Find Academic Supervisors

• Wildfire Ecology
• Forest Fire Regime Analysis
• Climate Change Impact on Fire Dynamics
• +3 more

Gonzalo Zavala Espiñeira is a Professor at the Department of Environmental Sciences, University of Castilla-La Mancha. His academic career at the institution spans from 2001 to the present, with roles including: Profesor Contratado Doctor (2018–Present) Profesor Ayudante Doctor (2012–2018) Profesor Asociado Tiempo Completo (2001) His research focuses on fire ecology and climate-fire interactions in Mediterranean ecosystems. Key themes include: Fire regime dynamics and seasonality Post-fire vegetation recovery mechanisms Carbon cycling in fire-prone forests Fire behavior modeling and prediction Land use policy impacts on wildfire risk Publications highlight his work in integrating remote sensing with field experiments to study plant responses to fire, traditional fire management implications, and climate-driven fire hazard assessment across spatial scales.

Manuel Fernández DelgadoView profile

Associate Professor

• Machine Learning
• Pattern Recognition
• Computer Vision
• +3 more

Manuel Fernández Delgado is an Associate Professor at the University of Santiago de Compostela (manuel.fernandez.delgado@usc.es). His research spans Machine Learning , Pattern Recognition , and Computer Vision with applications in medical diagnostics, agricultural monitoring, and gender-inclusive education. PhD in Computer Science (1999) Developed software tools: Govocitos , CystAnalyser , STERapp Research highlights: Medical Imaging : Breast cancer and oral leukoplakia analysis via image segmentation/classification Agricultural AI : Nutrient deficiency detection in wheat, marbling analysis in ham Gender Equality : Pioneering computational thinking education with gender perspectives Robotics : Fault diagnosis systems for antenna arrays Key methodologies include Extreme Learning Machines, Support Vector Machines, and Deep Learning. He collaborates with teams in TELGalicia and TecAnDaLi networks.

Natalia Seoane IglesiasView profile

Associate Professor

• Semiconductor Device Simulation
• Nano-Device Variability
• Parallel and Distributed Computing
• +3 more

Natalia Seoane Iglesias serves as an Associate Professor in the Department of Applied Physics at the University of Santiago de Compostela's College of Physics. Her research integrates semiconductor device physics with high-performance computing to address challenges in next-generation electronics and energy conversion systems. B.Sc. in Physics, University of Santiago de Compostela (Spain) Ph.D. in Physics, University of Santiago de Compostela (2007) Postdoctoral research: University of Glasgow (2007-09), University of Edinburgh (2011), Swansea University (2013-15) Her research focuses on semiconductor device simulation , nanoscale variability analysis , and laser power conversion systems . She develops advanced computational tools combining 3D finite-element modeling with machine learning techniques to optimize device performance. Current projects target ultra-high efficiency (>80%) SiC-based laser converters for space applications and statistical variability studies in sub-10nm transistor architectures. Her publication portfolio reveals strong trends in machine learning-enhanced TCAD and high-concentration photovoltaics . Recent work demonstrates how vertical epitaxial heterostructures with SiC/GaN materials can overcome traditional efficiency barriers in wireless power transfer systems, while her nanoscale variability studies provide critical insights for future CMOS scaling. Key scientific contributions include: Development of MLFoMpy for semiconductor data post-processing Novel Pelgrom-based predictive models for device variability Breakthrough laser power converter architectures exceeding 80% efficiency Comprehensive studies of metal grain effects in nanosheet FETs She leads the rePowerSiC project (2024-2028) developing space-qualified laser power systems and contributes to multiple EU-funded initiatives in high-performance computing. Her team employs advanced simulation frameworks including VENDES and Silvaco Atlas for device characterization, with applications ranging from satellite power systems to refinery monitoring drones.

Mikel Diaz RodriguezView profile

Research Fellow

• Prehistoric Archaeology
• Archaeological GIS
• Human Settlement Patterns
• +10 more

Mikel Díaz Rodríguez is a Margarita Salas Postdoctoral Research Fellow at the University of Santiago de Compostela (Spain) and a guest researcher at Aarhus University (Denmark) since 2022. He holds a PhD in Geospatial Technologies applied to the study of the Paleolithic in the Northwest Peninsular (2020, "Sobresaliente Cum Laude") and two master's degrees in Archaeology and Antiquity Sciences (USC) and Teaching Training (UAX). He earned his BA in History from the University of Santiago de Compostela in 2013.

• Machine Learning
• Applied Mathematics
• Computer Vision
• +6 more

Javier Martinez Torres is a Full-Time Professor in the Department of Applied Mathematics I at the School of Industrial Engineering , University of Vigo. His work bridges machine learning, applied mathematics, and functional data analysis across diverse domains. Education : PhD from University of Vigo (2011) with thesis on slate plate classification using computer vision and machine learning. Research Interests focus on: Machine learning applications in industrial engineering and healthcare Multi-criteria decision-making for sustainable urban planning Functional data analysis for environmental monitoring AI-driven optimization of thermal and mechanical systems Recent publications highlight his interdisciplinary approach, combining machine learning with operations research for pedestrian modeling, grey MCDM in urban development, and LSTM networks for solar energy systems. His work spans public health (SARS-CoV-2 pooling strategies) and digital humanities (AI for document heritage management). He collaborates with the Center for Research in Technologies, Energy, and Industrial Processes at the Vigo campus.

