جستجوی استاد راهنمای دانشگاهی

Juan Antonio Corrales Ramónمشاهده پروفایل

پژوهشگر

• Human-Robot Interaction
• Robotic Manipulation
• Soft Robotics
• +۵ مورد دیگر

Juan Antonio Corrales Ramón is a postdoctoral researcher at the University of Santiago de Compostela (USC) under the prestigious Beatriz Galindo Program, affiliated with the CiTIUS laboratory. Previously, he served as an Associate Professor at Sigma Clermont Engineering School (France) from 2014 to 2020, where he taught courses in automatic control, robotics, and programming while conducting research at the Institut Pascal laboratory. He holds a Doctorate in Automatic Control and Robotics from the University of Alicante (2011), following a Master’s in Computer Engineering (2005). His research focuses on human-robot interaction , robotic manipulation , and soft robotics , with applications in industrial automation, healthcare, and agriculture. He has led or contributed to multiple international projects, including H2020-funded initiatives like Bots2Rec, SoftManBot, and ACROBA. His work emphasizes tactile sensing, deformation control, and collaborative robotics systems. Key contributions include: Development of low-cost tactile sensors for soft robotics ( Sensors , 2022) Adaptive control frameworks for deformable objects ( Frontiers in Robotics and AI , 2022) Robotic grippers with reconfigurable fingers ( IEEE Robotics and Automation Letters , 2021) He has received the Beatriz Galindo Postdoctoral Fellowship (2021–present) and has authored over 30 peer-reviewed articles. His research bridges theory and practice, addressing challenges in dexterous manipulation and human-robot collaboration.

MARCOS FERNANDEZ PICHELمشاهده پروفایل

استادیار

• Health Information Credibility
• Natural Language Processing
• Information Retrieval
• +۳ مورد دیگر

Marcos Fernández Pichel is an Assistant Professor at the Department of Electronics and Computing, affiliated with the Higher Technical School of Engineering at the University of Santiago de Compostela. He holds a Doctorate from the same institution (2023) with a thesis focused on technologies for analyzing health-related online content credibility. His research focuses on health information credibility assessment, natural language processing (NLP), and misinformation detection. He collaborates with the Singular Center for Research in Intelligent Technologies (CiTIUS) and has developed systems like Depressmind for mental health surveillance on social media, and Social Minder for detecting pandemic-related misinformation. His work has been recognized by the Royal Galician Academy of Sciences' award for best young researcher article (2022). Key projects include analysis of search engine performance for health queries, LLM-based depression symptom assessment, and risk communication strategies for radon gas. He has contributed to TREC Health Misinformation Track competitions (2021-2022), demonstrating expertise in retrieval systems and misinformation detection methodologies. Pichel's research often bridges computational linguistics with public health applications, emphasizing real-time monitoring of dynamic web sources (e.g., eXtream system). His work frequently involves semi-supervised learning techniques and ethical considerations in AI-driven health communication systems.

ROBERTO IGLESIAS RODRIGUEZمشاهده پروفایل

استاد

• Artificial Intelligence
• Mobile Robotics
• Reinforcement Learning
• +۴ مورد دیگر

Roberto Iglesias Rodríguez is a Professor at the Department of Electronics and Computing, Higher Polytechnic School of Engineering at Universidade de Santiago de Compostela. He holds a PhD from the same institution (2003) with a thesis on vector quantification models. His research focuses on artificial intelligence, mobile robotics, reinforcement learning, and fuzzy logic control. He leads the GSI Group (Intelligent Systems Group) within the Center for Research in Intelligent Technologies (CITIUS). Key research areas include: Robot navigation and path planning Reinforcement learning and hybrid learning systems Fuzzy control systems in dynamic environments Computer vision for robotics Federated learning and distributed robotics Recent work emphasizes federated learning applications in robotics, non-IID data handling, and adaptive systems. Notable contributions include a self-organized multi-camera network for robot deployment (2013) and combining reinforcement learning with genetic algorithms (2006). His research bridges theoretical advances with practical implementations in autonomous systems. Publications span over 30 years, with impactful work in journals like Robotics and Autonomous Systems, IEEE Transactions, and Lecture Notes in Computer Science. Active collaborations include institutions like The University of Texas at Austin and Maastricht University.

