جست‌وجوی استاد و پژوهشگر

• Optimization Algorithms
• Smart Grids
• Renewable Energy Systems
• +۳ مورد دیگر

Silvia Jiménez Fernández is an Associate Professor in the Department of Signal Theory and Communications at Universidad Autónoma de Madrid. Her research focuses on optimization algorithms, smart grids, renewable energy systems, telemedicine, and machine learning applications. She holds a Ph.D. from Universidad Politécnica de Madrid (2009), supervised by Dr. Francisco del Pozo Guerrero and Dr. Paula de Toledo Heras. Her work integrates interdisciplinary approaches, such as combining evolutionary algorithms with engineering challenges in energy systems and healthcare. Key contributions include advancements in coral reefs optimization algorithms for energy management, machine learning for battery health estimation, and telemedicine systems for chronic disease monitoring. Recent research trends emphasize hybrid learning models in education, multi-objective optimization in renewable energy systems, and risk analysis in smart grids with electric vehicles. She is affiliated with the GHEODE Research Group (Modern Heuristics and Network Design).

• Climate Change
• Atmospheric Dynamics
• Renewable Energy
• +۶ مورد دیگر

Juan Antonio Añel Cabanelas is a Professor of Earth Physics at the University of Vigo , affiliated with the EPhysLab research group and the Specialized Group on Atmospheric and Ocean Physics of the Royal Spanish Society of Physics . He serves as an Executive Editor for Geoscientific Model Development and an Associate Editor for PLoS Climate . PhD in Physics (2007) from the University of Vigo, thesis: Climatic analysis of the tropopause using radiosonde data Taught courses in Meteorology, Atmospheric Physics, Computational Science, and Renewable Energy at the University of Vigo and international institutions His research focuses on climate change impacts , upper troposphere-lower stratosphere dynamics , renewable energy modeling , and computational reproducibility in climate research . He emphasizes instrumental data recovery and open science , with recent work addressing stratospheric contraction and mercury cycling . Key publications span extreme weather-energy sector interactions , Fortran code quality , and ozone data analysis . He mentors PhD students in Physics and Computer Science, and has collaborated with institutions in Mexico, Portugal, and the private sector. He advocates for free software and has organized workshops on climate intervention and citizen science . His work is funded by public grants from Spain's Government, Xunta de Galicia, and private entities like Naturgy and Acciona, with computing support from Google and Microsoft.

Abolfazl Simorghمشاهده پروفایل

پژوهشگر

• Aircraft Trajectory Optimization
• Climate Change Mitigation in Aviation
• Robust Control
• +۳ مورد دیگر

Abolfazl Simorgh is a researcher at Charles III University of Madrid's Department of Aerospace Engineering, specializing in climate-optimized aviation systems. His work bridges mathematical control theory with practical climate impact mitigation, focusing on robust trajectory optimization under environmental and operational uncertainties. He leads development of open-source tools for sustainable flight planning while contributing to major European aviation initiatives. Education: B.Sc. in Control Engineering (2017) M.Sc. in Control Engineering (2020) Ph.D. in Aerospace Engineering from Charles III University of Madrid Dr. Simorgh's research centers on developing mathematical frameworks that reconcile aircraft trajectory optimization with climate impact reduction. His expertise spans robust control systems, optimization under uncertainty, and climate modeling integration, with particular emphasis on non-CO₂ emissions. His methodology addresses both CO₂ and non-CO₂ climate forcing mechanisms through computationally efficient algorithms that account for weather variability and climate metric uncertainties. This work directly supports aviation's decarbonization by providing operational strategies that reduce environmental footprint without prohibitive cost increases. Analysis of his 15 most recent publications reveals a cohesive research trajectory focused on operationalizing climate-optimal flight planning. His work consistently integrates climate science with aerospace engineering through robust optimization frameworks, demonstrating particular innovation in handling multiple uncertainty sources (weather, climate models, emissions). The publications cluster around three interconnected themes: 1) Development of open-source computational tools (ROOST, CLIMaCCF), 2) Network-scale implementation of climate-aware air traffic management, and 3) Risk analysis of climate mitigation strategies. This body of work establishes new methodological standards for quantifying and minimizing aviation's total climate impact. Scientific Awards: Luis Azcárraga Aeronautical Innovation Award for collaborative research impact Best Paper Award (2022) from a high-impact aerospace journal Dr. Simorgh secures significant research funding through European Commission projects including FlyATM4E (climate-optimized flight planning), ALARM (aviation emissions reduction), and RefMAP (sustainable aviation pathways). His grant portfolio emphasizes practical implementation of climate mitigation strategies, with strong industry-academia collaboration. He mentors junior researchers through project teams and has developed three major open-source Python libraries (CLIMaCCF, ROOST, ROC) that have become community standards for climate impact assessment in aviation research. His current work focuses on scaling climate-optimized trajectories to continental airspace while addressing operational constraints and economic viability. He leads a research group focused on climate-aware air traffic management, developing the ROOST simulation framework for GPU-accelerated trajectory optimization and the CLIMaCCF library for standardized climate metric calculations. His team collaborates with European air navigation service providers and aircraft manufacturers to transition research into operational practice, with current projects emphasizing real-time implementation and regulatory compliance frameworks.

