جست‌وجوی استاد و پژوهشگر

• Model Predictive Control
• Water Resources Systems
• Intelligent Transportation Systems
• +۵ مورد دیگر

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

• Energy Storage
• Renewable Energy Systems
• Control Systems
• +۳ مورد دیگر

Thomas Paul Puleston is a researcher at the Institute of Robotics and Industrial Informatics (IRI) within the Universitat Politècnica de Catalunya (UPC). His work focuses on advanced control systems, energy storage optimization, and integration of vanadium redox flow batteries (VRFBs) with renewable energy systems. Email: tpuleston@iri.upc.edu Current research projects include: MAFALDA: Manufacture, automation, and integration of VRFBs in renewable energy systems (2022–present) MASHED: Efficient management of energy systems with hybrid electrochemical storage using digitalization (2022–present) His publications emphasize VRFB optimization, electrolyte imbalance mitigation, and real-time monitoring algorithms. Recent work explores nonlinear observers, high-order sliding-mode control, and capacity loss prevention strategies. Collaborations involve researchers such as M. Serra, R. Costa, and A. Trovò. No scientific awards or student advisement details were found in the provided data.

Pablo Ordejónمشاهده پروفایل

استاد پژوهشی

• Electronic Structure Calculations
• Condensed Matter Physics
• Computational Materials Science
• +۳ مورد دیگر

Pablo Ordejón is a CSIC Research Professor, Group Leader, and Director at the Catalan Institute of Nanoscience and Nanotechnology (ICN2). He earned his physics degree (1987) and PhD in science (1992) from Universidad Autónoma de Madrid. His career includes postdoctoral work at the University of Illinois at Urbana-Champaign (1992–1995) and roles at Universidad de Oviedo (1995–1999) and the CSIC’s Institut de Ciència de Materials de Barcelona. Since 2007, he leads ICN2’s Theory and Simulation Group. He has published over 225 articles, with 34k+ citations (h-index 63). Roles: CSIC Research Professor, ICN2 Director (since 2012), Group Leader Affiliations: ICN2, CSIC, Editorial Boards of Physica Status Solidi (since 2004) and Nanomaterials (since 2018) Research focuses on electronic structure calculations, large-scale atomistic simulations (e.g., SIESTA method), and materials properties at the atomic level. Key interests include nanoscale devices, 2D materials, and collaborations with industry. Awards include the Narcís Monturiol Medal (2018) and American Physical Society Fellowship (2005). His work spans computational methods, thermal transport in 2D materials, and corrosion inhibition. Recent articles address AI-driven materials discovery, charge density waves, and quantum transport phenomena. He co-founded SIMUNE, a spinoff for simulation technologies. Grants and advisory roles include ANEP’s Condensed Matter Physics panel (2003–2006) and the Spanish Supercomputing Network’s Physics and Engineering Panel (2005–2011).

Chana Weil-Kennedyمشاهده پروفایل

پژوهشگر

• Formal Verification
• Distributed Systems
• Petri Nets
• +۳ مورد دیگر

Chana Weil-Kennedy is a Researcher at CEA List in Paris, focusing on formal verification of distributed systems, Petri nets, and theoretical computer science. Previously, she was a Postdoctoral Researcher at the IMDEA Software Institute (2023–2024) and completed her PhD at the Technical University of Munich (TUM), supervised by Javier Esparza. Her PhD thesis, Observation Petri Nets , explores parameterized verification and Petri net reachability under the ERC-supported PaVeS project. Education: PhD in Computer Science, TUM (2023) Master’s in Computer Science, École Normale Supérieure Paris-Saclay (2018) Bachelor’s in Mathematics, Université Paris-Sud (formerly Orsay) Research Interests: Runtime verification, distributed systems, formal methods, Petri nets, and mathematical reasoning in computer science. Her work emphasizes parameterized verification of protocols and systems, with applications to population protocols and distributed computations. Teaching & Supervision: Tutored courses at TUM including Automata and Formal Languages, Petri Nets, and Fundamental Algorithms. Co-supervised three Bachelor’s theses and a Master’s thesis on distributed systems and verification tools. Awards: Best Paper Award at Petri Nets 2019 for Parameterized Analysis of Immediate Observation Petri Nets . Labs/Teams: Active at CEA List, collaborating on runtime verification and distributed system analysis. Formerly part of Pierre Ganty’s group at IMDEA and Javier Esparza’s team at TUM.

