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Miguel Ángel Sotelo Vázquez is a full Professor at the University of Alcalá, leading the INVETT Research Group (Intelligent Vehicles and Traffic Technologies). He holds the Department of Automatic Control and specializes in autonomous systems, particularly in path planning, sensor fusion, and human-vehicle interaction. His research integrates machine learning, robotics, and control theory to address challenges in intelligent transportation systems. He earned his Ph.D. in 2001 with a thesis on autonomous vehicle navigation in partially known environments. His work emphasizes real-world deployment, explainable AI, and safety-critical systems. Recent projects focus on lane change prediction, pedestrian behavior modeling, and cybersecurity for autonomous systems. Key contributions include neuro-symbolic frameworks for decision-making, real-time multi-physics field reconstruction, and cross-cultural studies of pedestrian interactions. He collaborates internationally on urban mobility resilience and hydrogen refueling infrastructure. Research Highlights : Development of knowledge graph-based prediction architectures Experimental validation of human-vehicle interaction in VR environments Creation of the SCOUT trajectory prediction framework

• Autonomous Vehicles
• Intelligent Transportation Systems
• Robotics
• +7 more

Dr. Anna Maria Mandalari is an Assistant Professor at University College London (UCL), affiliated with the Electronic and Electrical Engineering Department. She serves as Director of the SafeNetIoT laboratory and the Internet Engineering/Telecommunications MSc/MRes Programme at UCL. She holds an Honorary Research Fellow position at the Institute for Security Science and Technology at Imperial College London. Her research focuses on IoT security, privacy engineering, and network measurement techniques, particularly analyzing information exposure from consumer devices and developing adaptive network security strategies. Her work has led to significant contributions such as the IMC'19 Community Contribution Award-winning study on multidimensional IoT device exposure and the Telekom Challenge-winning IoTrim prototype for blocking non-essential IoT traffic. She has secured funding through InnovateUK’s CyberASAP program and participated in high-impact projects like NATwatcher and the European roaming analysis initiative. Key Awards: Community Contribution Award (IMC'19), Best Paper Award (C2B(I)D 2015) Grants: InnovateUK CyberASAP Phase 2 funding, Telekom Challenge Development Stream Top 5 prize Labs/Teams: Director of SafeNetIoT Lab, Leading M2M and IoT security teams at UCL Her recent work addresses IoT device misactivation risks (e.g., smart speakers), scalable detection of IoT devices in the wild, and protocol design informed by crowdsourced data. She actively collaborates with industry partners like Telekom and academic institutions on network infrastructure security and performance optimization.

• IoT Security
• Network Measurement
• Privacy Engineering
• +3 more

Angel Santamaria-Navarro serves as Associate Professor at Polytechnic University of Catalonia (UPC) and Robotics Researcher at the Institute of Robotics and Industrial Informatics (IRI), a CSIC-UPC joint center in Barcelona. His work bridges academic research and real-world deployment in mobile robotics, with current leadership in European TRIFFID (autonomous first-responder systems) and national LENA (lifelong navigation learning) projects spanning urban logistics and emergency response applications. His research centers on Mobile Robotics and Autonomous Systems with emphasis on human-robot collaboration in unstructured environments . Key focus areas include robot navigation in crowded urban settings, manipulation of deformable objects, and deployment of delivery systems like the LogiSmile project piloted across European cities. His work uniquely integrates machine learning with field robotics to solve practical challenges in last-mile logistics and disaster response. Recent publications (2022-2025) reveal a concentrated shift toward real-world robotic deployment , particularly in emergency response (TRIFFID) and urban logistics. Dominant themes include communication-aware multi-robot coordination, probabilistic perception for dynamic environments, and human acceptance studies – reflecting his commitment to transitioning lab innovations to operational field systems through Horizon Europe and national projects. Key recognitions include: 1st place at DARPA Subterranean Challenge, urban circuit (2020) 2nd place at DARPA Subterranean Challenge, tunnel circuit (2019) Beatriu de Pinós research fellowship (2021) Georges Giralt PhD award finalist (2018) R3 accreditation as consolidated researcher (2023) He actively mentors next-generation researchers as supervisor of PhD candidate Hafsa Taher (deep learning for autonomous vehicles) and Master's student Joan Tur Ruiz (object pose tracking). His research portfolio includes €5M+ in competitive funding spanning Horizon Europe projects (TRIFFID, TORNADO), national initiatives (LENA, AUDEL), and industry partnerships like the Vaive Logistics spin-off co-founded in 2023. As core member of UPC's robotics team, he contributed to the NeBula framework that won DARPA's Subterranean Challenge and currently leads development of TRIFFID's autonomous first-responder systems. His work with the LogiSmile consortium demonstrates practical urban deployment of delivery robots across Barcelona, Lisbon, and Milan, while the SOCIAL PIA project pioneers cybernetic avatars for cooperative human-robot teams.

