Roles and Affiliations: José María Alonso Moral is an Associate Professor at the Department of Electronics and Computing within the Higher Technical School of Engineering at the University of Santiago de Compostela (USC). He is affiliated with the Center for Research in Intelligent Technologies (CiTIUS-USC) and leads research in the Intelligent Systems Group (GSI). Education: PhD in Telecommunication Engineering from Universidad Politécnica de Madrid (2007) with Outstanding Cum Laude and Doctor Europeus distinctions Senior Engineer in Telecommunications (2003) from UPM Research Interests: His work focuses on Explainable and Trustworthy AI , Interpretable Fuzzy Systems , and Natural Language Generation . He explores AI applications in healthcare, environmental science, and ethical AI frameworks. His efforts emphasize human-centric AI systems that balance technical performance with transparency and accountability. Key Projects and Contributions: Principal Investigator in projects like TRUST and CONFIA addressing trustworthy AI and human trust dynamics Developed tools like ExpliClas for natural language explanations of machine learning models Authored over 190 publications in journals like IEEE Computational Intelligence Magazine and Information Sciences Awards and Roles: Recipient of the prestigious Ramón y Cajal Fellowship (2016–2022) Editorial roles at IEEE Computational Intelligence Magazine and International Journal of Approximate Reasoning Chair of Doctoral Consortium at ECAI 2020 and member of IEEE-CIS committees Labs and Teams: Leads research in the Intelligent Systems Group (GSI) and collaborates with CiTIUS-USC on interdisciplinary AI projects.
جستجوی استاد راهنمای دانشگاهی
برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۷۳۶-۷۵۰ از ۱٬۶۱۹ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Senén Barro Ameneiro is a Professor of Computer Science and Artificial Intelligence at the University of Santiago de Compostela (USC), affiliated with the Department of Electronics and Computing under the Faculty of Physics. He served as Rector of USC from 2002 to 2010, instrumental in developing 'Campus Vida' and boosting research and innovation. His research focuses on fuzzy logic, robotics, and medical informatics, with over 300 publications. Awards include the 2020 José García Santesmases National Informatics Award. He co-founded spin-offs SITUM Technologies and InVerbis, and chairs the Royal Galician Academy of Sciences. Education: PhD in Physics (extraordinary award) from USC (1988). Leadership Roles: Former Chancellor of USC, Vice-President of西班牙大学校长会议, President of RedEmprendia (2010–2017). Research Projects: Overseeing EU, national, and international contracts in AI and intelligent systems. Key collaborations include work at the University of Maryland, UC Berkeley, and Bristol University. Publications: Notable works include Fuzzy Logic in Medicine and influential papers on machine learning and fuzzy quantifiers. His work bridges theoretical computer science with applied domains like healthcare and robotics.
Alejandro Catalá Bolós is an Assistant Professor at the University of Santiago de Compostela (USC), affiliated with the Center for Research in Intelligent Technologies (CiTIUS) and the Intelligent Systems Group. He holds a PhD from the Universitat Politècnica de València (2012) and has held postdoctoral positions at the University of Twente (Netherlands) and the University of Castilla-La Mancha. His work focuses on Human-Computer Interaction, Trustworthy AI, and Explainable Artificial Intelligence, integrating multimodal interfaces, robotics, and tangible interaction. Education: PhD in Computer Science, Universitat Politècnica de València (2012) MSc in Software Engineering, Universitat Politècnica de València (2008) BEng in Computer Science, Universitat Politècnica de València (2006) Research Interests: Catalá explores how interaction technologies can enhance creativity, learning, healthcare, and entertainment through multimodal interfaces. He emphasizes explainable AI systems, ethical AI practices, and user-centered design principles. His work bridges tangible computing, augmented reality, and dialogue systems to build trustworthy human-AI collaborations. Publications & Impact: With over 70 publications, his research addresses lexical alignment in conversational agents, counterfactual explanations for machine learning, and AI literacy in K-12 education. Recent work focuses on regulatory frameworks for explainable AI in the EU and dementia care technologies like the Emobook app. Grants & Awards: Marie Skłodowska-Curie Individual Fellowship (EU Horizon 2020) Juan de la Cierva-Incorporación Grant (Spain) Best Student Award in Computer Science (UPV, 2006) Labs & Teams: Leads research in CiTIUS's Intelligent Systems Group, collaborating with interdisciplinary teams on projects like the coBOTnity EU initiative and sustainable AI frameworks. Active in organizing workshops such as MAI-XAI and NL4XAI.
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 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 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 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.
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 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 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.
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.
- 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.
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.
Eduardo Sánchez-Diez is a Research Team Leader and Research Line Manager at CIC energiGUNE, specializing in Electrochemical Energy Storage. He holds a B.S. in Chemistry from the University of the Basque Country (UPV/EHU) and a Ph.D. in asymmetric organocatalysis from the same institution under Prof. Jose Luis Vicario. His postdoctoral research focused on polymer electrolytes for lithium batteries at CIC energiGUNE, and he has since expanded his work to redox flow batteries, particularly in electrolyte development for stationary energy storage. His research emphasizes stable polymers, novel salts for low-temperature lithium batteries, and organic-based electrolytes for next-generation systems. His career includes a visiting period at the Toste Group at UC Berkeley (2015) to study fluorination chemistry and collaborations with institutions like the University of the Basque Country. Key research areas include polymer electrolytes, redox flow battery technology, and the design of high-performance electrolytes. He has contributed to patents on solid electrolytes and methods for preparing ionic compounds, often collaborating with researchers like Michel Armand and Heng Zhang. Eduardo’s work bridges fundamental chemistry and applied energy storage solutions, aiming to advance sustainable technologies. His publications focus on improving ion conductivity, battery safety, and material stability, with recent studies exploring single-ion-conducting electrolytes and computational modeling of redox flow systems. His research aligns with global efforts to enhance renewable energy storage through innovative materials and electrochemical strategies.
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.
نمایش نتایج تا ۷۵۰ مورد اول. برای یافتن نتایج دقیقتر، جستجوی خود را با فیلترها محدود کنید.