• Distributed Computing
• Performance Evaluation
• Computer Networks
• +۴ مورد دیگر

Eduardo Huedo Cuesta is a Professor in the Department of Computer Architecture and Automation at the Universidad Complutense de Madrid (UCM). He holds the role of Catedrático de Universidad, equivalent to Full Professor. His primary affiliation is with the Facultad de Informática, where he leads research in distributed computing, cloud-edge infrastructures, and high-performance systems. He has been Principal Investigator (PI) of UCM in the EDGEDATA project funded by the Madrid Government and Scientific Coordinator of the EU-funded BEACON initiative. Current courses taught include Cloud and Big Data, Network Security, and Processing Architectures. PhD supervision spans topics like distributed scheduling, data-intensive workflows, and grid/cloud resource provisioning. Research focuses on intelligent resource orchestration, edge-cloud federation, and latency-optimized infrastructures for data science applications. His work integrates machine learning for resource provisioning and emphasizes practical applications in e-science, including collaboration with international projects like Gaia mission data archiving. Notable grants include: EDGEDATA (Madrid Government-funded) BEACON (EU H2020, leading Work Package 2) Initiative for Globus in Europe (EU 7th Framework) He has advised over 15 PhD students and contributed to influential frameworks like GridWay metascheduler, enabling interoperability between grid infrastructures.

DIEGO VERGARA RODRÍGUEZمشاهده پروفایل

مدرس

• Educational Technology
• Virtual Reality in Education
• Artificial Intelligence in Pedagogy
• +۷ مورد دیگر

DIEGO VERGARA RODRÍGUEZ is a Lecturer at the Faculty of Sciences and Arts of the Universidad Católica de Ávila. He is affiliated with the TiDEE.rg (Technology, Instruction and Design in Engineering and Education Research Group) , focusing on integrating technology into pedagogical practices. His research spans educational technology innovations, particularly in virtual reality (VR) and artificial intelligence (AI) applications in teaching, sustainable hydrogen energy systems, and the impact of digital tools on academic settings. Diego holds a Doctorate from the Universidad de Salamanca (2007) with a thesis titled "Fragilización por hidrógeno de aceros de pretensado sometidos a estados triaxiales de tensión" , which explored hydrogen embrittlement in steels under triaxial stress states. His educational background combines materials science and engineering expertise with a strong emphasis on pedagogical research. His research interests prioritize the transformative role of VR and AI in education, including their application in high-risk training simulations and sustainability-focused energy systems. He has extensively studied the adoption of these technologies among university faculty, comparing perceptions across disciplines (engineering vs. health sciences) and countries (Peru, Colombia, Mexico, etc.). Recent work also addresses post-pandemic digital stress adaptation and the didactic potential of gamification in higher education. His contributions include bibliometric reviews on smart composites, nuclear energy strategies, and gamification trends. He collaborates internationally, with studies on ICT use in Pacific Alliance countries and Venezuela's digital pandemic stress. His work frequently intersects with practical classroom experiences, such as calculus teaching with AI and improving spatial vision through 3D PDF tools. Diego is actively involved in analyzing educational policies and the influence of technological ecosystems on learning environments. He advocates for inclusive digital solutions, emphasizing accessibility to cultural heritage and sustainable hydrogen infrastructure development.

Carlos Javier Pérez Gonzálezمشاهده پروفایل

دانشیار

• Statistics
• Operations Research
• Reliability Engineering
• +۳ مورد دیگر

Carlos Javier Pérez González serves as an Associate Professor in the Department of Mathematics, Statistics and Operations Research at the University of La Laguna, Spain. He is affiliated with The Institute of Mathematics and Applications and contributes to two PhD programs: Mathematics and Statistics, and Industrial Engineering, Informatics and Environmental Engineering. Education PhD in Mathematics and Statistics from University of La Laguna (2009), thesis: "Avances en el diseño óptimo de planes de muestreo en fiabilidad" (Advances in Optimal Design of Sampling Plans in Reliability), supervised by Dr. Arturo Javier Fernández Rodríguez Research Focus His primary expertise spans Statistics and Operations Research with emphasis on reliability engineering, acceptance sampling methodologies, and censoring techniques. He develops advanced statistical models for multi-component reliability systems, stress-strength analysis, and risk-based quality control frameworks. His work bridges theoretical statistics with industrial applications through Bayesian approaches and optimization algorithms. Publication Trends Recent publications (2020-2025) demonstrate consistent innovation in reliability test planning under censoring constraints, multi-component system analysis, and adaptive sampling schemes. His research increasingly incorporates real-world applications including marine conservation studies in the Canary Islands and emergency management data analysis using R programming. Research Integration As an active member of the Statistics research group at the Institute of Mathematics and Applications, he bridges methodological development with interdisciplinary collaborations across industrial engineering, environmental science, and public safety domains through data-driven approaches.

