جستجوی استاد راهنمای دانشگاهی

Cedric Martinez Campos is an Assistant Professor in the Department of Mathematics at the Faculty of Mathematics, University of Valencia. He is a member of the Geometric Analysis Group U.V. (GAGUV) and specializes in Geometry and Topology. His academic work is deeply rooted in geometric mechanics and mathematical physics. Research Interests: Geometric methods in classical and field theories Differential geometry and topology Variational calculus and optimal control Geometric numerical integration (variational integrators) Hamilton-Jacobi theory Constrained and dissipative systems His recent publications reveal a strong focus on applying advanced geometric structures—such as contact, multisymplectic, and k-contact geometries—to formulate and analyze mechanical and field theories, especially those involving dissipation and constraints. He develops high-order numerical methods grounded in variational principles, contributing to both theoretical and computational mechanics. Scientific Contributions: Over 16 publications in major mathematical physics journals Significant work on higher-order field theories and Lagrangian submanifolds Development of geometric integrators for optimal control Contributions to the Hamilton-Jacobi formalism in field theory He has collaborated extensively with leading figures such as Manuel de León, David Martín de Diego, and J. M. Sanz-Serna. His research has been cited over 90 times, reflecting its relevance in geometric mechanics. He advises no listed students yet but is actively involved in high-level research. He is part of ongoing efforts to extend geometric frameworks to non-conservative and singular systems, indicating a forward-looking research agenda in mathematical physics.

• Geometry and Topology
• Geometric Analysis
• Differential Geometry
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Jon Legarda Macon serves as a Lecturer and researcher at the University of Deusto's Faculty of Engineering within the Department of Computing, Electronics and Communication Technologies. Holding a PhD in Engineering from the University of Navarra (2004), he leads research initiatives focused on industrial communication technologies and sustainable systems. His research spans communication technologies, electronics, and IoT systems with specialization in energy harvesting, data spaces, and environmental impact reduction. Current work emphasizes data spaces applied to improving environmental and social impacts across industrial, energy, and governance environments, with significant contributions to textile antennas, RF energy harvesting, and sustainable supply chain solutions. His publication portfolio shows strong emphasis on wireless communication systems (35%), energy harvesting technologies (25%), and sustainable applications (20%), with recent work pivoting toward blockchain applications in energy markets and computational intelligence for agrifood systems. Dr. Legarda has supervised 10 doctoral theses across topics including textile rectennas, energy harvesting optimization, and wireless sensor networks. His research is supported by numerous competitive grants including EU Horizon projects (PARITY, FOODRUS), Spanish national programs, and regional Basque initiatives totaling over €15 million in funding since 2012. He actively contributes to the Deusto Sustainable Research Group and leads multiple industrial collaborations through projects like URETIK (energy-efficient greenhouse platforms) and SIONIA (real-time bird identification systems), focusing on practical implementations of sustainable IoT solutions.

• Communication Technologies
• Electronics
• Internet of Things (IoT)
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Julián Viejo Cortés is an Associate Professor at the University of Seville, affiliated with the Department of Electronic Technology in the School of Computer Engineering. His professional focus revolves around hardware design, embedded systems, and microelectronics, with notable contributions to secure IoT devices, FPGA-based systems, and time synchronization protocols. He has led or participated in multiple research projects such as USECHIP: Chair in Microelectronics and NanoFS: a hardware-oriented file system . Research Interests: - IoT Security and Embedded Systems - FPGA and Hardware Design Methodologies - Time Synchronization Protocols - Low-Power CMOS Circuit Design - Membrane Computing and Formal Systems - System-on-Chip (SoC) Integration His publications emphasize practical hardware solutions, including secure boot mechanisms ( IRIS ), efficient time server cores, and energy-efficient CMOS gate designs. He has directed doctoral research, such as Juan Quirós Carmona's thesis on membrane computing hardware implementations. Grants & Projects: USECHIP: Chair in Microelectronics (TSI-069100-2023-001) Advanced Initiation Systems for IoT (TIN2017-89951-P) Incentive Grants for TIC-204 Research Group (2017–2010) Labs/Teams: Active contributor to the Digital Research and Development group, focusing on innovative embedded systems and FPGA applications.