• Mobile Robotics
• Autonomous Systems
• Human-Robot Interaction
• +3 more

Carlos A. Ocampo Martínez is an Associate Professor in the Department of Automatic Control (ESAII) at the Universitat Politècnica de Catalunya (UPC), BarcelonaTech, Spain. He is affiliated with the Institut de Robòtica i Informàtica Industrial, CSIC-UPC, a joint research center between UPC and the Spanish National Research Council. He has been with UPC since 2011 and served as Deputy Director of IRI from 2014 to 2018. Education: PhD in Control Engineering, Universitat Politècnica de Catalunya, 2007 MSc in Industrial Automation, National University of Colombia, 2003 BSc in Electronics Engineering, National University of Colombia, 2001 His research is centered on model predictive control (MPC) , particularly constrained and distributed MPC, with applications in energy, water, and smart manufacturing. He investigates large-scale systems management, partitioning strategies, and non-centralized control architectures. His work integrates IoT frameworks for smart industrial systems. Key domains include renewable hydrogen production, fuel cell vehicles, microalgae bioreactors, and solar thermal plants. The recent publications reflect a strong trend in applying control theory to sustainable energy systems and environmental management. There is a clear focus on integrating game theory, population dynamics, and optimization into MPC frameworks for distributed and coalitional control. Applications span hydrogen infrastructure, solar energy, water irrigation, and transportation electrification, demonstrating interdisciplinary impact. Scientific Awards: Juan de la Cierva Research Fellow Dr. Ocampo-Martínez actively supervises PhD students and leads research projects such as MASHED , which focuses on digitalized energy systems with hybrid storage. He has advised students on topics including alkaline electrolyzers, hydrogen production control, and alcohol steam reformers. His grant involvement emphasizes renewable integration, smart grids, and sustainable transport. He collaborates with researchers across Europe and contributes to high-impact journals and IFAC conferences. He is a key member of the Automatic Control research group at ESAII and contributes to the strategic direction of the Institut de Robòtica i Informàtica Industrial. His team integrates control theory, optimization, and real-world industrial applications, particularly in energy and water systems.

• Control Engineering
• Model Predictive Control
• Constrained Control Systems
• +12 more

Mohammad Rajabdorri is an Assistant Professor at the Institute for Research in Technology (IIT) of Comillas Pontifical University, holding a position since 2020 and currently serving as an Assistant Research Collaborator since 2024. He earned a BSc in Electrical Power Engineering from Shiraz University (2016), an MSc in Electrical Power Systems from Shiraz University of Technology (2018), and a PhD in Electrical Engineering from IIT (2023). His research focuses on isolated power systems, electricity markets, renewable energy dispatch, and power system operation. Key projects include modeling grid-forming converters for system stability, blackstart strategies for renewable plants, and UFLS optimization in island systems. He has collaborated with entities like Iberdrola and the European Commission. Rajabdorri’s work spans 9 journal articles and 8 conference papers, emphasizing data-driven approaches in power system optimization. He advises PhD student M. Sarvarizadeh Kouhpaye on resilience and reliability of island systems. His professional networks include international exchanges at Durham University and invited seminars at IIT.

