Joaquim Agullo Batlle is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mechanical Engineering at the Barcelona School of Industrial Engineering (ETSEIB). His research focuses on musical acoustics, percussive dynamics, automatic guidance systems, and omnidirectional wheel design. He has authored numerous publications and collaborated on projects related to multibody dynamics, robotics, and vibration analysis. His academic career includes over 295 documented activities, spanning research articles, book chapters, and contributions to conferences. Notable works include studies on rigid body dynamics, impact scenarios in mechanical systems, and acoustic analysis of musical instruments. He has also contributed to educational materials, such as textbooks on mechanical engineering and vibration theory. Agullo Batlle’s research has addressed practical applications like robot calibration, mobile localization, and the design of orthotic devices for spinal injury patients. His work frequently intersects engineering mechanics with interdisciplinary fields like acoustics and mechatronics.
Pedro Ignacio Álvarez Peñín is a Professor at the University of Oviedo, Department of Construction and Manufacturing Engineering, specializing in Graphic Expression in Engineering. His research focuses on Computer-Aided Design (CAD), educational technology, and applications of graphic engineering. He has directed four doctoral theses and actively contributes to academic conferences and publications. Notable projects include the development of platforms like DIBUTEC and Selfcad, which enhance interactive learning in CAD and engineering graphics. His work integrates CAD with medical imaging for surgical simulations and explores BIM technology in industrial education. He has collaborated extensively on projects addressing curriculum adaptation to European standards and modernizing technical drawing education through multimedia and web-based tools. Institutions: University of Oviedo (1988–present) Education: Ph.D. in Graphic Design Systems from the University of Oviedo (1988). Research Interests: CAD in education, interactive learning systems, BIM technology, medical imaging applications, graphic engineering pedagogy, and software integration for engineering projects. He emphasizes practical applications of CAD tools in both academic and industrial contexts. Articles Trends: His work spans CAD education, software development for engineering documentation, and the integration of technology into teaching. Recent projects highlight cross-platform tools (e.g., DIBUTEC), mobile applications for energy simulation, and BIM-based industrial training. Earlier contributions explored algorithmic approaches to CAD systems and 3D modeling for surgical planning. Directed Theses: Bernardo Busto Parra (2016): Industrial project management with ICT. Pablo Pando Cerra (2006): 3D CAD learning environments. Ramón Rubio-García (2003): Modular CAD applications. Maximo Roman Perez Morales (2002): Descriptive geometry teaching tools. Grants/Projects: Multiple collaborations on EU-funded educational technology initiatives and graphic engineering research. Labs/Teams: Part of the University of Oviedo’s Graphic Engineering research group, focusing on CAD integration and educational innovation.
Conrado Martinez Parra is a Professor in the Department of Computer Science at the Faculty of Computer Science, Universitat Politècnica de Catalunya (UPC). He is a core member of the ALBCOM research group, which focuses on Algorithmics, Bioinformatics, Complexity, and Formal Methods. Affiliation : Department of Computer Science, Faculty of Computer Science (FIB), UPC Research Group : ALBCOM - Algorísmia, Bioinformàtica, Complexitat i Mètodes Formals Email : conrado@cs.upc.edu ORCID : 0000-0003-1302-9067 Researcher ID : G-4629-2015 His research spans theoretical computer science with a strong emphasis on the design and analysis of algorithms and data structures. His work includes average-case analysis of algorithms, combinatorial generation, probabilistic methods in algorithmics, and applications in information retrieval and data stream processing. He has extensively studied multidimensional data structures such as quadtrees, K-d trees, and skip lists, analyzing their performance under various query models including partial match and orthogonal range searches. His recent publications reveal a sustained focus on algorithmic efficiency, sampling techniques, and probabilistic modeling in data structures. Trends indicate a deep engagement with randomized algorithms, unbiased estimation, and cache-efficient selection methods, reflecting both theoretical rigor and practical applicability in modern computing environments. Scientific Contributions Extensive publication record spanning over three decades, from 1989 to 2024. Active in major algorithmic conferences such as ANALCO, AofA, and AAAI. Contributions to foundational algorithm analysis including Hoare’s FIND, Quickselect variants, and deletion in binary search trees. Collaborative research with prominent figures in theoretical computer science across Europe. Professor Martinez Parra has advised or collaborated with several doctoral students, including Gustavo Lau, whose thesis on partial match queries he supervised. He has participated in numerous competitive R&D projects funded by national and regional programs, focusing on large-scale information processing and graph-based computing models. His work is supported by long-standing grants from Spanish and Catalan research councils. He is affiliated with the ALBCOM research group, a leading team in algorithmic research at UPC, contributing to both theoretical advances and practical implementations in combinatorics and data structure optimization.