• Computer Engineering
• Microelectronics
• Embedded Systems
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Ana Baringo Morales is an Assistant Professor at the Institute for Research in Technology (IIT) of Comillas Pontifical University since July 2022. She holds a PhD in Electrical Engineering (cum laude, 2020) and an M.S. in Industrial Engineering from the University of Castilla-La Mancha. Her postdoctoral research included a 3-month fellowship at the Technical University of Denmark (DTU). Research Focus: Her work centers on electricity markets, uncertainty modeling, virtual power plants, optimization models, and automatic generation control. Key contributions include stochastic adaptive robust optimization frameworks for power system operation and planning. PhD Thesis: Operation and expansion strategies for virtual power plants participating in electricity markets Projects: Collaborations with Endesa, Red Eléctrica de España, and Repsol on secondary regulation markets and grid stability Recent Work: Her 2025 article in Energy proposes novel bidding strategies for renewable-only virtual power plants in secondary reserve markets. Earlier works address robust investment planning and holistic system design under uncertainty. Dissemination: Delivered seminars on Spanish secondary regulation pricing (2024) and frequency restoration reserve mechanisms (2023). Featured in media including Casting the Future (Feb 2024).

• Electricity markets
• Uncertainty modeling
• Virtual power plants
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Lukas Sigrist is an Associate Professor at the Instituto de Investigación Tecnológica (IIT) of Universidad Pontificia Comillas, serving as Deputy Director of Economic Affairs. He holds an M.Sc. in Electrical Engineering from EPFL (2007) and a Ph.D. from Universidad Pontificia Comillas (2010). His research focuses on modeling, analysis, and control of electric power systems, with specialization in island power systems and renewable integration. His research interests center on: Power system stability and operation under high renewable penetration Design of under-frequency load shedding (UFLS) schemes Virtual power plants and renewable integration strategies Energy storage applications for grid stability Frequency control in low-inertia systems Recent publications demonstrate strong focus on renewable integration challenges in island grids, with themes including frequency-constrained unit commitment, virtual power plant optimization, and stability enhancement using power electronics. His work frequently combines computational methods with power system fundamentals. Awards: 12th European Talent Award for Innovative Energy Systems (for UFLS scheme design) Research Leadership: Actively supervises doctoral candidates working on island system operation, virtual power plants, and grid-forming converters. Contributes to major EU projects like POSYTYF and HVDC-Wise focused on future power systems. Professional Service: Serves as Treasurer of Spanish IEEE PES Chapter and previously as Associate Editor for IET Generation, Transmission & Distribution. Organizes international conferences including IEEE PowerTech.

• Electric Power Systems
• Energy Systems Modeling
• Power System Stability
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Cristina Losada Gutiérrez is a Professor at the Department of Electronics, Universidad de Alcalá, Spain. She leads research in the GEINTRA group, focusing on Electronic Engineering applied to Intelligent Spaces and Transport. Her work integrates computer vision, robotics, and deep learning for applications in smart surveillance, human activity analysis, and assistive technologies. She earned a PhD in 2010 with a thesis on 3D robot localization using static camera networks. Her research spans real-time action recognition, anomaly detection, and sensor fusion for healthcare and transportation systems. Notable projects include the GEMS Erasmus+ initiative (Ruby sensory module) and EU-funded EYEFUL systems for functional evaluation. Her recent publications emphasize edge computing frameworks for video analysis, weakly-supervised learning models, and robust object detection in dynamic environments. She actively contributes to educational robotics projects like Eurobot Spain and explores portable architectures for intelligent wheelchairs. Her lab develops multisensory systems for applications such as crowd safety (stampede detection) and railway obstacle detection, leveraging time-of-flight cameras and deep learning pipelines. She collaborates internationally on projects blending academic research with industrial and societal challenges.

