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Summary Raúl Suárez Feijóo is a Researcher at the Universitat Politècnica de Catalunya (UPC) in the Institut d'Organització i Control de Sistemes Industrials (IOC). Born in Asturias, Spain (1959), he holds an Electronic Engineering degree from the National University of San Juan, Argentina (1984), and a Doctorate in Engineering from UPC (1993). His research focuses on robotized assembly, fine motion planning, grasping, and multi-robot systems. He has led the IOC as Deputy Director (2003–2009) and Director (2009–2016). He coordinates doctoral programs in Automation and Robotics at UPC. Suárez has authored numerous publications and received awards including the Best Paper Award at IEEE ISATP (1995) and the Best Reviewer Award at ICRA (2015). Education: Electronic Engineer (1984, Argentina), Doctor Engineer (1993, UPC) Leadership Roles: Director of IOC (2009–2016), Coordinator of Doctoral Programs Research: Over 100 publications in robotics, emphasizing grasping, manipulation, and industrial automation. His work includes contributions to robotic hands, motion planning, and collaborative robotics. Notable projects involve 5G-enabled robotic systems and multi-AGV traffic management. Awards highlight his impact in both international and national robotics communities.

• Robotized Assembly
• Fine Motion Planning
• Robotized Grasping and Manipulation
• +4 more

Pedro Lima is an Associate Professor at the Lisbon Higher Technical Institute (IST) of the Technical University of Lisbon. He serves as the Portuguese National Delegate to the European Space Agency’s Programme Board for Human Spaceflight Microgravity and Exploration and is President/founding member of the Portuguese Robotics Society. His research focuses on intelligent control systems, discrete event dynamic systems theory, and planning under uncertainty for large-scale complex systems like multi-robot teams. He coordinates the Intelligent Systems group at the Institute for Systems and Robotics. During his research stay at UC3M (2010), he developed decision-theoretic approaches for human-robot interaction involving robot collectives.

• Intelligent Control Systems
• Discrete Event Dynamic Systems
• Robotics
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Juan Luis Zamora Macho is an Associate Professor in the Department of Electronics and Automation at the School of Engineering, Comillas Pontifical University. He is also a researcher at the Technological Research Institute (IIT), where he has been affiliated since 1991. His academic and research career is deeply rooted in electrical systems, with a focus on control, identification, and signal processing. His research interests include control systems , system identification , signal processing , power electronics , and renewable energy integration . He has made significant contributions to the development of control strategies for dynamic voltage restorers, unified power quality conditioners, and HVDC systems. His work bridges theoretical control design with practical applications in smart grids and industrial automation. The analysis of his recent publications (2018–2023) reveals a sustained focus on power quality improvement , harmonic suppression , and advanced control algorithms (e.g., resonant, repetitive, and multi-reference-frame controllers) applied to power electronics devices. Earlier works emphasize motor control and parameter estimation in induction machines, showcasing a long-term research trajectory in system modeling and real-time control. Director of the Connected Industry Chair Award for the best Final Degree Project 2022-23 Director of the 1st Prize, ICAI Industrial Innovation Association, for the best Final Year Project 2010-11 Juan Luis Zamora Macho has supervised multiple PhD students, including M. Ochoa and J. Roldán-Pérez, and currently advises J. García-Aguilar and D. Cubillo Llanes. He has led numerous research projects funded by public agencies (e.g., Ministry of Science, FEDER) and industry partners such as Siemens Gamesa, Gamesa, and Endesa. His project portfolio includes work on wind turbine integration, HVDC-VSC systems, and smart grid technologies. He has also delivered training courses and organized academic events, demonstrating strong engagement in knowledge transfer and academic leadership. He is actively involved in research teams and laboratories focused on power systems and control at IIT, contributing to both fundamental and applied research in electrical engineering. His collaboration network includes researchers from national and international institutions, reflected in joint publications and technical reports.