Marta Nuñez Garciaمشاهده پروفایل

پژوهشگر

• Medical Image Processing
• Machine Learning
• Cardiac Imaging
• +۴ مورد دیگر

Marta Nuñez Garcia is a Ramón y Cajal researcher at the University of Santiago de Compostela's CITIUS (Center for Research in Intelligent Technologies), affiliated with the Department of Electronics and Computing. She holds a PhD in Medical Image Processing from Universitat Pompeu Fabra (2018), with postdoctoral experience at IHU Liryc (Bordeaux) and INRIA. Her research focuses on applying machine learning and image processing to cardiac imaging modalities like MRI, CT, and LGE-MRI to develop standardized multimodal cardiac models for disease analysis. She leads the GSI Group (Intelligent Systems Group) and contributes to the CiTIUS lab. Education: Bachelor's in Telecommunication Engineering (Universidade de Vigo) MSc in Computer Vision & AI (Computer Vision Center, Barcelona) PhD in Medical Image Processing (Universitat Pompeu Fabra, 2018) Research interests include: Cardiac segmentation and quantification Deep learning for medical image analysis Personalized cardiac modeling for arrhythmia prediction Image-guided catheter ablation strategies Automated CT/MRI reformatting pipelines Recent work emphasizes explainable AI for predicting ventricular arrhythmias, scar maturation scoring, and CT-based predictive tools. Her GitHub repositories showcase open-source implementations of cardiac imaging algorithms like left atrial flattening and short-axis view reformatting.

MIGUEL CARRERO PAZOSمشاهده پروفایل

استاد

• Computational Archaeology
• GIS and Spatial Statistics
• Megalithic Landscapes
• +۳ مورد دیگر

Miguel Carrero-Pazos is a permanent faculty member and Professor at the University of Santiago de Compostela, affiliated with the Department of History within the Faculty of Geography and History. He is a core member of the GEPN-AAT research group (Grupo de Estudios para la Prehistoria del Noroeste Ibérico. Arqueología, Antigüedad y Territorio) and associated with the Centro de Investigación Interuniversitario das Paisaxes Atlánticas Culturais (CISPAC). His doctoral thesis (2017) explored megalithic tomb patterns in Galicia using GIS and spatial statistics. His research focuses on computationally-informed landscape archaeology, emphasizing GIS applications, spatial statistics, and 3D imaging techniques. Key areas include megalithic landscape analysis, rock art documentation (using photogrammetry and digital enhancement), and Neolithic settlement patterns. He has published extensively on topics like burial mound distribution modeling, visibility analysis of megaliths, and digital methods for preserving epigraphic heritage. Recent work highlights include developing hybrid machine learning algorithms for detecting archaeological tumuli, analyzing the 'Coast of Death' dolmen topographies, and advancing open-source computational tools in archaeology. He collaborates internationally, contributing to projects like Epigraphica 3.0, which digitizes Roman inscriptions, and the IFRAO 2018 rock art congress proceedings. His research integrates cutting-edge technologies with traditional archaeological questions, prioritizing reproducibility and interdisciplinary methods. He actively engages in heritage preservation efforts, particularly in Galicia, addressing challenges posed by rural depopulation and demographic changes. Carrero-Pazos is a leading voice in applying computational approaches to understand prehistoric and early medieval human decision-making in landscape contexts.

Silvia Ubillos Landaمشاهده پروفایل

استاد

• Social Psychology
• Mental Health
• Violence Prevention
• +۳ مورد دیگر

Silvia Ubillos Landa is a Professor at the Universidad de Burgos, affiliated with the Department of Health Sciences within the Faculty of Health Sciences. She holds a PhD in Social Psychology from the Universidad del País Vasco, focusing on attitudes, beliefs, and risky sexual behaviors among young Basque individuals. Her research interests revolve around social inclusion, quality of life, and mental health, with a focus on topics such as intimate partner violence, emotional regulation, and coping strategies. She leads the SIQoL (Social Inclusion and Quality of Life) research group and has contributed extensively to studies on public health crises (e.g., pandemic mental health) and violence prevention. Her recent publications (2023–2025) emphasize meta-analytic reviews of stroke-Alzheimer’s linkages, gender-based violence dynamics, and the psychological impacts of global health crises. Her work integrates clinical, developmental, and public health perspectives, often employing longitudinal and intervention methodologies. Dr. Ubillos Landa has authored over 100 peer-reviewed articles, with a focus on vulnerable populations (e.g., adolescents, elderly individuals). Her research bridges academic and practical domains, emphasizing culturally adapted interventions and evidence-based policy recommendations.