• Electric Power Systems
• Renewable Energy Dispatch
• Isolated Power Systems
• +3 more

Enrique Lobato Miguélez is a Full Professor at the Higher Technical School of Engineering (ICAI) of Comillas Pontifical University in Madrid, Spain, where he has been a faculty member since June 1, 1998. His research is conducted at the Technological Research Institute (IIT), focusing on electrical power systems, with a strong emphasis on renewable integration, energy storage, and island grid stability. His research interests include the analysis, planning, operation, and economics of electrical systems, with specific expertise in frequency-power control, voltage control, electricity markets, and the sustainability of insular systems. He has made significant contributions to the integration of renewable energy sources and the application of storage elements in power systems. The recent publications highlight a consistent focus on optimization, control, and integration challenges in modern power systems, particularly in islanded and renewable-rich environments. Key themes include unit commitment with frequency constraints, robust design of under-frequency load shedding, battery energy storage in wind farms, and data-driven modeling for stability enhancement. His work often combines theoretical modeling with practical applications for industry partners like Red Eléctrica de España, Naturgy, and Endesa. Scientific Awards: Eolo annual Innovation Award in May 2016 awarded by the Wind Energy Business Association AEE Distinción Honorífica a la mejor Tesis Doctoral en Ingeniería «Voltage control design of wind energy harvesting networks» por Elena Sáiz Professor Lobato has supervised several PhD students, including M. Rajabdorri, I. Saboya, and E. Saiz. He has led numerous research and consulting projects funded by the European Commission, Spanish government agencies, and private companies such as Iberdrola, Endesa, and Viesgo, covering topics like grid integration of renewables, energy storage, and market design. He has also organized major scientific events such as the ICREPQ conferences and conducted training courses for industry professionals. He has conducted research stays at Sophia University in Tokyo and University College Dublin, and his work has resulted in a book on island power systems and over 60 journal publications.

• Electrical Power Systems
• Analysis, Planning, Operation and Economics of Electrical Systems
• Renewable Energy Integration
• +12 more

Rafael Vazquez Valenzuela is a University Professor in the Department of Aerospace Engineering and Fluid Mechanics at the Higher Technical School of Engineering, University of Seville. His research focuses on control systems for aerospace applications, particularly in spacecraft dynamics, orbital mechanics, and partial differential equation (PDE) control systems. Professor Vazquez Valenzuela's research spans several key areas in aerospace engineering and control theory. His primary interests include spacecraft guidance and navigation, particularly for asteroid exploration and rendezvous operations. He has made significant contributions to the field of backstepping control for PDE systems, with applications ranging from fluid dynamics to spacecraft control. His work also extends to stochastic analysis of aircraft performance, thermoacoustic instability control, and the development of advanced algorithms for unmanned aerial vehicles. Notably, his research bridges theoretical control theory with practical aerospace applications, resulting in numerous high-impact publications in top journals. His publication record shows a clear trend toward increasingly sophisticated control algorithms for complex aerospace systems. Recent work focuses on predictive control for spacecraft operations near asteroids, chance-constrained optimization for halo orbit rendezvous, and prescribed-time control methods. His research consistently addresses the challenging intersection of theoretical control design and practical implementation constraints in aerospace applications. Professor Vazquez Valenzuela has been involved in numerous research projects, including "APPLICATION OF LEADING TECHNOLOGY TO UNMANNED AERIAL VEHICLES FOR RESEARCH AND DEVELOPMENT IN ATM (ATLANTIDA)" "Diseño de Algoritmos de Guiado y Control Innovadores para Aplicaciones Avanzadas de Rendezvous: Órbitas Halo y Exploración de Asteroides" "SESAR WP-E ComplexWorld Network" These projects highlight his expertise in both theoretical control systems and practical aerospace applications. He is affiliated with the INGENIERÍA AEROESPACIAL (GIA) research group at the University of Seville, where he collaborates with researchers on advanced control and navigation systems for autonomous aerospace vehicles.