• Control Systems
• System Identification
• Signal Processing
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Álvaro Paricio García is an Assistant Professor at the Department of Automation within the School of Telematics Engineering at Universidad de Alcalá. He is affiliated with the NetIS Research Group (Networks and Intelligent Systems). His research focuses on smart city technologies, traffic engineering, optimization algorithms, and environmental engineering, with a particular emphasis on urban mobility, crowd evacuation systems, and emission reduction strategies. Education: He holds a PhD from Universidad de Alcalá, awarded in 2021 for his thesis Estrategias multi-mapa para el enrutamiento dinámico de tráfico urbano , supervised by Dr. Miguel Ángel López Carmona. Research Interests: His work integrates control systems, machine learning, and simulation-based optimization to address challenges in urban traffic management, crowd dynamics, and sustainable transportation. Key themes include: Design of low-emission zones for urban areas Development of adaptive evacuation systems using MPC (Model Predictive Control) Algorithmic innovations in traffic routing and multi-map strategies Article Trends: Recent publications (2021-2025) highlight his focus on: Wind farm layout optimization using metaheuristics Biometric identification via autoencoder-driven systems Dynamic low-emission zones and their policy implications Adaptive crowd evacuation systems like CellEVAC No scientific awards or grants were explicitly mentioned in the provided texts. He has not supervised any listed students. Labs/Teams: Active member of the NetIS Research Group, which develops networks and intelligent systems for urban and industrial applications.

• Smart City Technologies
• Traffic Engineering
• Optimization Algorithms
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Salvador Castillo Rivera is an Assistant Professor at the Department of Mathematics, Carlos III University of Madrid. His research integrates Game Theory, Artificial Intelligence, and Operations Research to address challenges in healthcare systems, additive manufacturing, and aeronautics. He holds a prominent position in interdisciplinary studies, focusing on optimization frameworks for ICU resource management, helicopter rotor dynamics, and 3D printing efficiency. Research interests span AI-driven healthcare decision-making, game-theoretic models for collaborative manufacturing, and mathematical modeling of mechanical systems. His work bridges theoretical mathematics with practical applications in aeronautics, medicine, and operations management. Key publications include frameworks for ICU cost optimization via game theory, dynamical analysis of helicopter tail rotors, and scheduling algorithms for additive manufacturing. His recent contributions emphasize the intersection of AI and healthcare, with chapters in Artificial Intelligence in Material Science and Advances in Health and Disease . No scientific awards are listed, but his active research collaborations are reflected through co-authored works and conference contributions. Advising and grants sections remain unspecified in the provided data. He manages interdisciplinary teams in applied mathematics and engineering projects, though specific lab affiliations are not detailed.

• Artificial Intelligence
• Game Theory
• Operations Research
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Iñaki Úcar is an Assistant Professor at the Department of Statistics, University Carlos III de Madrid, and a Research Fellow at the university's Big Data Institute. He directs the Master in Computational Social Science program and is an advocate for open-source software, particularly contributing to R packages like simmer , units , and quantities . His expertise spans statistical software, high-performance computing, simulation, data visualization, and network analysis. He holds an MEng in Telecommunications Engineering and an MScEng in Communications from Universidad Pública de Navarra (2011-2013), followed by an MScEng and PhD in Telematic Engineering from University Carlos III de Madrid (2014-2018). His research focuses on ML interpretability, computational social science applications (e.g., misinformation, inequality), and network dynamics. Recent work includes analyzing gender gaps in academic productivity during the pandemic and developing polynomial-based neural network frameworks. His articles highlight interdisciplinary contributions to R tooling, neural network theory, and socio-technical systems analysis. He actively organizes the Statistics Reading Club and NICDA workshops. Despite no listed formal advisees, his open-source contributions and collaborative projects reflect strong academic engagement.

