Represa Pérez, César is a faculty member at the University of Burgos , affiliated with the School of Engineering . He has contributed extensively to computer science, parallel computing, and embedded systems through research articles, educational materials, and conference presentations. Education: Doctorate in Parallel & Hybrid Programming (2002). Research Areas: Parallel computing (MPI/CUDA), 3D virtual labs, sensor technology, Android applications, and embedded systems design. Key Collaborations: Co-authored works with José María Cámara Nebreda, Pedro L. Sánchez Ortega, and others on technical education and hardware-software integration. Recent Trends: Focus on smartphone-driven sensors, additive manufacturing monitoring, and educational tools for engineering students.
Francesc Arandiga Llau is a Professor in the Department of Mathematics at the Faculty of Mathematics, Universitat de València, Spain. He is affiliated with the ANIMS (Numerical Analysis, Images, Multiresolution and Simulation) research group, where he conducts research in applied mathematics with a focus on numerical methods and their applications. Education: PhD from Universitat de València (1992), thesis on operator approximation and spectral radius continuity, supervised by Dr. Vicent Caselles Costa. His research interests center on Numerical Analysis , Approximation Theory , and Multiresolution Methods , with significant contributions to WENO schemes , nonlinear interpolation , and image and signal compression . His work often bridges theoretical developments with practical implementations in computational mathematics and engineering. He has made notable advances in the stability, accuracy, and adaptability of reconstruction techniques for piecewise smooth and discontinuous functions. The analysis of his recent publications reveals a consistent focus on high-order numerical methods, particularly in the context of image processing and data compression . His work leverages multiresolution analysis , radial basis functions , and adaptive interpolation to improve accuracy and efficiency. Themes across his articles include monotonicity preservation, error control, and the design of nonlinear schemes that avoid spurious oscillations near discontinuities. There are no scientific awards explicitly mentioned in the provided text. Francesc Arandiga has extensive collaborative research, particularly with scholars such as Rosa Donat, Dionisio F. Yáñez, Pep Mulet, and Antonio Baeza. His work has been supported through various research projects, though specific grants are not detailed in the text. He has advised students, including those who have completed theses under his supervision, although a full list is not provided. He is a key member of the ANIMS research group, which focuses on Numerical Analysis, Images, Multiresolution, and Simulation. This team works on developing and analyzing advanced computational methods for scientific and engineering applications, particularly in the areas of data representation, image processing, and numerical solutions to differential equations.
Marta Rosa Hidalgo García is a faculty member in the Department of Mathematics at the Faculty of Mathematics, University of Valencia. She holds the academic rank of Assistant Professor (Ajudant Doctor) and is affiliated with the ANIMS research group, focusing on Numerical Analysis, Images, Multiresolution, and Simulation. Institution: University of Valencia School: Faculty of Mathematics Department: Department of Mathematics Research Group: ANIMS Email: marta.hidalgo@uv.es She received her PhD in 2013 from the Universitat Politècnica de Catalunya under the supervision of Dr. Robert Joan Arinyo. Her doctoral research centered on geometric constraint solving within dynamic geometry frameworks. Her research interests lie at the intersection of applied mathematics and computer science, particularly in geometric constraint solving, computational geometry, and graph theory. Her work involves algorithmic approaches to generating and analyzing minimally rigid graphs using Henneberg sequences, with applications in computer-aided design and symbolic computation. Her publication record includes a notable 2017 paper in the Journal of Symbolic Computation , which demonstrates her expertise in developing efficient algorithms for tree-decomposable minimally rigid graphs. The analysis of her research output indicates a strong focus on theoretical foundations of rigidity and constraint systems, with implications for automated geometric reasoning. Primary Field: Applied Mathematics Core Topics: Geometric Constraint Solving, Graph Algorithms, Rigidity Theory Marta Rosa Hidalgo García continues to contribute to the field through her research in applied mathematics, though no scientific awards or student advisement details are publicly documented in the provided sources. She is an active researcher with a solid foundation in mathematical computing and algorithmic geometry, contributing to both theoretical advances and practical applications in her domain.