M. Luisa Bonet Carbonell is a researcher in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB). Her work focuses on computational complexity, SAT and MaxSAT solvers, proof systems, and algorithmic optimization. She has extensive collaborations within the LOGPROG and ALBCOM research groups, contributing to projects like TASSAT3 and MULOG-2. Her research spans theoretical computer science, with emphases on proof complexity, polynomial calculus, and the analysis of industrial SAT instances. Notable contributions include studies on Sherali-Adams and Nullstellensatz proof systems, as well as the fractal dimension of SAT formulas. Over 90 publications include articles in Artificial Intelligence , Journal of Computer and System Sciences , and conferences like SAT and IJCAI. Her work bridges theoretical foundations with practical applications, such as improving MaxSAT algorithms and analyzing community structures in problem instances.
Blas Pelegrin Pelegrin is a Professor in the Department of Statistics and Operations Research at the School of Sciences, Universidad de Murcia, Spain. His academic career spans over three decades with significant contributions to operations research, particularly in location theory and competitive facility location models. Dr. Pelegrin received his doctorate from Universidad de Sevilla in 1980 with a thesis titled "Sistemas de localización en el plano con distancia general y demanda aleatoria" under the supervision of Dr. Rafael Infante Macías. His research primarily focuses on mathematical programming approaches to spatial competition problems, Stackelberg games, and optimization of facility locations. His publication record demonstrates a consistent research trajectory in competitive location models, with particular expertise in duopoly competition, price competition in spatially separated markets, and network location problems. His work often applies game-theoretic approaches to facility location problems, bridging operations research with economic theory. Dr. Pelegrin has collaborated extensively with researchers including María Dolores García Pérez, Pascual Fernández Hernández, and other colleagues in the operations research community. His work has been published in reputable journals such as Annals of Operations Research, European Journal of Operational Research, and Top.
Juan Viu Sos is an Associate Professor (Profesor Permanente Laboral) at the Universidad Politécnica de Madrid (UPM), specializing in Pure Mathematics with a focus on Number Theory and Algebraic Geometry. He has held teaching-researcher positions at institutions including the University of Pau (UPPA, France), Institut Fourier (Univ. Grenoble), University of São Paulo (2017-2019), and IMPA (2019-2020). His research has been published in top-tier journals like Advances in Mathematics (Q1 JCR) and Mathematische Annalen (Q2 JCR). Education B.S. in Mathematics (University of Zaragoza, 2011) M.Sc. in Mathematical Research (UPPA, France, 2011-2012) M.Sc. in Pure Mathematics (University of Zaragoza, 2012) Ph.D. in Pure Mathematics (UPPA and UZ, 2012-2015; Cum laude/Très bien) His research focuses on Algebra, Number Theory, and algorithmic methods using tools like SageMath and Python. He has participated in international projects across France, Brazil, and Spain, and contributed to seminars and conferences as an invited speaker. Scientific awards include competitive postdoctoral grants at the University of São Paulo and IMPA, as well as a Short Communication selection at ICM-2018. At UPM, he has coordinated subjects, created educational resources, and managed communication for the Mathematics Degree program.
Baldur Sigurdsson serves as an Assistant Professor in the Department of Mathematics and Computer Science Applied to Civil and Naval Engineering at Universidad Politécnica de Madrid, actively contributing to the Geometry and its applications research group as verified in September 2024 institutional records. His research centers on geometric methodologies with strong emphasis on applied mathematics and computational geometry, specifically targeting civil and naval engineering challenges through computer science integration. This interdisciplinary approach bridges theoretical geometry with practical engineering solutions, focusing on structural modeling and fluid dynamics applications where geometric precision is critical. As a core member of the Geometry and its applications research group, he participates in developing algorithmic frameworks for engineering simulations, with particular attention to maritime infrastructure and civil construction projects requiring advanced spatial analysis.
Gonzalo Besuievsky is Associate Professor at the Department of Computer Science and Applied Mathematics of the University of Girona , Spain. He leads research on physically-based rendering and global illumination, with particular emphasis on Monte-Carlo methods and dynamic radiosity environments. Education: PhD in Computer Science, Universitat Politècnica de Catalunya , 2001 — Dissertation: "A Monte Carlo Approach for Animated Radiosity Environments" Research Interests: His work spans several inter-related domains: Global Illumination & Radiosity: developing algorithms for realistic light transport in synthetic scenes. Monte Carlo Techniques: adaptive and hierarchical sampling to accelerate rendering. Dynamic Environments: efficient update schemes for animated lighting and moving light sources. Daylighting Simulation: integrating sunlight models into architectural 3-D workflows. Motion Blur & Temporal Coherence: novel methods to render motion-blurred radiosity images. Publication Trends: Across his 1993–2006 publications, a clear evolution is visible from foundational stochastic ray-tracing work toward sophisticated Monte-Carlo radiosity frameworks that handle dynamic lighting, daylighting, and frame-to-frame coherence for animations. Labs & Groups: He is affiliated with the Girona Graphics Group , a research team devoted to advanced graphics and visualization technologies.