• Machine Learning
• Computational Social Science
• High-Performance Computing
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Imma Gálvez Carrillo is a Lecturer at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mathematics and the Escola Superior d'Enginyeries Industrials, Aeroespacial i Audiovisual de Terrassa (ESEIAAT). She also collaborates with the Faculty of Mathematics and Statistics (FME) and the Barcelona Graduate School of Mathematics. Her research focuses on higher homotopy structures, operads, algebraic topology, category theory, and manifold invariants. She holds a PhD in Mathematics from the Universitat Autònoma de Barcelona (2001) and a Master's (1996) from the same institution, receiving the 1993 Graduation Award. Her work includes pioneering contributions to decomposition spaces, incidence algebras, and Möbius inversion. Recent research emphasizes categorical and simplicial methods in algebraic structures, with applications to quantum field theory and combinatorics. She has organized major events like the Barcelona Topology Workshop and led projects such as the Geometry of Manifolds and Applications (2014-SGR-634). Her articles span topics from A-infinity operads in cacti to Hopf algebras, reflecting a blend of pure and applied topology. Education: Ph.D. in Mathematics (UAB, 2001), Master's in Mathematics (UAB, 1996) Grants/Projects: MTM2013-42178-P Structured Homotopy, GTAB Algebraic Topology Group (2009-SGR-119) Awards: Graduation Award (1993, UAB) Advising: Co-supervised Leandro Lombardi's PhD (UBA, 2014), now a CONICET postdoc Labs/Teams: Active in Barcelona's algebraic topology community, including the CRM and IMUB

• Algebraic Topology
• Higher Homotopy Structures
• Operads
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Jose Julian Toledo Melero is a Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, Universitat de València. He is a leading researcher in nonlinear partial differential equations, with a focus on nonlocal diffusion, evolution equations, and optimal transport in metric random walk spaces. His work bridges pure and applied analysis, with strong collaborations with mathematicians such as José M. Mazón and Julio D. Rossi. His research interests include: Nonlinear Partial Differential Equations Nonlocal Diffusion and Operators Calculus of Variations and Optimal Transport Evolution Problems in Metric Spaces Geometric Analysis and Minimal Surfaces Doubly Nonlinear and Degenerate Equations The recent articles show a consistent focus on analytical and geometric properties of nonlocal models, particularly in discrete and metric random walk settings. His work frequently appears in top journals such as Calculus of Variations , SIAM Journal on Mathematical Analysis , and Journal of Evolution Equations , often in collaboration with leading experts. The publications reveal a deep engagement with both theoretical foundations and structural analysis of solutions. He has co-authored influential books such as Nonlocal Diffusion Problems (AMS, 2010) and Variational and Diffusion Problems in Random Walk Spaces (Birkhäuser, 2023), which are key references in the field. His research is highly cited, indicating significant impact in the mathematical community. He advises no publicly listed students in the provided data. There is no mention of specific grants or teaching roles, but his extensive publication record and book authorship reflect a sustained and high-level research career. He maintains an active research profile with upcoming events such as the 2025 CIMPA-UCA School on optimal transport and PDEs, suggesting ongoing leadership and contribution to the international mathematical community.

• Partial Differential Equations
• Nonlocal Diffusion
• Calculus of Variations
• +7 more

Pau Segovia Castillo is a Research Fellow in the Department of Automatic Control at Universitat Politècnica de Catalunya (UPC) since September 2023, holding the prestigious Beatriz Galindo Fellowship. His research focuses on large-scale systems management using non-centralized predictive control approaches, with applications in water resources, transportation, and energy systems. He holds a joint PhD in Automatic Control from UPC and IMT Lille Douai (France), completed in 2019. Previously, he held postdoctoral positions at IMT Lille Douai (2019–2020), TU Delft (2020–2023), and UPC (2023). His educational background includes a BS/MS in Industrial Engineering from UPC (2015). He is a member of the Advanced Control Systrems (SAC) group within the CS2AC research center. His work emphasizes model predictive control (MPC), observer design for nonlinear systems, and digital twin technologies applied to waterway infrastructure. Notable contributions include multilayer control strategies for canals and coordinated scheduling for inland vessel navigation. Key research areas span fault diagnosis in hydraulic systems, optimization algorithms for transportation logistics, and sustainable energy production from waterways. His publications address topics like MPC-based digital twins, observer schemes for noisy nonlinear systems, and lock scheduling using max-plus linear systems. He currently supervises Javier Pedrosa Alias's PhD on job-shop scheduling with AI approaches. Awards: Beatriz Galindo Fellowship Labs/Teams: Advanced Control Systrems (SAC) group, CS2AC Research Center