Raquel Dosil Lago 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. Her research focuses on Artificial Vision, Computer Vision, and Robotics, with applications in environmental monitoring and medical imaging. She holds a PhD in Computer Science from the University of Santiago de Compostela (2005), supervised by Dr. José Ramón Fernández Vidal and Dr. José Manuel Pardo López. Her research interests emphasize multisensory systems, drone-based environmental surveillance, visual attention models, and feature detection in 3D medical imaging. Recent work includes drone payloads for maritime pollution detection and biologically inspired vision systems. Earlier contributions span saliency detection, photogrammetry, and composite feature integration for motion analysis. Publications reflect a progression from early medical imaging and 3D pattern partitioning (2000s) to modern drone and environmental applications (2020s). Key themes include sensor fusion, CNN-based detection, and human-like visual attention mechanisms. She is part of the Artificial Vision research group, collaborating on projects like BIVSEE and AVSS challenges. No scientific awards are explicitly mentioned. Her academic advising includes her doctoral thesis committee. Research grants and future work details are not provided in the source text.
Jose Luis Cantero Guisandez is a Full Professor at the Department of Mechanical Engineering, University Carlos III of Madrid. He is affiliated with the Álvaro Alonso Barba Institute of Chemistry and Materials Technology and leads the 'Mechanical and Biomechanical Component Manufacturing and Design Technology' research group. His work focuses on advanced machining processes, tool wear monitoring, composite materials (especially CFRP), and aerospace component fabrication. Key research interests include drilling process optimization for hybrid material stacks, tool failure detection using signal analysis (wavelet transforms), and machine learning applications in manufacturing systems. He has published extensively on topics like Inconel 718 machining, Haynes 282 finishing, and MQL drilling techniques. Current projects involve collaboration with Airbus on drilling process improvement (funded by Airbus Operations S.L.) and digitalization of industrial drilling systems (DIGITDRILL project with AEI). He has supervised multiple theses on tool health monitoring and multi-material drilling optimization. His work integrates experimental analysis with numerical modeling, addressing challenges like delamination in CFRP drilling and thermal effects in dry machining. Recent efforts emphasize data-driven approaches for process control and predictive maintenance in aerospace manufacturing.
Saturnino Maldonado Bascón is a full Professor at the Universidad de Alcalá, affiliated with the Signal Theory and Communications Department. His research focuses on advanced signal processing techniques, machine learning applications, and computer vision systems. He earned his doctorate from Universidad de Alcalá in 1999 with a thesis on multiresolution analysis for image compression. Key research interests include traffic sign recognition, video surveillance algorithms, 3D object recognition, and noise reduction in digital images. His work frequently employs support vector machines (SVM), spatial pyramids, and clustering methods to address challenges in robotics, autonomous systems, and sensor data analysis. Publications highlight contributions to vehicle tracking, odometry correction in differential robots, and efficient video annotation techniques. His research group (GRAM) develops multisensorial analysis solutions for intelligent infrastructure systems like the WHISNU platform. Maldonado has explored diverse applications from biomedical signal processing to traffic management systems through grants and collaborative projects. No scientific awards are explicitly mentioned, but his extensive publication record reflects sustained academic impact. He leads a research team focused on real-time systems, sensor fusion, and computer vision applications in both academic and industrial contexts.