• Aerospace Engineering
• Spacecraft Dynamics
• Orbital Mechanics
• +5 more

Iñaki Vazquez Gomez is a Lecturer and Researcher at the University of Deusto , affiliated with the College of Engineering and Department of Computing, Electronics and Communication Technologies . He holds a PhD in Computer Science and Artificial Intelligence (University of Deusto and Lancaster University) and served as Director of Deusto Institute of Technology (2020-2023). His research focuses on Reinforcement Learning , Internet of Things , and Cognitive Robotics , with applications in human-robot interaction and ambient intelligence. Member of European Internet of Things Council Founder of technology startups Editorial board member of International Journal of Ambient Computing and Intelligence His 15 most recent publications (2005-2024) span themes of Autonomous Systems , Context-Aware Computing , and Smart Environments , with subtopics including semantic device communication, adaptive positioning algorithms, and collaborative robotics architectures. 2024: Adaptive Robot Behavior via Reinforcement Learning 2021: Gesture Recognition for Resource-Constrained Devices 2015: Context-Aware Service Matching in AAL Scientific honors include: X Premio UD-Banco Santander de Investigación (2015) Sexenio de Investigación (2018-2025) Profesor Doctor de Universidad Privada (2009-2025) He supervised PhD students like Asier Gonzalez Santocildes and Ignacio Fidalgo Astorquia, while leading grants such as AI-Driven Cognitive Robotics (2021-2024) and Quantum Technologies (2021-2022). His work includes developing middleware for smart spaces and founding the Sentient Things project for self-adapting environmental systems.

• Reinforcement Learning
• Internet of Things (IoT)
• Cognitive Robotics
• +4 more

Gleb Pogudin is an Assistant Professor at École Polytechnique, Institute Polytechnique de Paris, where he is a member of the MAX team within the Laboratoire d'informatique. His research focuses on the intersection of symbolic computation, differential equations, and algebraic methods with applications across multiple scientific domains. Dr. Pogudin's primary research interests span several interconnected areas: Symbolic computation and computer algebra algorithms Theory and applications of differential and difference equations Nonlinear algebra and polynomial systems Structural identifiability of dynamical models Model reduction techniques for complex systems His recent publications (2024-2025) demonstrate a strong focus on developing theoretical foundations for differential elimination, structural identifiability analysis, and model reduction. These works span applications in systems biology, epidemiology, pharmacology, and optics. Notably, his research bridges pure mathematical theory with practical computational implementations, creating tools that address real-world scientific challenges. Dr. Pogudin has developed several significant software tools that implement his theoretical advances: StructuralIdentifiability.jl: A Julia package for assessing structural identifiability CLUE: Software for exact model reduction of ODE models via constrained lumping SIAN: Software for structural identifiability analysis of ODE models His GitHub repositories contain numerous implementations of algorithms from his papers on differential elimination and related topics, demonstrating his commitment to making theoretical advances practically accessible to researchers across disciplines.

• Symbolic computation
• Algorithms for differential equations
• Algorithms for difference equations
• +5 more

Dr. Francisco Javier Renedo Anglada is a Guest Researcher at the Instituto de Investigación Tecnológica (IIT), affiliated with the Higher Technical School of Engineering (ICAI) at Comillas Pontifical University, Spain. He has been actively involved in research at IIT since 2012, with a formal position since 2021. His work is centered on electrical systems, particularly in the domain of power system stability and HVDC technologies. Industrial Engineer (Electrical), ICAI - Comillas Pontifical University (2010) Master in Mathematical Engineering, Carlos III University of Madrid (2013) PhD in Engineering Systems Modeling, ICAI - Comillas Pontifical University (2018) His research interests focus on the stability and control of modern power systems. Key areas include multi-terminal VSC-HVDC systems , power system stability (especially transient and small-signal), power electronics applications in grids, and challenges in systems with high renewable energy content and low inertia. He has developed simulation tools and control strategies to enhance grid resilience. The analysis of his recent publications reveals a strong trend toward solving stability issues in hybrid AC/DC grids, particularly using DC segmentation, fast voltage boosters, and coordinated control of VSC-HVDC systems. His work addresses critical challenges like intra-area oscillations, transient stability in 100% inverter-based systems, and frequency support in low-inertia grids, reflecting a consistent focus on enabling high renewable integration. His scientific achievements include: Honorary Distinction for the best Doctoral Thesis in Engineering, Comillas Pontifical University (2019) Dr. Renedo has supervised PhD students and contributed to numerous national and international research projects funded by the European Commission (Horizon 2020), Spanish Ministry of Science, IRENA, IADB, and industry partners like Iberdrola and Endesa. He serves as a reviewer for IEEE Transactions on Power Systems and is an active member of IEEE and CIGRE Working Group C4B4.52, contributing to guidelines on sub-synchronous oscillations in power electronics-dominated systems. He has been involved in several research laboratories and teams, primarily within the IIT’s Electrical Systems area, focusing on modeling, control, and simulation of hybrid power systems. His work often involves collaboration with international universities and industry stakeholders.