• Computer Vision
• Robotics
• Deep Learning
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Francisco Javier Cuadrado Aranda is a faculty member in the Department of Naval and Industrial Engineering at the Ferrol Engineering Polytechnic School, University of A Coruña (UDC), Spain. His academic work spans teaching, research, and industrial collaboration, with a focus on mechanical engineering, multibody dynamics, and biomechanics. His research interests include: Multibody System Dynamics Computational Kinematics and Dynamics Biomechanics of Human Motion Gait Analysis and Orthosis Design Machine and Maintenance Engineering Simulation and Numerical Integration His recent publications (2021–2025) reflect a strong trend in applying multibody dynamics to biomechanics and robotics, particularly in human gait simulation, exoskeletons, assistive devices, and industrial applications. The research combines modeling, optimization, real-time simulation, and sensor integration, often with industrial or medical applications in automotive, maritime, and rehabilitation sectors. He has secured significant research funding from national (MINECO, Xunta de Galicia), European (EU), and industrial sources (GKN Driveline, NAVANTIA, Pixee Medical), and has directed multiple final-year and master’s theses. He is also involved in patents and software development through collaborations with Tecnalia and spin-offs like ABLE Human Motion. He leads the Laboratorio de Ingeniería Mecánica, where he supervises student projects and conducts applied research. His teaching includes Machine Design, Maintenance Engineering, Theory of Machines, and Biomechanics across Mechanical, Industrial, and Podiatry programs.

• Multibody System Dynamics
• Computational Kinematics
• Biomechanics of Human Motion
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Ros Giralt, Lluis is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mechanical Engineering and the CRG - Grup de Robòtica Computacional . His primary roles include academic research and teaching in robotics, with a focus on computational kinematics, dynamic motion planning, and singularity analysis in robotic systems. He holds a Doctorate in Industrial Engineering from UPC. Research Interests: His work centers on advanced robotics topics such as trajectory optimization for constrained systems, singularity-aware control, and motion planning for parallel and closed-chain robots. Key contributions include collocation methods for trajectory optimization and algorithms for singularity avoidance in complex mechanisms. Recent Research Trends: Recent publications emphasize trajectory optimization techniques (e.g., Legendre-Gauss pseudospectral methods), randomized kinodynamic planning for closed-chain robots, and cable-driven parallel robot control. His work bridges numerical computation and practical robotic applications, often involving collaboration with industry partners. Awards: Honorary Mention for the Planets Project (2017), Best Final Year Engineering Project (1991-1992). Advising & Grants: Advised PhD students like Ricard Bordalba and Carlos Rosales. Involved in projects like Synthesis of Optimally Agile and Graceful Robot Motions (2022) funded by competitive R&D grants. Labs/Teams: Leads the CRG - Computational Robotics Group , collaborating with institutions like the Institut de Robòtica i Informàtica Industrial (CSIC-UPC). Active in developing the CUIK Suite , a tool for analyzing multibody system motion.

• Robotics
• Computational Kinematics and Dynamics
• Motion Planning and Control
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Manuel Fernando Soler Arnedo is a Full Professor in the Aerospace Engineering Department at Carlos III University of Madrid's College of Engineering. His research focuses on Aerospace Engineering with specialization in Optimal Control Theory , Climate Impact Mitigation , and Artificial Intelligence applications for air traffic systems. He leads the Aerospace Engineering Research Group and has contributed extensively to Flight Trajectory Optimization , Weather-Induced Uncertainty , and Network-scale Conflict Resolution . Principal Researcher on EU-funded projects like F4EClim (2024-2027) and KAIROS (2023-2026) Key international collaborations with NEXTOR (UC Berkeley) and ETH Zurich Developed tools like CLIMaCCF V1.0 and ROOST V1.0 for climate-aware flight planning His work integrates Artificial Intelligence with Climate Modeling to address 4D Trajectory Planning , Thunderstorm Avoidance , and Non-CO2 Emission Reduction in aviation. Recent publications emphasize Robust Optimization under meteorological uncertainty and Deep Learning for traffic flow management. He has supervised theses on Data Science for Weather Mitigation and Multi-objective Space Mission Design , with grants from European Commission , Boeing , and Spanish government agencies .