Pep Mulet Mestre is a full Professor in the Department of Mathematics at the Faculty of Mathematics, Universitat de València. He is a member of the ANIMS research group, focusing on Numerical Analysis, Images, Multiresolution, and Simulation. University: Universitat de València School: Faculty of Mathematics Department: Department of Mathematics Research Group: ANIMS His primary research interests include numerical analysis, partial differential equations, fluid mechanics, image processing, and high-order finite difference methods. He has made significant contributions to WENO schemes, total variation-based image restoration, and models for sedimentation and traffic flow. The 15 most recent publications highlight a consistent focus on high-order accurate numerical methods, particularly WENO and IMEX schemes, applied to conservation laws, image processing, and biological models. His work bridges theoretical numerical analysis with practical applications in fluid dynamics and epidemiology. He has collaborated extensively with researchers such as Raimund Bürger, Rosa Donat, Antonio Baeza, and David Zorío, resulting in over 60 indexed publications since 1996. Dr. Mulet earned his PhD from the Universitat de València in 1992 with a thesis on local cohomology and duality in non-commutative Gorenstein rings, supervised by Dr. A. Verschoren. He advises graduate students and leads research projects in numerical methods for PDEs and scientific computing, though specific advisees are not listed in the provided text. There is no mention of specific grants or scientific awards in the available information.
Damien Rohmer is a Professor of Computer Science at École polytechnique , Institut Polytechnique de Paris. He leads the VISTA research team at LIX (CNRS UMR 7161) and serves as Deputy Director of LIX since 2024. Current PhD supervisions with ANR/CIFRE funding Open-source tool development for computer graphics education Editorial roles in SCA, MIG, SIGGRAPH conferences His research spans 3D modeling , real-time animation , and user-interactive simulation , with applications in entertainment, medical sciences, and design. Key sub-areas include: Character motion retargeting Multi-scale natural phenomenon simulation Field-based implicit modeling Wearable technology visualization Gesture-controlled animation systems Recent publications in SIGGRAPH , Eurographics , and SCA earned multiple Best Paper/Poster awards in 2024-2025. He co-develops the CGP library for educational 3D programming and maintains community resources for French computer graphics institutions.
Antonio Baeza Manzanares is an Associate Professor in the Department of Mathematics at the Faculty of Mathematics, University of Valencia, Spain. He is a member of the ANIMS research group, focusing on Numerical Analysis, Images, Multiresolution, and Simulation. He obtained his PhD in 2010 from the University of Valencia under the supervision of Dr. Pep Mulet Mestre. PhD, University of Valencia, 2010 His research lies at the intersection of numerical analysis and applied mathematics, with a strong emphasis on developing high-order accurate numerical methods for partial differential equations. His work is particularly influential in the design and analysis of WENO schemes, finite difference methods on complex domains, adaptive mesh refinement, and Taylor-type integrators for ODEs. These methods are essential for simulating fluid dynamics and conservation laws with high fidelity. The trend in his recent publications shows a sustained focus on improving the accuracy, efficiency, and robustness of numerical schemes, especially for problems involving shocks, complex geometries, and boundary treatments. He frequently publishes in leading journals such as the Journal of Scientific Computing and SIAM Journal on Numerical Analysis . He has no listed scientific awards in the provided text. Antonio Baeza actively collaborates with prominent researchers including Pep Mulet, David Zorío, Raimund Bürger, and Francesc Aràndiga. His work is supported by ongoing research projects and contributions to the mathematical community through publications and group leadership. He advises students within the ANIMS group, though specific names are not listed. He is affiliated with the ANIMS (Numerical Analysis, Images, Multiresolution and Simulation) research group, which conducts interdisciplinary work in computational mathematics, image processing, and scientific simulation.