Santana Hernández, Lidia Esterمشاهده پروفایل

مدرس پاره‌وقت

• Entrepreneurship
• Circular Economy
• Tourism Management
• +۳ مورد دیگر

Santana Hernández, Lidia Ester is a Part-Time Substitute Lecturer at the Department of Economics and Business Management, Universidad de Las Palmas de Gran Canaria (ULPGC). She is affiliated with the GIR TIDES (Entrepreneurship, Digital Business, and Innovation) research group and the IU of Tourism and Sustainable Economic Development. Her academic work focuses on entrepreneurship dynamics, circular economy, tourism management, and scientometric analysis. Education: Master's Thesis in 2016: 'Estudio de las metodologías ágiles en la gestión de grupos de trabajo' advised by Sergio Ramos Ramos. Research Interests: She explores entrepreneurial behavior, circular economy models, tourism innovation, and the application of scientometric methods to analyze knowledge dynamics. Her work bridges socio-cognitive theories with empirical data, often using machine learning techniques to dissect global entrepreneurship trends. Publications Overview: Her recent work includes a 2025 study on circular economy entrepreneurship, a 2024 review of entrepreneurial intention literature, and analyses of regional entrepreneurship impacts during the pandemic. These contributions highlight her focus on evidence-based policy recommendations for sustainable economic development. Grants & Advising: While no grants are explicitly listed, she has advised master’s theses and collaborates with interdisciplinary teams on entrepreneurship education initiatives. Her research group activities emphasize digital transformation and innovation ecosystems. Labs/Teams: Active member of the GIR TIDES and interdisciplinary collaborations with the IDETIC group (Digital Signal Processing Division).

Dora Blanco Herasمشاهده پروفایل

استاد

• High Performance Computing
• Parallel Computing
• GPU Computing
• +۷ مورد دیگر

Dora Blanco Heras is a Full Professor in the Department of Electronics and Computing at the University of Santiago de Compostela (Spain). She holds a PhD in Physics (cum laude) from the same institution and has served as Head of the Sustainable Development Office (2005–2010). Her research focuses on high performance computing, parallel computing, and GPGPU techniques applied to remote sensing and medical image processing. She leads the ARQCOMP research group in Computer Architecture and is affiliated with the Center for Research in Intelligent Technologies (CITIUS). Research interests include: High-performance computing for real-time image processing GPU acceleration of hyperspectral/multispectral analysis Anomaly detection in fluvial ecosystems Domain adaptation for Earth observation Machine learning for remote sensing classification Recent work emphasizes deep learning architectures (ResNet, GANs) for land-cover prediction and multispectral anomaly detection. Over 100 peer-reviewed publications span journals like IEEE Transactions on Geoscience and Remote Sensing, with impactful contributions to GPU-optimized algorithms and open-source tools like HypeRvieW. Professional service includes organizing HDCRS Summer Schools on high-performance geospatial AI and chairing Euro-Par workshops. Her team develops cutting-edge solutions for environmental monitoring and sustainable computing.

David Mera Perezمشاهده پروفایل

استاد

• Machine Learning
• Environmental Data Systems
• Oceanography
• +۳ مورد دیگر

David Mera Perez is a Professor at the Department of Electronics and Computing, affiliated with the Higher Technical School of Engineering at the University of Santiago de Compostela. He holds a PhD in Computer Science from the same institution, completed in 2013 with a thesis on virtual oceanographic laboratories leveraging Grid computing. His research focuses on machine learning applications in environmental monitoring, geospatial data systems, and smart infrastructure. He leads the COGRADE research group (Computer Graphics and Data Engineering). Key areas include oil spill detection via SAR imagery, inverse problem solutions in medical imaging, and smart building temperature forecasting. He has contributed to frameworks like GeoHbbTV for interactive geographic TV content and Retelab, a geospatial Grid laboratory for oceanographic research. His work bridges computational methods with real-world challenges in environmental science and engineering.