• Power System Stability
• Multi-terminal VSC-HVDC Systems
• Power Electronics in Power Grids
• +7 more

Antonio de la Oliva is a Professor at the University Carlos III de Madrid, affiliated with the School of Engineering. His primary research focuses on advanced networking technologies, including 5G/6G, Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and mobile edge computing. He leads and contributes to major EU-funded projects such as 5G-CORAL, 5G-Transformer, and 5G-Crosshaul, which aim to integrate and optimize transport networks for industry verticals. He has supervised PhD students like Maria Isabel Sanchez Bueno (awarded UC3M's Special PhD Award) and Sergio Gonzalez Diaz. His work spans experimental evaluations of SDN-based service provisioning, network slicing, and deterministic communications for Industry 4.0. He actively engages in standardization efforts (e.g., IEEE 802.21, IETF) and collaborates with industry partners like Ericsson, Nokia, and Telecom Italia. His research also explores edge robotics, digital twins, and AI integration in networked systems. Key projects include developing the 5G-Crosshaul architecture for integrated fronthaul/backhaul networks and the SLICES-Madrid multi-domain TSN framework. He emphasizes practical applications in healthcare, emergency response, and industrial automation, leveraging edge-fog-cloud architectures.

• 5G Networks
• Software-Defined Networking (SDN)
• Network Functions Virtualization (NFV)
• +4 more

Florio Maria Ciaglia is a researcher in the Department of Mathematics at Carlos III University of Madrid (UC3M), affiliated with the Applied Mathematics, Control Systems, and Signals research group. His work lies at the intersection of mathematical physics, quantum mechanics, and information geometry, with a focus on geometric and algebraic structures in quantum theory. His research interests include quantum mechanics (particularly Schwinger's picture) , information geometry , groupoids and higher categorical structures , Jordan and C*-algebras , and geometric methods in quantum information . He investigates the differential geometric foundations of quantum and classical states, monotone metrics, parametric estimation, and the role of symmetry and causality in quantum dynamics. His work often bridges abstract mathematics with foundational physical concepts. The trends in his recent publications reveal a deep and consistent exploration of geometric formulations of quantum mechanics , especially through groupoids and algebraic structures, alongside information-theoretic approaches in quantum theory . He frequently publishes in journals such as Journal of Geometry and Physics , Entropy , and International Journal of Geometric Methods in Modern Physics , reflecting a strong emphasis on mathematical rigor and physical interpretation. He has led significant research projects including: QUITEMAD-CM - QUITEMAD (2025–2028), funded by Comunidad de Madrid Classical and Quantum Information Theory and Functional Analysis: Foundations and applications (2021–2024), funded by CAM Groupoids, Von Neumann Algebras and the Mathematical Foundations of Quantum Mechanics (2021–2025), funded by AEI These projects underscore his leadership in advancing the mathematical foundations of quantum information and quantum mechanics. He collaborates within interdisciplinary teams focusing on applied mathematics and quantum systems. While no formal students or awards are listed in the provided text, his extensive publication record and principal investigator roles indicate a significant research impact.