Francisco Guerrero Cortina is a permanent academic faculty member at the University of Valencia, affiliated with the Faculty of Mathematics, Department of Mathematics, and the Applied Mathematics area. He is a member of the ANIMS research group, focusing on Numerical Analysis, Images, Multiresolution, and Simulation. His primary research interests include Applied Mathematics , Numerical Analysis , Mathematical Modeling , and Epidemiology , with applications in fluid mechanics, public health, and social behavior dynamics. His work often involves high-order numerical schemes, nonstandard finite differences, and analytical approximation methods such as HAM and Padé. The recent publications indicate a strong trend in developing and applying advanced numerical methods to real-world problems, particularly in fluid dynamics and epidemiological modeling . His research bridges theoretical mathematics with practical applications in engineering and social sciences. He has collaborated extensively with researchers such as Pep Mulet, Rosa Donat, and F.J. Santonja, particularly on models for substance use in Spain. No scientific awards or student advisement details are publicly listed. He holds a PhD from the University of Valencia (1999), supervised by Dr. Antonio Pich, and continues to publish actively, with recent work appearing in 2025. His email is francisco.guerrero-cortina@uv.es, confirming current institutional engagement.
Sergio López Ureña is a permanent faculty member (Prof. Permanente Laboral) in the Department of Mathematics at the Universitat de València, Spain. He is affiliated with the Faculty of Mathematics and the ANIMS (Numerical Analysis, Images, Multiresolution and Simulation) research group, focusing on applied mathematics. His research lies at the intersection of numerical analysis and approximation theory, with a strong emphasis on subdivision schemes, signal processing, and multiresolution methods. He develops advanced mathematical tools for high-accuracy approximation of piecewise smooth functions and nonlinear subdivision techniques that reproduce exponential and trigonometric functions. His work combines theoretical analysis with computational applications, particularly in geometric modeling and data processing. Based on his recent publications, López Ureña has been actively contributing to the advancement of subdivision schemes, especially in the areas of non-oscillatory interpolation, reproduction of exponential polynomials, and convergence analysis via weighted local polynomial regression. His work demonstrates a consistent focus on improving accuracy and stability in numerical approximation. Dr. Rosa María Donat Beneito (PhD advisor) Costanza Conti Alberto Viscardi Dionisio F. Yáñez Francesc Aràndiga He has published in leading journals such as Applied Mathematics and Computation , Journal of Computational and Applied Mathematics , and Advances in Computational Mathematics . While no formal awards or student advisement details are mentioned, his active publication record since 2017 indicates a strong research trajectory. He is based in the Faculty of Mathematics, contributing to both theoretical and computational aspects of applied mathematics.
MARIA CARMEN MARTI RAGA is a Professor in the Department of Mathematics at the Faculty of Mathematics, University of Valencia. Her academic work is centered on applied and computational mathematics, with a strong focus on numerical methods for differential equations and simulation. Her research interests lie primarily in Applied Mathematics , Numerical Analysis , and Scientific Computing . She is a member of the ANIMS research group, which specializes in Numerical Analysis, Images, Multiresolution, and Simulation. Her work involves the development and analysis of computational techniques, particularly for finite-difference schemes and systems of conservation laws. Her recent publications indicate a strong trend in the numerical solution of ordinary differential equations and partial differential equations, especially those modeling physical phenomena like sedimentation and flotation. The research employs advanced numerical methods such as implicit Taylor methods and finite-difference WENO schemes. She completed her PhD at the University of Valencia in 2014 with a thesis on new computational techniques for finite-difference weighted essentially non-oscillatory schemes. Email: maria.c.marti@uv.es
Giovanni Trappolini serves as Assistant Professor at Sapienza University of Rome within the Department of Computer, Control, and Management Engineering, conducting research at the RSTLess Lab under Prof. Fabrizio Silvestri. Previously, he completed his Ph.D. in Machine Learning at Sapienza under Prof. Emanuele Rodolà, following an MSc in Data Science where he graduated cum laude as a Sapienza honor graduate. His educational background includes: MSc in Data Science, Sapienza University of Rome (cum laude, Sapienza honor graduate) Ph.D. in Machine Learning, Sapienza University of Rome (2022) BSc from Luiss Guido Carli Trappolini's research bridges Machine Learning and Deep Learning with emphases on multimodal systems and information retrieval . He pioneers applications in Graph Neural Networks security, Federated Learning architectures, and Italian-language Large Language Models —notably creating Fauno , Italy's leading LLM. His work extends to operating system innovation through generative AI, 3D shape analysis using transformers, and creative applications like AI-driven music generation. Analysis of his 2023 publications reveals dominant trends toward integrating retrieval systems with generative models (RAG), developing robust neural databases, and enhancing cross-modal understanding. Key themes include adversarial defense for graph networks, privacy-preserving federated retrieval, and transformer-based geometric learning—demonstrating consistent focus on foundational AI infrastructure. Scientific recognition includes: Sapienza honor graduate Cum laude graduate distinction Trappolini actively contributes to academic instruction through courses including Advanced Data Mining and Language Technologies (Sapienza, 2023) and multiple iterations of Python Programming for Data Science (2019-2023). He maintains significant research collaborations with Stanford, Technion, Meta, Amazon, TII, and UniPi while preparing new PhD-level coursework in Geometric Deep Learning for 2024. His research operates within the RSTLess Lab ecosystem, focusing on scalable AI systems and multimodal integration.
