscale bioelectrical characterization, smart nano-bio-devices, and molecular imaging Technological Impact: Development of low-power gas sensors and nanoscale membrane analysis tools His interdisciplinary approach contributes to fields like biomedical signal processing, biomaterials, and precision medicine. Recent projects highlight collaborations with clinical institutions and industrial partners to address challenges in muscular dystrophy and antimicrobial therapies. Key contributions include: 2020 IEEE Access paper on energy-efficient gas sensors 2010 PNAS study on nanoscale cell membrane characterization

• Nanobioengineering
• Biosensors
• Biomedical Signal Processing
• +۳ مورد دیگر

Francesc Torres is a Full Professor at the Signal Theory and Communications Department of the Universitat Politècnica de Catalunya (UPC-BarcelonaTech). He holds a Doctor Ingeniero degree in Telecommunication Engineering from UPC (1992) and has extensive experience in microwave systems and space instrumentation. His research focuses on remote sensing, interferometric radiometry, and the European Space Agency's SMOS mission. He co-leads the Barcelona SMOS Expert Centre for radiometric calibration and ocean salinity studies. Torres has contributed to numerous ESA projects and served as a visiting scholar at NASA's Jet Propulsion Laboratory (2005-2006). His work bridges engineering education, with publications on STEM pedagogy and early-career development, and advanced instrumentation for Earth observation. Education: Ingeniero en Telecommunication Engineering (1988) Doctor Ingeniero en Telecommunication Engineering (1992) Research Interests: His primary areas include microwave radiometry, spaceborne sensors, calibration methodologies, and the application of remote sensing to geophysical studies. He also explores educational strategies to enhance critical thinking and self-management skills in STEM students. Current projects involve improving SMOS data accuracy through novel calibration techniques and developing educational frameworks for sustainable engineering practices. Grants & Projects: Key contributions include the SMOS mission calibration validation (CALIMAS team), GeoSTAR pilot project (JPL), and SuperMIRAS instrument development. He has led efforts to mitigate systematic errors in SMOS data and pioneered polarimetric analysis methods for rain events and ionospheric studies. Labs/Teams: Director of the Remote Sensing Laboratory (UPC), collaborating with ESA, JPL, and international research networks. Active in the Barcelona SMOS Expert Centre and the SMOSOps-Hexagonal initiative for operational mission improvements.

• Remote Sensing
• Microwave Engineering
• Space Technology
• +۴ 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.

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

Antonio Maria Gonzalez Colas is a Full Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Faculty of Computer Science of Barcelona (FIB). He leads the ARCO research group focused on Microarchitecture and Compilers and is actively engaged in high-impact research in computer architecture, GPUs, and energy-efficient computing. His collaborations extend to the Barcelona Supercomputing Center and various national and European research initiatives. Research Interests: His primary research areas include computer architecture, microarchitecture, compilers, GPUs, and processor design. He focuses on energy-efficient computing, deep neural network (DNN) accelerators, GPU simulation and optimization, memory systems, and architectural support for machine learning and autonomous systems. His work often integrates compiler techniques with hardware design for performance and efficiency. Scientific Production Trends: His recent publications demonstrate a strong focus on energy-efficient hardware for AI workloads, particularly DNN and speech recognition acceleration, GPU architectural innovations, memory optimization, and real-time rendering. He frequently publishes in top-tier venues such as ISCA, MICRO, HPCA, and IEEE/ACM journals. ICREA Academia Award 2024 HiPEAC 2024 Paper Award ACM Senior Member (2020) Advising and Grants: He has advised numerous PhD students whose theses cover topics like energy-efficient architectures for autonomous driving, speech recognition, and neural networks. He leads competitive R&D projects, including an ERC Advanced Grant and projects funded by the Spanish National Program and the ICREA Academia program, focusing on domain-specific architectures and cognitive computing units. Labs and Teams: He is the principal investigator of the ARCO (Microarchitecture and Compilers) research group at UPC, a leading team in computer architecture research in Spain. The group is part of a larger collaborative network within UPC and with international partners.

• Computer Architecture
• Microarchitecture
• Compilers
• +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.

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

Angel Merchan Perez is a faculty member at the Universidad Politécnica de Madrid , affiliated with the College of Computer Science and the Computer Systems Architecture and Technology Department . He is a key member of the Center for Biomedical Technology (CTB) since 2011 and the Technologies for Health Sciences Research Group since 2018. His work bridges neuroscience and computational technologies, focusing on ultrastructural analysis of the brain. Doctoral Postdoc: Harvard Medical School (1992-1995) Current Projects: Cajal Blue Brain Project, Human Brain Project His research focuses on developing advanced 3D electron microscopy techniques (FIB-SEM) for synaptic reconstruction, enabling quantitative analysis of synapse distribution and density in rat, mouse, and human cerebral cortex . He also contributed to image-analysis software like Espina for automated synapse detection. Recent publications highlight his expertise in: 3D Synaptic Mapping in Hippocampal Neurons Neurodevelopmental Disorder Pathology (Schizophrenia, Autism) Thalamocortical Circuit Complexity Mitochondrial Distribution in Neuropil Software Tools for Electron Microscopy

• Neuroscience
• Electron Microscopy
• Synaptic Connectivity
• +۳ مورد دیگر

Dr. José Luis Calvo Rolle serves as a Professor in the Department of Industrial Engineering at the School of Engineering, Universidade da Coruña (UDC), specializing in Systems Engineering and Automation. His research focuses on intelligent control systems, fault detection, and virtual instrumentation within the Cybernetic Science and Technology Research Group. Teaches across multiple programs including Master's in Industrial Computing and Robotics, Textile Technology, and Occupational Risk Prevention Coordinates thesis supervision across Industrial Engineering and related disciplines His research spans intelligent control systems and optimization, with significant contributions in virtual sensors, fault detection, and AI-driven modeling for industrial applications. Current projects integrate machine learning with industrial processes for naval construction, wastewater treatment, and precision livestock farming, demonstrating cross-disciplinary impact from energy systems to agricultural technology. Recent publications reveal strong trends in applying deep learning to industrial metaverse frameworks, wastewater optimization, and livestock monitoring systems. His work bridges theoretical control engineering with practical implementations in energy management, naval manufacturing, and sustainable agriculture, frequently utilizing dimensionality reduction and one-class classification techniques. Dr. Calvo Rolle actively mentors students through thesis supervision across multiple engineering disciplines and coordinates research projects with diverse funding sources including the European Commission, Spanish National Research Agency, and industrial partners like Navantia and Telefónica. His laboratory work centers on the Cybernetic Science and Technology Research Group, developing testbeds for industrial automation, virtual instrumentation, and AI-driven monitoring systems. Current initiatives include digital twin implementations for naval manufacturing and smart energy management systems.

• Intelligent Control Systems
• Fault and Anomaly Detection
• Virtual and Robust Sensors
• +۵ مورد دیگر