Antonio Jesús García Loureiroمشاهده پروفایل

استاد

• Semiconductor Device Modeling
• Semiconductor Physics
• Parallel Computing
• +۳ مورد دیگر

Antonio Jesús García Loureiro is a Professor at the University of Santiago de Compostela (USC), affiliated with the Department of Electronics and Computing within the Faculty of Physics. He is part of the ARQCOMP research group and the Center for Research in Intelligent Technologies (CITIUS). His primary research focuses on semiconductor device modeling, semiconductor physics, and parallel computing, with significant contributions to solar cell technology and high-performance computing. He holds a PhD from USC (2000) with a thesis on semiconductor device simulation. His work bridges computational modeling, nanoelectronics, and renewable energy systems, emphasizing applications like photovoltaic converters and advanced materials. Research Interests : 3D semiconductor device simulation using finite element methods Optimization of solar cell efficiency (CIGS, tandem structures) Nanoscale transistor performance under process variability Laser power conversion systems for space and terrestrial use Machine learning tools for semiconductor data analysis Labs/Teams : Active in CITIUS and ARQCOMP, leading projects on semiconductor device simulation, parallel computing architectures, and energy-efficient systems. Recent Trends in Publications : Current work emphasizes GaN-based photovoltaic systems for space, high-efficiency tandem solar cells, and quantum transport effects in nanoscale FETs.

• High Performance Computing (HPC)
• Big Data
• Parallel Computing
• +۵ مورد دیگر

Cesar Alfredo Piñeiro Pomar is an Assistant Professor at the University of Santiago de Compostela, affiliated with the Department of Electronics and Computing within the Higher Technical School of Engineering. His research focuses on bridging High Performance Computing (HPC) and Big Data technologies, with a strong emphasis on parallel computing, heterogeneous programming frameworks, and bioinformatics applications. He holds a Doctorate from the University of Santiago de Compostela, awarded in 2022 for his thesis on 'New technologies to bridge the gap between High Performance Computing (HPC) and Big Data.' His academic contributions span the design of interoperability frameworks for HPC and Big Data, development of scalable Big Data toolkits (e.g., BigSeqKit for genomics data), and multilingual linguistic analysis tools like LinguaKit. He has also worked on distributed algorithms such as Fast Distributed kNN Graph Construction and optimized phylogeny estimation methods in Very Fast Tree. His publications reflect a focus on parallelization strategies, framework design, and cross-disciplinary applications of computing technologies. While no specific grants or awards are listed, his research demonstrates expertise in integrating computational paradigms to address large-scale data challenges in science and engineering.

PABLO QUESADA BARRIUSOمشاهده پروفایل

استاد

• Remote Sensing
• Parallel Computing
• GPU Acceleration
• +۳ مورد دیگر

Pablo Quesada Barriuso is a Professor at the University of Santiago de Compostela's Department of Electronics and Computing, affiliated with the Higher Technical School of Engineering. He holds a PhD in Information Technology (2015, Cum Laude) from the same institution, focusing on real-time spectral-spatial classification of n-dimensional images using GPUs. His research emphasizes parallel computing techniques for hyperspectral/multispectral remote sensing data processing, targeting low-cost devices to optimize real-time analysis and storage efficiency. Research interests include GPU-accelerated algorithms, wavelet-based denoising, mathematical morphology, and deep learning applications for environmental monitoring. He has been part of the Computer Architecture Group since 2010, contributing to projects like the Galician Rivers Multispectral Anomaly Detection Dataset and CGAN-based reconstruction models. His publications (2013-2025) highlight innovations in superpixel segmentation, watershed algorithms on GPUs, and ELM-based classification systems. While no awards are explicitly listed, his work demonstrates significant contributions to efficient GPU computing for remote sensing challenges. Advising and grants information is not detailed in the provided text. His work is closely tied to the ARQCOMP (Computer Architecture) research group, exploring hardware-software co-design for high-performance imaging solutions.