Marta Fairén is an Assistant Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the ViRVIG (Visualització, Realitat Virtual i Interacció Gràfica) Research Group and serves as a senior researcher at the Virtual Reality Center of Barcelona . Her work focuses on advanced VR systems and software development platforms. Department of Computer Science (CS), UPC ViRVIG Research Group Virtual Reality Center of Barcelona Research Interests Virtual Reality software and interfaces with emphasis on collaborative environments Haptic device integration for tactile feedback Visualization of large-scale models in immersive settings Distributed systems for graphics applications GPU-accelerated algorithms for collision detection Educational technology in computer graphics and programming Research Trends The 15 most recent articles demonstrate ongoing work in VR training applications (2024), medical education (2023-2020), haptic rendering techniques (2016-2007), and educational software frameworks (2020-2006). Key themes include GPU optimization, surface detail modeling, and adaptive teaching tools. Scientific Awards Advising & Grants No formal student advisees are listed in the provided content, and grant details are not explicitly mentioned. Labs & Teams Active member of the ViRVIG Research Group and senior researcher at the Virtual Reality Center of Barcelona , focusing on collaborative VR environments and distributed graphics systems.
Lucas Cuadra Rodríguez is a Full Professor in the Department of Signal Theory and Communications at Universidad Alfonso X El Sabio (UAX). He holds a PhD from Universidad Politécnica de Madrid (2004), specializing in intermediate band solar cell development. His research spans quantum dot systems, network science applications in materials and energy systems, and machine learning for environmental and engineering challenges. Key areas include photovoltaic materials, complex network modeling of disordered systems, and renewable energy optimization. Education: Doctorado en Física from Universidad Politécnica de Madrid (2004), supervised by Dr. Antonio Marti Vega and Dr. Antonio Luque López. His work bridges physics, computer science, and engineering, with a focus on interdisciplinary solutions for energy and environmental systems. Research Interests: His primary focus is on developing novel semiconductor solar cell structures, particularly quantum dot-based intermediate band solar cells, and applying network science to study carrier transport in nanomaterials. He also explores machine learning applications in Earth observation, wind energy prediction, and complex system analysis. His recent work emphasizes spatially embedded networks and their relevance to material science and renewable energy infrastructure. Notable Projects: Leading the GHEODE Research Group (Modern Heuristics and Network Design), he investigates optimization algorithms for smart grids and network robustness. Recent studies include modeling electron transport in van der Waals materials and analyzing fog event persistence through nonlinear dynamics. Awards: No specific awards mentioned in the provided text. Advising & Grants: While his PhD supervision details are noted, no current student advisees or grant projects are detailed here. His work often involves collaborative interdisciplinary projects with engineering and environmental science teams. Labs/Teams: Active in the GHEODE Group at UAX, focusing on heuristic algorithms and network-based solutions for engineering challenges.