• Earth Physics
• Climate Science
• Remote Sensing
• +۳ مورد دیگر

Francisco J. Tapiador is a Professor at the Universidad de Castilla-La Mancha , affiliated with the Department of Environmental Sciences. His research spans Earth Physics, Climate Science, and Remote Sensing, with a focus on precipitation modeling, climate classification systems, and data fusion techniques. He leads the Earth Physics research group at UCLM and collaborates extensively with international institutions. Key Research Areas : Earth Physics Climate Modeling Satellite Meteorology Data Fusion Algorithms Environmental Uncertainty Quantification Publication Trends : Dr. Tapiador's recent work emphasizes high-resolution precipitation merging via radar corrections, machine learning for storm detection, and uncertainty quantification in climate models. His articles integrate Remote Sensing , Machine Learning , and Climate Informatics to address extreme weather and hydrometeorological hazards. Peer Review Leadership : Atmospheric Research Chaos, Solitons and Fractals Chemosphere Heliyon Journal of Computational Science Meteorology and Atmospheric Physics Water Resources Research Collaborative Networks : Andrés Navarro Eduardo García-Ortega Gyuwon Lee Kyo-Sun Sunny Lim Ziad S. Haddad Technological Impact : His work bridges fluid dynamics , entropy-based algorithms , and neural networks to advance satellite precipitation estimation and climate model validation. Current projects include multi-satellite data correction and climate-human system couplings.

Antonio Contreras de Villarمشاهده پروفایل

دانشیار

• Coastal Engineering
• Hydraulic Engineering
• Sediment Transport
• +۳ مورد دیگر

Antonio Contreras de Villar is an Associate Professor at the University of Cádiz, affiliated with the Department of Industrial Engineering and Civil Engineering. A member of the RNM912 Coastal Engineering research group, his work focuses on hydraulic engineering, sediment transport, and coastal resilience. Education: PhD in Coastal Engineering from University of Cádiz (2017), with thesis on beach regeneration parameters under tidal conditions. His research spans advanced technologies like UAV-SfM photogrammetry for coastal defense monitoring, climate change impacts on coastal zones, and innovative sediment analysis methods. He also contributes to engineering pedagogy through virtual resources and laboratory practice improvements. Key scientific trends include sediment transport dynamics, climate adaptation strategies, and integration of geospatial technologies in coastal studies. While no awards are explicitly mentioned, his extensive publications reflect expertise in Mediterranean coastal systems, particularly in Cádiz and Málaga provinces.

• Power Electronics
• Renewable Energy Systems
• Microgrids
• +۳ مورد دیگر

Maria Elena Martin Cañadas is an Associate Professor at the Department of Electrical Engineering within the Barcelona East School of Engineering (EEBE) at Universitat Politècnica de Catalunya (UPC). She leads research at the SEPIC group (Power Electronics and Control Systems), focusing on renewable energy integration and power systems optimization. Research Interests: Her work spans power electronics, microgrid design, energy policy analysis, and control systems for distributed generation. Key research areas include: Regulatory frameworks for renewable energy adoption Uncertainty modeling in energy systems High-temperature heat pump technologies Economic optimization of microgrids Solar energy integration and policy analysis Publication Trends: Recent articles (2020-2025) demonstrate strong focus on regulatory impacts in energy systems, with methodologies addressing uncertainty through stochastic modeling and probabilistic analysis. Dominant themes include microgrid optimization, solar policy evolution, and decarbonization strategies for industrial applications. Student Advising & Projects: Supervised doctoral candidates include Alonso (microgrid design), Coronas (distributed generation), and El Mariachet (power quality). Actively leads competitive R&D projects such as: Decarbonization of energy-intensive industries Power quality improvement in remote systems Regulatory framework development for Latin American biogas projects Research Group: Core member of SEPIC laboratory specializing in power electronics applications for sustainable energy systems, collaborating with industrial and international partners.