• Mathematical Physics
• Quantum Mechanics
• Information Geometry
• +17 more

Vanesa Guerrero Lozano is an Associate Professor in the Department of Statistics at Universidad Carlos III de Madrid, affiliated with the Flores de Lemus Institute and the UC3M-Santander Big Data Institute. Her work bridges mathematical optimization, statistical modeling, and data science, with applications across disciplines including biomedicine, fluid mechanics, and sustainable development. Her research focuses on developing advanced statistical methodologies using mathematical optimization. Key interests include shape-constrained regression, P-splines smoothing, sparse modeling, clustering of categorical data, and interpretable machine learning. She applies these techniques to complex datasets in turbulence modeling, biological age imputation, and pandemic forecasting. The recent publications reveal a strong trend in integrating optimization techniques with statistical learning, particularly in nonparametric and semiparametric models. There is a consistent emphasis on interpretability, robustness, and scalability, especially for high-dimensional and dynamic datasets. Applications span from fluid dynamics to public health, demonstrating interdisciplinary impact. Scientific Awards and Recognition: Ayuda adicional within the Juan de la Cierva Incorporación Program (2020), awarded by the State Research Agency (AEI) Research Leadership and Advising: She has served as principal investigator on multiple competitive research projects funded by national and regional agencies, including the State Research Agency (AEI), the Jacques Hadamard Mathematical Foundation, and the Community of Madrid. Her projects cover topics such as constrained additive models, machine learning for sustainable fishing, turbulence control, and ADHD diagnosis using data science. She has supervised at least one doctoral thesis on constrained smoothing models, indicating active mentorship in methodological statistics and optimization. Laboratories and Research Groups: She is a member of the Energy Analytics research group and conducts her work within the UC3M-Santander Big Data Institute, which supports interdisciplinary data science research. Her affiliation with the Flores de Lemus Institute further underscores her engagement with advanced statistical and computational methodologies.

• Mathematical Optimization
• Statistical Modeling
• Machine Learning
• +13 more

Dr. Diego Casado Mansilla is a Researcher at the MORElab group within the Department of Computing, Electronics and Communication Technologies at the College of Engineering, University of Deusto. His work bridges Sustainable Human-Computer Interaction (HCI), Persuasive Technologies, and Internet of Things (IoT) systems to drive behavior change in energy consumption, urban sustainability, and STEM education accessibility. Education: PhD in Persuasive Technologies for Sustainability and Behavior Change (2016), University of Deusto His research spans two decades, focusing on Sustainable Design , Physical Interaction with Everyday Objects , and Human-Centric IoT Systems . He has led projects like Suggestive Autonomy (2016) and co-led GreenSoul (2017, 2019), which employ IoT for energy awareness in public buildings. Current projects include AmIAire (air quality monitoring) and Urban Adaptation and Alert Solutions (climate resilience, 2024-2028). Key trends in his 20+ publications (2012-2025) include: Energy efficiency in tertiary buildings and smart cities IoT protocols (CoAP, IEC 61850) for industrial and urban systems Behavioral economics and nudging for sustainable decisions Rural STEM education via remote experiments Privacy-preserving smart workplace systems Climate change perception studies across generations His supervised theses and projects address User Diversity , Edge Computing , and Industry 4.0 Adoption . He collaborates with European institutions on grants from the Ministry of Science and Innovation and European Commission , contributing to citizen science initiatives like SOCIO-BEE and educational tools such as EngageMate and Computario .

• Sustainable HCI
• Persuasive Technologies
• Behavior Change Technologies
• +3 more

David Poza García is an Associate Professor at the University of Valladolid’s Department of Business Organisation and Market Research. He holds affiliations with INSISOC (GIR UVa, GREX251, UIC086) and professional organizations including ESSA, ADINGOR, and AEIPRO. His certifications include IPMA-D Project Management accreditation. Research focuses on optimization in industrial systems, spanning additive manufacturing, project scheduling, combinatorial auctions, and risk modeling. Key themes include algorithmic efficiency, stochastic analysis, and sustainable operations. Publications emphasize computational methods for industrial challenges, with recent trends in simulation-based scheduling, additive manufacturing economics, and uncertainty management in project frameworks. No advising roles, grants, or lab affiliations are detailed in available texts.

• Additive Manufacturing
• Project Management
• Combinatorial Auctions
• +1 more