• Semiconductor Device Simulation
• Nanoelectronics
• Quantum Transport in Nanostructures
• +۳ مورد دیگر

Natalia Seoane Iglesias is a Professor at the University of Santiago de Compostela, affiliated with the Department of Electronics and Computing within the Higher Technical School of Engineering. She holds a PhD from the same institution (2007), focusing on optimizing parallel 3D simulators for studying HEMT device fluctuations under the guidance of Dr. Antonio García Loureiro. Her research expertise spans semiconductor device simulation, nanoelectronics, and quantum transport phenomena in nanostructures. She has pioneered work on advanced transistor architectures (e.g., nanosheet/nanowire FETs), materials like GaN and SiC for space applications, and machine learning-driven optimization tools for semiconductor technologies. Her work bridges computational modeling (Monte Carlo, NEGF methods) with experimental nanofabrication challenges. Recent contributions include developing MLFoMpy for TCAD data analysis, high-efficiency laser power converters using SiC, and benchmarking future transistor nodes below 2nm. Her research group (ARQCOMP) focuses on variability reduction in nanoscale devices and sustainable semiconductor manufacturing. Her publications emphasize statistical variability studies in FinFET/NFET architectures, quantum corrections in 3D simulations, and the application of AI to reduce carbon footprint in nanodevice design. She has co-authored over 100 peer-reviewed articles, with a focus on device physics, materials innovation, and computational tools for nanoelectronics.

Javier Carrasco Rodriguezمشاهده پروفایل

پژوهشگر

• Electrochemical Energy Storage
• Materials Science
• Computational Modeling
• +۴ مورد دیگر

Javier Carrasco Rodriguez is a Group Leader at CIC energiGUNE, leading the Atomistic Modelling and Computational Studies group since 2013. His research focuses on computational modeling for energy storage materials, including batteries and fuel cells. He holds a PhD from Universitat de Barcelona (2006) and has held fellowships at the Fritz Haber Institute (Max Planck Society), University College London, and the Instituto de Catálisis y Petroleoquímica. His expertise spans density functional theory (DFT), first-principles simulations, and machine learning for materials discovery. Research interests include solid-state electrolytes, ion transport mechanisms, and high-throughput screening of battery materials. He has contributed to over 100 publications and holds patents on solid electrolyte compositions. Awards include the Lee Hsun Young Scientist Lecture Series Award (2019). His work bridges theoretical chemistry, solid-state physics, and engineering to advance sustainable energy technologies. Education: PhD in Chemistry, Universitat de Barcelona (2006); Alexander von Humboldt Fellow (2007–2009), Newton International Fellow (2009–2011), Ramón y Cajal Fellow (2011–2013). Research Themes: Electrochemical energy storage (batteries, solid-state electrolytes), computational modeling of materials, nanoscale ion dynamics, and application of machine learning to accelerate discovery. Key Contributions: Development of atomistic models for Li-ion and Na-ion battery materials, computational screening of fast-ion conductors, and elucidation of interfacial phenomena in solid-state batteries. His group also explores novel electrolyte designs and phase transformations in electrode materials. Grants & Collaborations: Leads projects like HELENA (solid-state battery innovation) and ADEL (high-throughput screening). Collaborates globally with institutions like CICECO Aveiro and CSRC. Labs/Teams: Directs the Modelling and Computational Simulation team at CIC energiGUNE, specializing in multi-scale simulations and data-driven materials science.

• Autonomous Vehicles
• Computer Vision
• Intelligent Transportation Systems
• +۵ مورد دیگر

Jose Maria Armingol Moreno is a Full Professor at the University Carlos III of Madrid, affiliated with the Department of Systems Engineering and Automation. He serves as Director of the Master's Degree in Internet of Things: Applied Technologies and leads the Intelligent Systems Laboratory research group within the Duque de Santomauro Institute of Motor Vehicle Safety. His expertise spans autonomous systems, computer vision, robotics, and intelligent transportation infrastructure. Key research interests include vehicle safety, sensor fusion, and deep learning applications in traffic monitoring and autonomous navigation. He has authored over 100 peer-reviewed articles, with recent work focusing on 3D vehicle detection, UAV battery systems, and intelligent infrastructure for smart cities. Dr. Armingol has also led numerous projects on autonomous vehicle development, cooperative driving systems, and traffic safety technologies. His contributions include patented innovations in vehicle inspection and collision avoidance systems.