• Model Predictive Control
• Water Resources Systems
• Intelligent Transportation Systems
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Pau Segovia Castillo is a Beatriz Galindo Fellow in the Department of Automatic Control at Universitat Politècnica de Catalunya (UPC), where he conducts research in large-scale systems control. He is affiliated with the Advanced Control Systems (SAC) research group at the Research Center for Supervision, Safety and Automatic Control (CS2AC). Previously, he held postdoctoral positions at IMT Lille Douai (2019–2020), Delft University of Technology (2020–2023), and UPC (2023). BS/MS in Industrial Engineering, Universitat Politècnica de Catalunya (UPC), 2015 Joint PhD in Automatic Control, Robotics and Vision, UPC and IMT Lille Douai, France, 2019 His research focuses on non-centralized predictive control approaches for managing large-scale systems, with applications in water resources systems, intelligent transportation systems, and energy systems. He applies model predictive control, digital twin technologies, and switching control strategies to real-world infrastructure such as canals, irrigation networks, and inland waterways. His work emphasizes real-time optimization, robustness, and scalability in complex environments. The recent publications highlight a strong trend in model predictive control applied to waterway and transportation systems. Key themes include coordination of vessels and bridges, digital twin implementation, multilayer control architectures, and observer design for nonlinear systems. The research spans both theoretical advances in control theory and practical implementations using real databases and simulations. Scientific recognition includes: Beatriz Galindo Fellow He advises PhD students, including Javier Pedrosa Alias, and has been involved in collaborative research projects across institutions in Spain, France, and the Netherlands. His work is supported by his fellowship and integrated within the SAC research group, contributing to national and international efforts in smart infrastructure and automation. The research group CS2AC provides a multidisciplinary environment for supervision, safety, and automatic control applications. He is a member of the Advanced Control Systems (SAC) research group at CS2AC, which focuses on developing advanced control methodologies for safety-critical and large-scale systems. The team works on real-time monitoring, fault detection, and optimization of industrial and environmental processes.

• Automatic Control
• Model Predictive Control
• Large-Scale Systems
• +7 more

Sergio Mover is a Professor at the Department of Computer Science , Polytechnic Institute of Paris , affiliated with the Cosynus team and the LIX - Computer Science Laboratory . His research focuses on formal methods , particularly model checking using SMT for hybrid systems, embedded software, and program analysis. He has contributed to tools like HyCOMP , nuXmv , and SABBATH . Research interests include: Formal verification of infinite-state systems Symbolic model checking Hybrid system stability Callback protocol analysis Relational abstraction techniques In 2024, he published a book on abstraction techniques for symbolic model checking. His work has been featured at top conferences like CAV , FMCAD , and ICLR . Awards include the IEEE TCSE Distinguished Paper Award (2018) and Best Paper at FMCAD 2012 . He collaborates with researchers such as Alessandro Cimatti , Stefano Tonetta , and Bor-Yuh Evan Chang , focusing on hybrid systems, Android callback protocols, and SMT-based verification.

• Formal Methods
• Model Checking
• Satisfiability Modulo Theories (SMT)
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Pau Fonseca Casas is a Professor at the Universitat Politècnica de Catalunya (UPC) in the Department of Statistics and Operations Research, affiliated with the Barcelona Informatics School (FIB). His research focuses on simulation modeling, digital twins, optimization algorithms, and their applications in urban mobility, healthcare systems, and education. He leads the IMP (Information Modeling and Processing) research group and collaborates with the inLab FIB (part of the TECNIO Network and CIT UPC). He holds a doctorate from UPC and has over 242 scholarly activities including articles, projects, and awards. Notable contributions include pandemic modeling using digital twins, bike-sharing system optimization, and educational innovations leveraging computational thinking and Industry 4.0 principles. Fonseca Casas has received awards like the UPC's 14th Research Valorization Prize and has served on committees for major simulation conferences like Annual Modeling and Simulation Conference. His work spans interdisciplinary collaborations in sustainability, healthcare, and technology, with ongoing projects on wastewater surveillance networks and smart urban management. He actively publishes in journals like Sustainability , Logistics , and Advanced Theory and Simulations , emphasizing practical solutions for complex systems through rigorous validation processes.