• Machine Learning
• Climate Science
• Energy Systems
• +۳ مورد دیگر

Sancho Salcedo Sanz is a Full Professor at the Universidad de Alcalá, affiliated with the Signal Theory and Communications Department and the GHEODE Research Group. His work focuses on applying machine learning and optimization techniques to energy systems, climate science, and environmental modeling. He holds PhDs from Universidad Complutense de Madrid (2019) and Universidad Carlos III de Madrid (2002). Key research interests include deep learning for energy price prediction, spatio-temporal climate analysis, and hybrid models for renewable energy forecasting. His GHEODE group develops optimization algorithms for network design and distributed systems. Recent publications highlight advancements in extreme weather prediction, smart grid optimization, and explainable AI for environmental monitoring. He has pioneered methodologies like Autoencoder-based flow analogues for heatwave reconstruction and multi-method ensembles for energy demand modeling. Labs/Teams: Leader of the GHEODE Group, specializing in modern heuristics and network design. Collaborates extensively on interdisciplinary projects combining AI with environmental and engineering applications.

• Climate Science
• Environmental Science
• Atmospheric Science
• +۷ مورد دیگر

Summary Dr. Gonzalo Miguez Macho is a Professor at the Department of Particle Physics, Faculty of Physics, Universidade de Santiago de Compostela. His research focuses on climate science, environmental dynamics, and numerical modeling, with emphasis on land-use impacts, hydroclimatic sustainability, and wildfire behavior. He leads the GFNL Nonlinear Physics Group and is affiliated with the Center for Interdisciplinary Research in Environmental Technologies (CRETUS). Education: Ph.D. in Atmospheric Sciences (not explicitly stated, inferred from research focus). Research Interests: Dr. Miguez Macho studies climate change effects on ecosystems, particularly in the Amazon and Mediterranean regions. His work explores soil moisture dynamics, groundwater interactions, and the role of vegetation in precipitation recycling. He also investigates extreme weather events, such as heatwaves and wildfires, and their links to anthropogenic climate change. Publications: His recent work includes studies on groundwater influences on soil moisture, climate impacts of urbanization in Phoenix, and modeling deep root water uptake in tropical forests. Key themes include land-atmosphere feedbacks and the hydrological cycle. Awards: None explicitly mentioned in the text. Grants/Teams: Collaborates with institutions like NCAR and USGS on projects such as CONUS404 datasets and wildfire modeling. His research group uses advanced models like WRF and RAMS for simulations. Labs/Teams: GFNL Nonlinear Physics Group and CRETUS, focusing on interdisciplinary environmental research.

• Machine Learning
• Signal Theory and Communications
• Structural Engineering
• +۴ مورد دیگر

César Peláez Rodríguez is an Assistant Professor at the Department of Signal Theory and Communications, University of Alcalá. He is affiliated with the GHEODE research group (Modern Heuristics and Network Design Research Group) within the School of Electrical Engineering. His research focuses on machine learning applications in structural engineering, weather forecasting, and optimization. He earned his PhD from the University of Valladolid in 2024, with a thesis on machine learning for non-deterministic actions in slender structures. Key research areas include data-driven modeling of extreme events, hybrid machine learning systems for energy grids, and spatio-temporal analysis of climate phenomena. His work combines AI techniques with domain-specific challenges in civil engineering and renewable energy. Recent contributions address resilience to wind extremes, heatwave drivers, and fog-related low-visibility prediction using ensembles and fuzzy logic. Publications highlight innovations in autoencoder frameworks for forecasting, stochastic pedestrian modeling, and explainable AI approaches for hospital emergency predictions. Collaborations span academia and industry, emphasizing practical implementations of machine learning solutions.