• Traffic Safety
• Vehicle Safety
• Vulnerable Road Users Safety
• +5 more

Francisco Javier Paez Ayuso is an Associate Professor in the Department of Mechanical Engineering at the Technical University of Madrid (UPM), serving as Director of the University Institute for Automobile Research (INSIA-UPM) since January 2023 after holding prior roles as Subdirector and Director De Instituto. He has led INSIA's Traffic Accidents Investigation Unit since 1993 and coordinates Master's programs in Automotive Engineering and Electric/Hybrid Vehicle Engineering. Education: Predoctoral Fellowship, Ministry of Education and Science (1994-1996) Doctoral Thesis: "Model for predicting the occurrence of accidents on road sections by continuous measurement of influence variables" (2000, Cum Laude) Research Interests: Dr. Paez Ayuso specializes in traffic and vehicle safety with emphasis on vulnerable road users (VRUs), conducting in-depth accident investigations, injury mechanism analysis, and safety recommendation development through statistical analysis of macroscopic and in-depth accident databases. His VRU safety research since 2002 employs virtual reality techniques to model pre-collision behavior and evaluate active/passive safety systems, spanning accident databases, passive safety device development, and active safety effectiveness assessment. Scientific Awards: No specific awards, fellowships, or medals were documented in the source material. Advising and Grants: Supervised doctoral thesis: A. Badea (2016), "Parametrical Study of Pedestrian Accidents Using Multivariate Models" Coordinates practical training for ~20 students annually as Deputy Director of Training Academic Commission member for PhD Program in Mechanical Engineering Professor-coordinator of UPMRACING Formula Student team (70 students) Secured 42 competitive R&D projects (5 as Principal Investigator) and 38 non-competitive contracts (10 as PI), including 7 international projects across national frameworks (DPI, PROFIT, RENIT) and European programs (V Framework, ECTRI). Labs and Teams: Traffic Accidents Investigation Unit at INSIA-UPM UPMRACING Formula Student competition team (since 2005)

• Bayesian Networks
• Probabilistic Graphical Models
• Machine Learning
• +5 more

Rafael Rumí Rodríguez is a Professor in the Mathematics Department at the University of Almería, Spain, with extensive experience in probabilistic modeling and data analysis. He leads the 'Análisis de datos' research group and serves as Principal Investigator for multiple research projects, including the current 'Hacia una Inteligencia Artificial Probabilística Confiable (TOPAI-UAL)' (2023-2026). Dr. Rumí Rodríguez's research focuses on Bayesian networks and probabilistic graphical models , with applications spanning environmental science, ecology, agriculture, and education. His work includes developing methods for continuous distributions in hybrid Bayesian networks, flood risk assessment in Mediterranean regions, climate change impact modeling for Andalusian agriculture, and educational assessment analytics. He has created practical tools like the 'hcrBN' R package for hybrid Bayesian network applications. His publication record includes 43 articles , 2 books or chapters , 3 theses , and 31 conference papers , with an h-index of 16 (Scopus) and 15 (Web of Science). Many publications appear in Q1 journals, reflecting significant research impact across computer science, environmental science, and statistics. Scopus h-index: 16 Web of Science h-index: 15 Scopus i10-index: 27 Web of Science i10-index: 23 Dr. Rumí Rodríguez has secured substantial research funding throughout his career, including as Principal Investigator for the current TOPAI-UAL project (€120,100) and previous projects like the European AMIDST initiative (€323,490). His research group provides opportunities for students to engage in both theoretical advances and practical applications of probabilistic modeling, with strong connections to environmental and agricultural domains in the Mediterranean region.

• Fuzzy Data Analysis
• Statistical Analysis of Imprecise Data
• Random Sets
• +3 more

Ana Belén Ramos Guajardo is a Professor in the Department of Statistics and Operations Research and Mathematics Education at the University of Oviedo. She is affiliated with the GRINAT Research Group (Grupo de Investigación en Riesgos Naturales) and holds a doctorate from the University of Oviedo with her thesis titled "Contrastes de hipótesis tratamiento de la variabilidad y la imprecisión" (2011), supervised by Dr. Gil González Rodríguez, Dr. María Angeles Gil Alvarez, and Dr. Ana María Colubi Cervero. Her research focuses on statistical methodologies for imprecise data, particularly fuzzy data analysis, random sets, interval data analysis, and hypothesis testing. She has developed innovative approaches for distance-based statistical analysis, fuzzy clustering, and regression models for random intervals. Her work bridges theoretical statistics with practical applications in environmental sciences and other domains requiring analysis of imprecise measurements. Her publications reveal a strong focus on developing statistical methods for non-standard data types, with particular emphasis on random fuzzy sets and interval-valued data. She has contributed significantly to hypothesis testing frameworks for fuzzy data, distance metrics for imprecise data analysis, and computational methods for implementing these techniques. Her most recent work continues to advance the theoretical foundations while exploring practical applications. Ramos Guajardo has collaborated extensively with researchers in the fuzzy data analysis community, particularly with Ana Colubi, Gil González-Rodríguez, and María Asunción Lubiano. Her work has been published in top statistical journals including International Journal of Approximate Reasoning, Fuzzy Sets and Systems, and Information Sciences. She has advised or collaborated with numerous researchers in the field, contributing to the development of statistical fuzzy data analysis as a specialized subfield. Her methodological contributions have applications in environmental risk assessment, particularly through her affiliation with the Natural Risks Research Group at the University of Oviedo.