• Aerospace Engineering
• Optimal Control Theory
• Air Traffic Management
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José Manuel Arco Rodríguez is an Associate Professor in the Department of Automation at the Universidad de Alcalá (Spain). He holds a Doctorate from the same institution for his thesis Propuesta de optimización de la interconexión de redes con calidad de servicio para aplicaciones multimedia (2000), supervised by Dr. Daniel Meziat Luna. His research focuses on intelligent networks, software-defined networking (SDN), edge computing, and telecommunication systems, with particular emphasis on network optimization, protocol design, and AI integration in network architectures. He leads the NetIS research group (Networks and Intelligent Systems), exploring cutting-edge solutions for scalable, reliable data center networks and industrial IoT ecosystems. Key research areas include in-band network control, hybrid SDN architectures, multi-hop edge computing with IoT devices, and low-latency bridging protocols. His work spans theoretical frameworks to hardware implementations (e.g., NetFPGA), with a strong emphasis on practical applications in data centers, campus networks, and industrial environments. Recent contributions address AI-driven network management, plug-and-play routing protocols, and zero-configuration network architectures. Publications highlight advancements in SDN topology discovery (TEDP), scalable addressing (GA3), and path exploration protocols (ARP-Path, All-Path Bridging). His research bridges theoretical networking principles with real-world deployment challenges, often emphasizing interoperability between legacy and modern systems. Arco Rodríguez has collaborated on EU-funded projects and contributed to international standards for network protocols. His lab (NetIS) actively develops open-source tools for network analysis and simulation. Current research trends include AI-enhanced softwarized networks and cloud-edge continuum architectures for IIoT.

• Computer Networks
• Software-Defined Networking (SDN)
• Telecommunications
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Elisa Rojas Sánchez is a tenured professor at the University of Alcalá, affiliated with the Department of Automation within the School of Telematics Engineering. Her primary research focuses on advanced networking technologies including Software-Defined Networking (SDN), edge computing, IoT integration, and network architecture optimization. She leads the NetIS research group (Networks and Intelligent Systems), exploring innovations in programmable networks and intelligent systems for future communication infrastructures. Her academic background includes a doctoral thesis on high-performance transparent Ethernet switch architectures. She has contributed significantly to protocols like ARP-Path and Torii-HLMAC, advancing scalable routing and fault-tolerant data center designs. Her work bridges theoretical networking research with practical implementations in 6G, industrial IoT, and cloud-edge continuum systems. Recent publications highlight breakthroughs in data-driven protocols (e.g., BareFlow), AI-driven fault prediction in smart grids, and topology-aware resource management in dense networks. She also explores educational innovations like gamification in engineering teaching and hybrid SDN methodologies. Key Research Themes: SDN protocols, edge computing frameworks, IoT scalability, network resilience, AI in networking Notable Achievements: Developed open-source tools like NetIDE, contributed to OpenFlow standards, and pioneered multi-path routing algorithms Her work frequently addresses real-world challenges such as latency reduction in programmable ASICs (Tofino P4), secure in-band control channels, and collaborative resource-sharing in edge environments. She actively participates in international conferences as a program chair and continues advancing the next generation of network architectures.

• Networking
• Software-Defined Networking (SDN)
• Edge Computing
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Manuel Utrilla Manso is an Associate Professor at the Department of Signal Theory and Communications at the University of Alcalá. His research focuses on signal processing, acoustic sensor networks, and machine learning applications in audio-based systems. He leads the AES3 research group, specializing in smart acoustic and electromagnetic sensor networks and signal processing. His work addresses challenges in UAV acoustic detection, emotion recognition (e.g., anger detection), and speech processing for hearing aids. He holds a Ph.D. from the University of Alcalá with a thesis on finite-precision analysis in advanced digital filter structures. Key research interests include: Acoustic localization and source separation Machine learning for audio classification Optimization of microphone array configurations Non-destructive spectral analysis using sound Hearing aid algorithms and noise suppression Publications emphasize robust systems for noisy environments, computational efficiency, and interdisciplinary applications in healthcare and environmental monitoring. His work bridges theoretical signal processing with practical implementations in automotive, biomedical, and smart sensor domains. Notable contributions include development of benchmark datasets for sound event classification and optimization frameworks for waveform design in non-destructive testing. Research extends to educational technologies, including formative assessment methodologies for engineering students and interdisciplinarity in technical education.