• Physical Geography
• Climatology
• Climate Change
• +۷ مورد دیگر

Maria Jose Estrela Navarro is a Full Professor in the Department of Geography at the Faculty of Geography and History, University of Valencia, where she conducts research in physical geography, climatology, and hydrological systems. She is a key member of the CLIMAMET research group, focusing on climate change, weather risks, and hydrological inputs in the Mediterranean region. Her research interests include: Climate change and its impacts on bioclimatic zones Fog-water collection as a sustainable water resource Mesoscale meteorological modeling (WRF, RAMS) Drought and precipitation trends in Mediterranean basins Fire weather and forest fire risk assessment Remote sensing and satellite data applications in climatology Her recent publications (2023–2025) reveal a strong focus on long-term climate trends in Spain and the Balearic Islands, particularly in precipitation, drought, fog-water dynamics, and wildfire risk. These studies employ advanced modeling, statistical downscaling, and satellite data to assess climate variability and change across the Iberian Peninsula. The work consistently emphasizes the Mediterranean context, leveraging high-resolution data to understand regional climate behavior and its societal implications. Scientific awards and honors are not mentioned in the available text. She advises students and leads research projects, though specific names of advisees are not listed. She has been involved in operational forecasting systems and climate modeling projects, contributing to real-time meteorological prediction in the Valencia region. Her work bridges academic research and practical applications in water resource management and climate adaptation. She leads and conducts research within the CLIMAMET research group, which investigates climate change impacts, weather extremes, and hydrological processes in the western Mediterranean, particularly in the Valencian Community and surrounding river basins (Júcar and Segura).

• Machine Learning
• Remote Sensing
• Artificial Intelligence
• +۹ مورد دیگر

Jordi Muñoz Mari is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, University of Valencia. He is a key member of the Image and Signal Processing (ISP) research group within the Image Processing Laboratory (IPL), a recognized research institute (ERI) at the university. His research focuses on the intersection of artificial intelligence, remote sensing, and environmental science. Key areas include machine learning for Earth observation, biophysical parameter retrieval, crop yield forecasting, climate modeling, and causal inference in ecological systems. He also explores applications of AI in education, particularly generative models for assessment and digital learning tools. The most recent publications highlight a strong trend toward physics-aware machine learning, uncertainty quantification, and large-scale applications using platforms like Google Earth Engine. His work spans climate extremes (medicanes, hurricanes, droughts), agricultural monitoring, biodiversity, and educational technology, demonstrating interdisciplinary innovation. Jordi Muñoz Mari completed his PhD at the University of Valencia in 2004 on telemonitoring systems for cardiac patients. His ongoing research involves advanced signal processing, kernel methods, and AI-driven geoinformation systems.

• Agriculture, Multidisciplinary
• Soil Science
• Microbiology
• +۹ مورد دیگر

Laura Sanchez Martin serves as a University Professor in the Department of Food Chemistry and Technology at the Technical University of Madrid (UPM), holding this position since April 23, 2019. She has been affiliated with UPM since October 22, 2014, initially as a Profesora Contratada Doctora. Her institutional roles include membership in the Research Group on Pollution of Agroecosystems by Agricultural Practices (since June 14, 2005) and the Center for Studies and Research on Agricultural and Environmental Risk Management (CEIGRAM), a joint UPM-AGROSEGURO-ENESA initiative (since January 23, 2018). Her research spans critical interdisciplinary domains at the intersection of agriculture and environmental systems: Soil Science and Environmental Chemistry Agronomy, Crop Science, and Animal Science Atmospheric Sciences, Meteorology, and Global Change Ecology and Microbiology of agroecosystems This work focuses on agricultural pollution mechanisms, risk assessment in food production systems, and sustainable management of environmental resources. Her methodologies integrate laboratory analysis with field studies to address contamination pathways in soil-water-atmosphere interfaces. Professional contact is maintained via laura.sanchez@upm.es . Current projects emphasize agricultural risk modeling through CEIGRAM's collaborative framework with industry and government stakeholders.

• Forest Fires
• Wildland-Urban Interface Fires
• Technological Risk
• +۵ مورد دیگر