Isabel Navazo is a Lecturer at the Department of Computer Languages and Systems, Polytechnic University of Catalonia, Spain. Her work focuses on medical imaging applications, volume and solid modeling, virtual reality, and occlusion culling. Research Interests: She specializes in Volume and Solid Modeling , Virtual Reality , and Medical Applications , particularly in colon segmentation, volumetric rendering, and interactive visualization tools. Her research often bridges computational methods with clinical diagnostics. Publication Trends: Recent articles highlight her contributions to MRI segmentation, medical visualization, and haptic rendering. Key themes include colonic content analysis , interactive exploration of medical data , and texture-based hybrid visualizations for diagnostic applications.
Alvar Vinacua is an Associate Professor at the Polytechnic University of Catalonia , affiliated with the Computer Languages and Systems department. His work focuses on computational geometry and immersive software interfaces. Research areas include Computer-Aided Geometric Design and Computational Geometry Algorithms Specializes in Virtual/Enhanced Reality software and interfaces
Dr. Manuel Ángel Aguilar Torres is a Professor in the Department of Engineering at the University of Almería, Spain, where he leads the research group 'Integrated Territory Management and Spatial Information Technologies.' With an h-index of 29 (Scopus) and 26 (Web of Science), he has established himself as a leading researcher in remote sensing applications for agricultural and forest monitoring. His research primarily focuses on plastic greenhouse mapping using satellite imagery , LiDAR technology for forest inventory , and precision agriculture applications . He specializes in object-based image analysis, spectral indices development, and the integration of multi-source geospatial data for environmental monitoring, with particular emphasis on Mediterranean ecosystems. His work has resulted in 98 journal articles, 16 book chapters, and numerous conference presentations. Dr. Aguilar Torres has served as Principal Investigator for multiple research projects, including 'Mapeado de invernaderos e identificación de cultivos hortícolas protegidos mediante análisis de imagen basada en objetos y series temporales de imágenes de satélite' (RTI2018-095403-B-I00) and 'Identificación basada en objetos de cultivos hortícolas bajo invernadero a partir de estéreo imágenes del satélite Worldview-3 y series temporales de Landsat 8' (AGL2014-56017-R). His recent publications (2022-2025) demonstrate continued productivity in remote sensing methodology development, particularly in greenhouse mapping, forest inventory using UAV and LiDAR technologies, and spectral analysis. Notable scientific contributions include: Development of novel methods for plastic greenhouse detection using multi-temporal satellite imagery Benchmarking studies of spectral indices for agricultural monitoring Advanced techniques for individual tree segmentation in Mediterranean forests Integration of UAV and terrestrial LiDAR data for forest inventory As a supervisor, Dr. Aguilar Torres has guided numerous PhD students through the completion of their theses, with former students including Rafael Jiménez Lao, Abderrahim Nemmaoui, and María del Mar Saldaña Díaz. His research group maintains active collaborations with international institutions, providing students with opportunities for cross-border research experiences. The laboratory facilities support advanced geospatial analysis, with capabilities for processing satellite imagery from platforms like Sentinel-2, WorldView-3, and Deimos-2, as well as UAV and LiDAR data processing for environmental monitoring applications.
Antonio Salmerón Cerdán is a Professor in the Mathematics Department at the University of Almería, where he has established himself as a leading researcher in probabilistic artificial intelligence and Bayesian networks. With over 25 years of academic experience, he leads the 'Análisis de datos' research group and serves as Principal Investigator for multiple nationally and internationally funded projects, including the current 'Hacia una Inteligencia Artificial Probabilística Confiable (TOPAI-UAL)' project (2023-2026). His research expertise spans theoretical and applied aspects of probabilistic graphical models, with particular focus on Bayesian networks, causal inference, and their applications across diverse domains. His work demonstrates a consistent trajectory from foundational theoretical contributions to practical implementations in software engineering, genomics, sports analytics, and trustworthy autonomous systems. Professor Salmerón's publication portfolio reveals a strong emphasis on methodological innovations in probabilistic reasoning, with recent work exploring divide-and-conquer approaches for causal computation, noise-robust classification methods, and the integration of observational and randomized data sources. His research shows increasing interdisciplinary reach, connecting computer science methodologies with applications in plant genomics, software maintenance, and healthcare. Journal Publications: 105 articles in high-impact venues including Ecological Informatics (Q1), International Journal of Approximate Reasoning (Q2), and ACM Transactions Research Funding: Principal Investigator for 9 major projects since 2001 totaling over €800,000 in funding Thesis Supervision: Director of 7 doctoral theses on probabilistic graphical models and their applications Metrics: h-index 22 (Web of Science), i10 index 59 His research program demonstrates a unique combination of theoretical rigor in probabilistic reasoning with practical applications across diverse scientific domains, positioning him at the forefront of reliable probabilistic AI development.