• Signal Processing
• Acoustic Sensor Networks
• Machine Learning Applications
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Adriano Jose Carmona serves as Full Professor at Universitat Politècnica de Catalunya (UPC-BarcelonaTech) within the Department of Signal Theory and Communications, College of Telecommunications Engineering. He holds dual affiliations with the Remote Sensing Lab (RSLAB) and NanoSat Lab, while also maintaining a visiting professorship at UAE University since 2022. His research spans microwave remote sensing , GNSS-reflectometry , RF interference mitigation , and nanosatellite development . Notable projects include the 3Cat series of CubeSats (3Cat-1 through FSSCAT), with FSSCAT producing the first scientific-quality Arctic soil moisture and sea ice maps using CubeSat technology. His work integrates signal processing innovations with practical Earth observation applications. Analysis of his 15 most recent publications reveals dominant trends in High-resolution soil moisture mapping using neural networks Earthquake precursor detection through multi-sensor thermal anomalies Advanced RFI mitigation techniques for radiometers CubeSat constellation architectures for 6G networks Wildfire burned area prediction using causal models Honors include IEEE Fellow (2011), ICREA Academia Award (2009, 2015), and the IEEE GRSS Education Award (2021), alongside multiple technology transfer prizes like the ESA Sentinel Small Satellite Challenge (2017). As research advisor, he has supervised 29 completed PhD theses (with 9 ongoing), producing professionals now at NASA/JPL, University of Michigan, and founders of startups BALAMIS and MITICS. His leadership extends to directing the CommSensLab Research Center (2016-2020) and serving as past President of the IEEE Geoscience and Remote Sensing Society.

• Microwave Remote Sensing
• GNSS-R
• Radio Frequency Interference Detection
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Raul Sarrias Mena serves as Assistant Professor in the Department of Automation, Electronics, Architecture and Computer Networks Engineering at the University of Cádiz since February 2020, following his appointment as full-time professor in January 2017. He is a core member of the PAIDI Research Group TEP-023: Sustainable and Renewable Electrical Technologies since its creation in 2011. His educational background includes: Industrial Engineering with specialization in Industrial Electronics (2003-2007) at University of Cádiz Second cycle of Industrial Engineering (2007-2010) Master's Degree in Computational Modeling in Engineering (Extraordinary Award recipient) PhD in Wind power generation with energy storage systems (2016, International Mention, Cum Laude, Extraordinary Doctoral Award) Dr. Sarrias Mena's research focuses on renewable energy integration with particular expertise in microgrid control architectures , energy storage optimization , and power electronics for sustainable systems . His work bridges theoretical control strategies with practical hardware implementation, frequently utilizing Raspberry Pi platforms for low-cost validation. Current investigations emphasize multi-energy systems combining electrical, hydrogen, and thermal components through reinforcement learning approaches. Analysis of his 15 most recent publications (2023-2025) reveals dominant research trends in multi-microgrid coordination (32% of articles), hydrogen integration (27%), and fault-tolerant control (20%), with increasing application of artificial intelligence techniques. His work consistently addresses practical implementation challenges in power electronics hardware. Scientific recognition includes: Extraordinary Doctoral Award International Mention for PhD thesis Outstanding Cum Laude grade Extraordinary Award for Master's degree Dr. Sarrias Mena has supervised 10 Final Degree/Master's theses and currently co-directs 4 doctoral theses. His research has been supported through participation in 3 competitive national/international projects including collaborations with Cardiff University established during his 2015 research stay. The TEP-023 research group provides his primary laboratory infrastructure for experimental validation of microgrid control systems.

• Renewable Energy Systems
• Microgrid Control
• Energy Storage Integration
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Juan Carlos López Ríos is an Associate Professor at the School of Mathematics, Industrial University of Santander (UIS), Bucaramanga, Colombia. He specializes in Partial Differential Equations, Inverse Problems, and Fluid Mechanics, with a focus on water-wave dynamics and control theory. His work involves collaborations with international researchers from Chile, Spain, and France. Education: PhD in Engineering Sciences (2015), University of Chile Bachelor in Mathematics (2006), National University of Colombia His research addresses mathematical modeling of fluid dynamics, including sloshing problems, chemotaxis-Navier-Stokes systems, and heat transport in Hele-Shaw geometries. Recent work explores controllability of surface gravity waves and inverse problems in shallow water equations. Publications span journals like Inverse Problems , ESAIM: Control, Optimization and Calculus of Variations , and Journal of Mathematical Fluid Mechanics . Collaborative efforts include numerical methods for PDE-constrained optimization and surface measurement-based bottom detection in water waves.

• Partial Differential Equations
• Inverse Problems
• Fluid Mechanics
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