Elsa Pastor Ferrer is a Professor in the Department of Chemical Engineering at the School of Engineering of Eastern Barcelona (EEBE), Universitat Politecnica de Catalunya (UPC). She serves as a contracted professor (Catedràtic contractat) and leads significant research in forest fires and technological risk assessment. Her work spans multiple research groups including CERTEC (Center for Technological Risk Studies) and CER-H2 (Research Center for Hydrogen at UPC). Dr. Pastor Ferrer's research focuses on wildland-urban interface (WUI) fires, fire safety engineering, and technological risk assessment. Her expertise encompasses wildfire risk modeling, structural protection against fires, vegetation flammability, and hydrogen safety. She has developed methodologies for vulnerability assessment at property level and created tools like TourGuard for infrastructure vulnerability assessment. Her work integrates computational fluid dynamics (CFD) with artificial intelligence for dynamic risk assessment in fire scenarios. Her recent publication trends show strong emphasis on practical applications of fire safety research, with numerous deliverables for EU projects like WUITIPS and FIREPRIME. These publications demonstrate growing integration of virtual reality for risk visualization and intelligent systems for dynamic risk assessment. Her work bridges theoretical fire science with practical risk mitigation strategies for communities and infrastructure. Best Poster Award - First Place (2025) Mención Honorífica de DOCTOR EUROPEO (European Doctor Mention of Honor) Dr. Pastor Ferrer actively advises PhD students including Juan Antonio Muñoz Navarro, Francisco de Borja Rengel Darnaculleta, and Mario Miguel Valero Perez. She leads multiple competitive research projects with funding from EU Civil Protection Mechanism, Horizon Europe, and Spanish national programs. Her work includes significant collaboration with Eulalia Planas Cuchi (275 joint publications) and Alba Àgueda Costafreda (77 joint publications). She contributes to major research initiatives including the 3D Fire LABoratory and the GUARDIAN project for WUI fire protection. Her work extends to practical applications like assessing fire behavior in parking structures and developing irrigation technologies for wildfire protection.

Javier Garcia-Heras Carreteroمشاهده پروفایل

دانشیار

• Air Traffic Management
• Flight Planning under Uncertainty
• Convective Weather Prediction
• +۱۲ مورد دیگر

Javier Garcia-Heras Carretero is an Associate Professor in the Department of Aerospace Engineering at Universidad Carlos III de Madrid (UC3M), where he conducts research and teaches in air traffic management, flight planning, and AI applications in aviation. He is a member of the Aerospace Engineering Research Group. Research Interests: His work focuses on enhancing air traffic flow management through machine learning and optimization, particularly in mitigating weather-related disruptions. Key areas include robust 4D flight planning under uncertainty, convective weather prediction, continuous climb operations, and environmental impact reduction in aviation. He integrates AI models such as LSTM and CNNs to forecast thunderstorms and optimize traffic flow. Recent Publication Trends: His most recent articles (2023–2024) emphasize deep learning for pre-tactical convection prediction, fast stochastic flight path simulation under uncertainty, and AI-driven hotspot detection in air traffic due to weather. These works reflect a strong trend toward data-driven, real-time decision support systems in ATM using neural networks and parallel computing. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: He supervises BSc and MSc theses, including one on data science techniques for weather mitigation in ATFM. He has led multiple research projects as Principal Investigator, including Collaborative Learning for Intelligent Meteorological Aviation (2024–2027) and Donut proyect (2019–2022). He has participated in numerous EU-funded projects such as KAIROS, REFMAP, ECONTRAIL, and ISOBAR, as well as industry collaborations with Airbus, Boeing, and SENASA. Labs and Teams: He is part of the Aerospace Engineering Research Group at UC3M, focusing on ATM systems, trajectory optimization, and digital aviation technologies. His team collaborates internationally on projects involving AI, weather forecasting, and sustainable aviation.

• Organizational Psychology
• Work Psychology
• Occupational Health
• +۵ مورد دیگر

Adrian Garcia Selva serves as an Assistant Professor in the Department of Behavioral Sciences and Health at Miguel Hernández University of Elche, operating as a part-time multi-campus lecturer. His teaching portfolio spans three bachelor's programs (Labor Relations and Human Resources, Occupational Therapy, Psychology) and the Master's in Human Resources Management, covering courses including Work Psychology, Health Education, Psychology of Human Resources, and Organizational Strategy. His research centers on Organizational Psychology and Occupational Health , with specific expertise in psychosocial risk factors, workplace stress, post-traumatic growth, and pandemic impacts on labor dynamics. Key investigation areas include technostress, telework adaptation, burnout in high-risk professions, and labor market integration for vulnerable populations. Recent publications (2018-2022) demonstrate consistent focus on crisis-induced workplace transformations, with 60% of articles addressing COVID-19 impacts. His work combines bibliometric analyses with empirical studies across diverse sectors (education, transportation, retail), emphasizing cross-cultural comparisons and methodological innovation in psychological assessment. As an active member of the Occupational Health research group, Garcia Selva supervises final degree projects and master's theses while coordinating multiple core courses. His tutorial system requires prior email appointment, reflecting structured student engagement within his part-time faculty role.