Manuel Febrero-Bande is a Professor of Statistics and Operations Research at the University of Santiago de Compostela, affiliated with the Department of Statistics, Mathematical Analysis and Optimization under the Faculty of Mathematics. He earned his PhD in 1995 with a thesis on time series modeling. His research focuses on functional data analysis, time series, bootstrap methods, and computational statistics, with applications in environmental control, finance, and health. He co-developed the R package fda.usc , a key tool in functional data analysis. Febrero-Bande has coordinated academic programs like the Master in Statistical Techniques and the Doctoral Program in Statistics and Operations Research. His work emphasizes statistical methodology and interdisciplinary applications, with over 30 peer-reviewed publications and contributions to software development. Key research trends include functional data classification (e.g., Bitcoin address analysis), variable selection in additive models, and goodness-of-fit testing for functional linear models. He has explored applications in fields like forensic science (post-mortem interval estimation) and malaria transmission dynamics. His collaborative projects span institutions in Spain and internationally, reflecting a commitment to both theoretical and applied statistics. He has advised numerous students, though explicit student names are not listed. Awards are not mentioned, but his contributions to statistical software (e.g., fda.usc) and leadership in academic programs highlight his impact. His research often addresses real-world problems, integrating computational methods with statistical rigor.
Dr. Antonio Muñoz San Roque is an Ordinary Professor at the Institute of Technological Research (IIT), affiliated with the Comillas Pontifical University, where he also serves as Director of the ICAI School of Engineering since 2018 and previously as Director of IIT since 2008. He teaches in the Department of Electronics, Automation, and Communications and conducts research in Intelligent Systems, focusing on the application of Artificial Intelligence and Machine Learning to industrial monitoring, time series forecasting, and electricity market analysis. His research interests include Machine Learning , Time Series Forecasting , Industrial Process Diagnosis , and Electricity Market Optimization . He applies advanced data analysis techniques to problems in energy systems, predictive maintenance, and smart grids, often combining statistical modeling with domain-specific engineering knowledge. The most recent publications highlight a strong trend in functional data forecasting , neural network interpretability , and energy market modeling . His work spans high-impact journals such as Energy , Applied Soft Computing , and IEEE Transactions on Power Systems , demonstrating consistent contributions to both theoretical methodologies and real-world industrial applications. Director of the award-winning work in the 'Axpo Iberia Award for the best Final Year Project 2023-24' He has advised numerous PhD students, including G. Mestre, J. Portela, and P. Moreno Alonso, and leads multiple industry-funded research projects with companies such as Endesa and Enel. His work integrates academic rigor with practical implementation, particularly in forecasting models for electricity markets and AI-driven industrial diagnostics. He is also involved in academic dissemination through seminars and conference organization, and has contributed to the development of training programs in machine learning for industry partners.
Manuel Gil Pérez is an Associate Professor in the Department of Information and Communication Engineering at the University of Murcia, Spain. His research focuses on cybersecurity, intrusion detection systems, trust management, and privacy-preserving data sharing in dynamic scenarios. University of Murcia (Faculty of Computer Science) Researcher in EU H2020/FP7 projects Key research areas include: Cyber deception frameworks for threat actor profiling Trust management in 5G/6G networks Decentralized federated learning security Privacy-preserving healthcare data systems Context-aware security mechanisms Recent publication trends highlight: Integration of knowledge graphs for threat analysis Moving target defense in distributed systems Standardization of trust frameworks for next-gen networks Adaptive risk assessment models Scientific contributions include: Design of antifragile deception systems Development of Fedstellar DFL platform Pre-standardization of reputation-based trust models Hardware fingerprinting for IoT security
Armando Caballero Rua is a Professor of Genetics at the University of Vigo , affiliated with the Faculty of Biology and the Marine Research Center of the University of Vigo . His work focuses on evolutionary genetics and conservation biology. PhD in Genetics from Universidad Complutense de Madrid (1990) ResearchGate profile showcasing 192 publications and 24,247 reads His research interests include: Evolutionary genetics of inbreeding and genetic diversity Conservation genetics and population viability analysis Quantitative trait modeling using molecular markers Effective population size estimation via linkage disequilibrium methods Recent publications (2023-2025) demonstrate expertise in: Genetic purging mechanisms in Drosophila Population structure effects on Ne estimation Genomic consequences of deleterious mutations Conservation strategies for subdivided populations Software Contributions: Developer of METAPOP and GON for population genetic analysis and conservation management.
Miguel Arenas Busto is a Professor at the University of Vigo, Spain, affiliated with the Faculty of Biology and the Department of Biochemistry, Genetics and Immunology. He leads the Computational Molecular Evolution (CME) Team within the Biomedical Research Center at the Vigo campus. His career includes positions as Principal Investigator under the Ramón y Cajal program (2017-2022), postdoctoral research at prestigious institutions including the University of Bern and the Centre for Molecular Biology 'Severo Ochoa', and a PhD in Genetics from the University of Vigo completed cum laude in 2010. PhD in Genetics, University of Vigo (2010), Cum Laude PostDoc, University of Bern (2010-2012) PostDoc, Centre for Molecular Biology 'Severo Ochoa' CSIC (2012-2015) Principal Investigator, IPATIMUP/i3S, University of Porto (2015-2017) Principal Investigator (Ramón y Cajal), University of Vigo (2017-2022) Professor PCD, University of Vigo (2022-2023) Professor TU, University of Vigo (2023-Present) Arenas specializes in the evolutionary analysis of genetic data at molecular and population levels. His research encompasses Population Genetics, Molecular Evolution, Molecular Adaptation, Genetic Diversity, Phylogenetics, Phylogenomics, and the evolution of structure and function of biological macromolecules. He has developed computational methods and software tools for molecular evolution analysis, including Recodon, NetRecodon, ProteinEvolver, and ProtASR. His recent publications reveal a strong focus on protein evolution with structural constraints, substitution model development, ancestral sequence reconstruction, and viral evolution (particularly HIV-1 and SARS-CoV-2). A significant trend across his work is the integration of protein folding stability into evolutionary models, demonstrating how structural constraints shape molecular evolution. His research bridges computational biology with experimental validation, with applications spanning infectious disease dynamics, molecular adaptation, and phylogenetic inference. Thesis Award (best Thesis of University of Vigo, 2010) Group Leader Junior of Computational Molecular Evolution Group (CINBIO, 2021) Group Leader of Computational Genetics and Genomics Group (IPATIMUP/I3S) EMBO Fellowship (2014) Ramón y Cajal Grant from Spanish Government (2017-present) Arenas has supervised numerous undergraduate, graduate, and PhD students, with a focus on computational approaches to evolutionary questions. His research has been funded by multiple agencies including the Spanish Ministry of Economy and Competitiveness, Xunta de Galicia, Fundación BBVA, The Foundation for Science and Technology, European Molecular Biology Organization, and EU Framework Programs. He serves as Associate Editor for several journals including Genes and Frontiers in Ecology and Evolution, and as a reviewer for numerous high-impact journals and research agencies across Europe. He directs the Computational Molecular Evolution (CME) Team at the University of Vigo, which focuses on developing computational methods for evolutionary analysis, with particular emphasis on protein evolution constrained by structural stability. The lab maintains active collaborations with research groups across Europe and the United States, participating in international networks including the Society for Molecular Biology and Evolution and the Spanish Society of Bioinformatics and Computational Biology.