José E. Chacónمشاهده پروفایل

استاد

• Nonparametric Statistics
• Kernel Smoothing Methods
• Density Estimation
• +۳ مورد دیگر

José E. Chacón is a Professor of Statistics in the Department of Mathematics at the University of Extremadura since 2022. Previously, he held roles at the University of Valladolid and other positions within Extremadura. His research focuses on nonparametric statistics, kernel smoothing methods for density estimation, and their applications in clustering. He is actively involved in initiatives like the NICDA Workshop and Statistics Reading Club. Education history details are not explicitly provided in the text. His research interests emphasize advanced statistical methodologies including density derivative estimation, nonparametric clustering, and applications in epidemiology and ecology. Notable contributions include work on Bayesian taut splines, mode-based symmetry estimation, and statistical modeling for animal home ranges. Recent publications (2020–2024) explore cutting-edge topics such as geodesic normal distributions, cross-validation techniques, and SIR modeling for pandemic data. His work bridges theoretical advancements with practical applications in health, ecology, and machine learning. Awards and grants are not explicitly mentioned. Chacón has advised no listed students but collaborates on interdisciplinary projects, including the special issue on Data Science for COVID-19. His research lab focuses on multivariate kernel smoothing and nonparametric methods.

Leonardo Surianoمشاهده پروفایل

پژوهشگر

• Runtime Adaptive Hardware/Software execution
• High-Performance Computing
• Parallel Computing
• +۴ مورد دیگر

Leonardo Suriano is a Ph.D. student at the Universidad Politécnica de Madrid (UPM), affiliated with the Department of Electronic Engineering. His research focuses on runtime adaptive hardware/software execution in complex heterogeneous systems (CPU + FPGA + GPU), high-performance computing, parallel computing, and embedded systems. He has contributed to European projects Enable S3 and Cerbero, developed tools for dataflow-based design space exploration, and is a contributor to the PREESM open-source project on GitHub. His work bridges hardware acceleration, cyber-physical systems, and real-time computation. He received the Best Research Project at the Industrial Research Meeting 2016 Best Oral Session award in the Simposio Tu Tesi en 4 Minutos (UPM, 2018) He has published extensively on heterogeneous MPSoC optimization, inverse kinematics, and image processing, with key subfields including GPU/FPGA integration, task scheduling, and firmware development.

• Plasma Turbulence
• Nuclear Fusion
• Magnetohydrodynamics (MHD)
• +۴ مورد دیگر

Luis Raul Sanchez Fernandez is a Full Professor at Universidad Carlos III de Madrid, serving as Director of the Master's Degree in Plasma Physics and Nuclear Fusion. His research focuses on plasma turbulence, magnetohydrodynamics (MHD), and advanced confinement regimes in fusion devices. Key areas include I-mode transport control, Alfven eigenmode dynamics, and numerical methods for plasma equilibrium. His work integrates computational tools like SIESTA and FLIPEC for solving MHD equilibria and stability problems. Recent studies explore non-diffusive transport, magnetic island effects, and cross-phase modification for enhanced plasma confinement. He has contributed to ITER-related pedestal transport analysis and tungsten impurity studies. Publications emphasize fusion energy applications, plasma edge physics, and turbulence modeling. His team addresses challenges in stellarators and tokamaks, with a focus on self-organized criticality and transport barrier formation. Ongoing projects include developing efficient numerical algorithms and advancing control mechanisms for burning plasmas.

• Mechanical Engineering
• Robotics
• Additive Manufacturing
• +۳ مورد دیگر

ENRIQUE SORIANO HERAS is an Adjunct Professor at the Universidad Carlos III de Madrid's Department of Mechanical Engineering. His research focuses on mechanical systems, robotics, additive manufacturing, and biomedical engineering applications. Key interests include mechanism design, predictive maintenance, and advanced manufacturing techniques. His work spans interdisciplinary projects such as applying machine learning to railway maintenance, developing robotic prosthetics, and optimizing 3D printing processes. He emphasizes practical applications, integrating Industry 4.0 principles into mechanical systems and advancing educational methodologies in engineering education. Recent publications highlight innovations in four-bar linkage synthesis, underactuated robotic fingers, and mathematical modeling for clamping systems. His research often bridges theoretical analysis with real-world implementation, addressing challenges in both mechanical and biomedical domains. No scientific awards are explicitly mentioned. His advising record is not detailed here, but his extensive project-oriented learning initiatives reflect a commitment to educational innovation.