• Simulation
• Modeling and Analysis
• Operations Research
• +4 more

Professor Pedro Diez is a faculty member at the Universitat Politècnica de Catalunya (UPC), specializing in computational mechanics and reduced-order modeling. He holds a BSc and PhD in Civil Engineering from UPC (1989 and 1996, respectively). His research focuses on error estimation, extended finite element methods (X-FEM), and applications in automotive and geophysical systems. He co-organizes the International Conference in Adaptive Modeling and Simulation since 2003, with the next edition in 2023. Key research areas include: Reduced Order Models (POD/PGD) Goal-oriented adaptivity in numerical simulations Geophysical inversion and thermal modeling Automotive structural dynamics and NVH analysis Sustainable materials for civil engineering His work bridges computational methods with real-world applications, such as earth dam monitoring, hydraulic fracturing modeling, and biomechanical simulations. Recent publications emphasize real-time risk analysis, parametric solutions for nonlinear systems, and inverse problem techniques in geophysics. His contributions to numerical methods have advanced high-fidelity, low-cost simulations across engineering disciplines. Publications span over 30 years, with a focus on: Efficient parametric solutions for transient coupled systems Nonintrusive reduced basis methods Thermo-hydro-mechanical modeling of geological media Advances in error estimation and model order reduction underpin much of his work, enabling applications in structural health monitoring, crashworthiness analysis, and geophysical exploration.

• Reduced Order Models
• Error Estimation and Adaptivity
• Extended Finite Element Methods (X-FEM)
• +4 more

Eva Barrena Algara is a Professor at the Department of Economics, Quantitative Methods, and Economic History at the University Pablo de Olavide. Her work bridges operations research, transportation planning, and mathematical optimization, with a focus on urban rail systems and network design. Her research interests include: Railway timetabling and scheduling under dynamic passenger demand Mixed-integer programming for transportation network optimization Multiplex network analysis in collective transportation systems Heuristic and metaheuristic algorithms for coordinated vehicle routing Waste logistics and humanitarian relief routing applications Her publications since 2013 demonstrate expertise in train unit scheduling, demand-adapted timetables, and network transferability analysis, often using Gröbner bases and adaptive algorithms. She collaborates with researchers like Gilbert Laporte and David Canca, with papers appearing in journals such as Computers & Operations Research and European Journal of Operational Research . Key application areas include metro systems, disaster response logistics, and waste collection optimization. She serves on the editorial board or as reviewer for transportation and operations research journals, and her work has been cited over 45 times. Her methodological contributions span exact formulations, biased-randomized heuristics, and stochastic modeling for time-dependent problems.

• Operations Research
• Mathematical Programming
• Transportation Planning
• +7 more

Joaquín Arias is an Associate Professor at the Universidad Rey Juan Carlos (URJC) in Madrid, Spain, since 2025. He previously served as an Assistant Professor at URJC (2020–2025) and as a Pre-Doctoral Researcher at the IMDEA Software Institute (2013–2020). He holds a Ph.D. in Computer Science (2020), a Master of Science in Computer Science (2015), a Bachelor of Science in Computer Science (2014), and a Master of Architecture (2002), all from the Universidad Politécnica de Madrid (UPM). His research focuses on constraint logic programming, answer set programming (ASP), and their applications in stream data analysis, spatial reasoning, and legal reasoning systems. His main research interests include (Constraint) Logic Programming, TCLP, s(CASP), and value-aware systems. He has developed frameworks like Modular TCLP and ATCLP for constraint integration and aggregate computation. Notable projects include applying s(CASP) to legal reasoning (s(LAW)), BIM modeling, and automated conversational agents using LLMs and ASP. His work emphasizes explainable AI and ethical alignment in automated decision-making. Key contributions include the Automated Legal Reasoning with Discretion framework (2024), a socialbot leveraging LLMs and ASP (2024), and a legal reasoning system for administrative processes (2024). He has contributed to proceedings of the ICLP workshops and edited volumes for conferences like AAAI and CAEPIA. His academic awards include the Best Paper Prize at CAEPIA 2021. Collaborations include the University of Texas at Dallas (2017), Aalto University (2019), and IMDEA Software Institute. His teaching includes promoting logic programming in computer science curricula, as highlighted in his 2023 SIIE conference paper.

• Constraint Logic Programming
• Answer Set Programming (ASP)
• Stream Data Analysis
• +3 more