Luis Miguel Bergasa Pascualمشاهده پروفایل

استاد

• Autonomous Driving
• Reinforcement Learning
• Vehicle Motion Prediction
• +۴ مورد دیگر

Luis Miguel Bergasa Pascual is a Professor specializing in autonomous driving, robotics, and artificial intelligence. His work focuses on bridging simulation-to-reality gaps for autonomous systems, with particular emphasis on control algorithms, motion prediction, and V2X communication integration. His research spans Reinforcement Learning , Semantic Segmentation , and Hybrid Decision-Making Systems to enhance autonomous navigation in complex urban scenarios. Recent projects explore ROS-based modular architectures and social behavior modeling for vehicle motion prediction. Publications reveal a strong focus on Computer Vision , Intelligent Transportation Systems , and Simulation Testing , particularly using the CARLA simulator. Key trends include multimodal sensor fusion, synthetic data training, and safety validation protocols. While specific awards and students are not listed, his contributions to point cloud segmentation , deep learning control systems , and collaborative planning highlight his role in advancing autonomous vehicle technologies.

• Power Electronics
• Renewable Energy Systems
• Electrical Engineering
• +۳ مورد دیگر

Emilio José Bueno Peña is a full Professor at the Department of Electronics, Universidad de Alcalá, Spain. He leads the GEISER research group (Electronic Engineering Applied to Renewable Energy Systems). His research focuses on power electronics, renewable energy integration, and control systems for distributed generation. He holds a PhD in Electronics from Universidad de Alcalá (2005), supervised by Dr. Francisco Javier Rodríguez Sánchez and Dr. Felipe Espinosa Zapata. His work emphasizes grid-forming converters, smart grid technologies, and thermal modeling of power electronics components using artificial neural networks. Recent contributions include DC/AC interface impedance shaping, mobile charging infrastructure analysis, and adaptive model predictive control for high-efficiency converters. He has published extensively on multilevel converters, virtual synchronous machines, and renewable energy system stability. His research bridges theoretical advancements with practical implementations in railway systems, wind turbines, and solid-state transformers. No scientific awards are listed, but his work has significant industry and academic impact.

• Photonics Engineering
• Optical Fiber Sensing
• Distributed Acoustic Sensing (DAS)
• +۳ مورد دیگر

Dr. María del Rosario Fernández Ruiz is a researcher at the University of Alcalá (UAH) in the Department of Electronics , affiliated with the GRIFO Photonics Engineering Group . She earned her Ph.D. from Université du Québec in 2016 with a thesis on time- and spectral-domain holography for optical signal processing. Her research focuses on advanced optical fiber sensing technologies, particularly distributed acoustic sensing (DAS), time-expanded phase-sensitive OTDR (ΦOTDR), and dual-comb spectroscopy. Key Research Areas: Photonics Engineering Optical Fiber Sensing Distributed Acoustic Monitoring Time-Expanded OTDR Dual-Comb Spectroscopy Her recent work addresses high-resolution dynamic strain sensing, curvature monitoring, and applications in geophysics, including seismic activity and climate change analysis. She explores noise reduction techniques, Nyquist zone averaging, and multifrequency demodulation to enhance sensor performance. Her articles highlight collaborations in submarine sensing, seismic tomography, and aerospace structural monitoring. Notable Scientific Contributions: Developed time-expanded ΦOTDR systems for sub-centimeter resolution Advanced dual-comb and Nyquist zone averaging methods Explored dark fiber networks for environmental monitoring

José Luis Lázaro Galileaمشاهده پروفایل

استاد

• Electronics Engineering
• Intelligent Systems
• Positioning Systems
• +۳ مورد دیگر

José Luis Lázaro Galilea is a Professor in the Department of Electronics at the University of Alcalá. He is affiliated with the GEINTRA research group, focusing on Electronic Engineering applied to Intelligent Spaces and Transport. His doctoral thesis (1998) explored infrared modeling for mobile robot guidance. Key research areas include visible light positioning systems, FPGA-based hardware architectures, and remote laboratory development. He has contributed to vehicular VLC systems, indoor navigation algorithms, and biomedical applications like closed-loop insulin delivery systems. Notable projects include the ALCOR initiative for optimizing robot guidance in smart environments and the Helpresponder system for emergency intervention safety. Education: PhD in Electronics from University of Alcalá (1998). Supervised by Dr. Manuel Ramón Mazo Quintas. Academic focus spans digital electronics, embedded systems, and sensor networks. Active in educational innovation, including adapting digital electronics practices for blended learning models. Research emphasizes practical applications of electronic systems in smart spaces, with over 70 publications since 1998. Recent work addresses multipath effects in optical positioning, reconfigurable hardware platforms, and human-centered lighting systems. His interdisciplinary approach integrates robotics, telecommunications, and biomedical engineering. Notable contributions include: Development of high-precision indoor positioning systems using PSD sensors Optimization of sensor deployment via evolutionary algorithms Design of FPGA-based real-time processing architectures Innovative remote laboratory frameworks for STEM education Current projects explore vehicular visible light communication, wearable medical devices, and intelligent transportation systems. His work bridges theoretical advancements with practical implementations in both academic and industrial contexts.