Find Academic Supervisors

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +6 more

Francisco Javier Escolano Ruiz is a Professor at the University of Alicante's Department of Computer Science and Artificial Intelligence, affiliated with the Higher Polytechnic School II. He holds a Doctorate in Computer Systems (1997) and a Graduate degree in Computer Science (1992) from the Polytechnic University of Valencia. His academic roles include teaching courses like Machine Learning, Discrete Mathematics, and Artificial Vision. Research Interests: Prof. Escolano's work spans computer vision, Bayesian inference, information theory, and assistive technology. He founded the Robot Vision Group (2001) and co-founded the Mobile Vision Research Lab (2012), developing Navilens—a breakthrough navigation system for visually impaired individuals using mobile vision. Since 2020, he has collaborated on COVID-19 data science initiatives, contributing to pandemic forecasting models. Publication Trends: Recent research focuses on graph theory applications in medical diagnostics (Alzheimer's detection), pandemic mobility modeling, and computer vision for accessibility. His team's work earned the XPRIZE Pandemic Response Challenge in 2022. Awards: First Prize, XPRIZE Pandemic Response Challenge (2022) Students & Grants: He has supervised 8 PhD students and mentored ELLIS doctoral candidates. Currently coordinates national projects including: Rewiring de Grafos Unificado y Escalable (2023-2027) Reconocimiento Estructural de Patrones con Teoría de la Información (2019-2021) Labs & Teams: Leads the Mobile Vision Research Lab (MVRLab) and collaborates with ELLIS Alicante on AI initiatives.

• Computer Science
• Artificial Intelligence
• Cryptography
• +5 more

Leandro Tortosa Grau is a Professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante's Higher Polytechnic School, where he has been teaching and conducting research since November 2007. He directs the Data Analysis and Visualization in Networks (ANVIDA) research group and is affiliated with the Institute of Computer Research at the University. His academic credentials include: Doctorate in Computer Engineering and Computing (2000) Computer Engineering degree (2000) Graduate in Mathematics from the University of Valencia (1988) Professor Tortosa Grau's research spans three distinct phases. Initially focused on parallel systems of linear equations during his doctoral studies (1995-2000), he then shifted to computer security and cryptography after joining the Security and Cryptology research group. Since late 2012, his research has centered on urban planning and urban networks from a computer science perspective, particularly using Self-Organizing Map (SOM) neural network models. In 2014, he founded the ANVIDA research group, which studies urban networks as complex networks and applies modern network theory to city modeling and visualization. His recent publications demonstrate a strong interdisciplinary approach, combining computer science with urban planning, traffic safety, and materials science. His work integrates deep learning, neural networks, and network analysis to address complex real-world problems in urban environments, transportation safety, and material science. Professor Tortosa Grau has supervised four doctoral theses to completion, all receiving the highest distinction of 'Sobresaliente Cum Laude.' He has coordinated multiple research projects including 'Analysis and visualization of the city as a multiple data network' (TIN2017-84821-P) and 'Analysis and visualization of data in complex networks' (TIN2014-53855-P), and contributed to the 'Data Analysis to Prevent the Spread of COVID-19' project (2020). He leads the ANVIDA research group which focuses on studying urban networks as complex networks, applying network theory to urban modeling and visualization. The group's work bridges computer science, urban planning, and data science to create innovative approaches for understanding and improving urban environments through computational methods.

• Soil Science
• Agricultural Statistics
• Environmental Science
• +6 more

Henar Urmeneta Martín-Calero is a Professor at the Department of Statistics, Computer Science and Mathematics, Public University of Navarra. She earned her PhD from the same university in 2003 with an Outstanding 'Cum Laude' distinction. Her work bridges soil science and advanced statistical methodologies. Education : PhD in Statistics and Mathematics (2003), Public University of Navarra Research Interests : Her research focuses on soil inorganic carbon dynamics under agricultural practices, irrigation impacts on soil health, and statistical methods for environmental and agricultural data. She also investigates stochastic processes, generalized Pólya urn models, and convergence theorems in Banach spaces. Publication Trends : Her recent work combines environmental science with statistical innovations, including studies on carbon sequestration in Mediterranean soils (2024), numerical integration techniques (2024), and historical sewage sludge effects on calcareous soils (2022). Earlier contributions involve theoretical mathematics, particularly stochastic circuits and convergence rates. Grants and Projects : She participates in projects like 'Balance de carbono inorgánico en suelos mediterráneos' (2023-2026) and 'Investigación y gestión de operaciones para la mejora de servicios de salud' (2016-2020). She has contributed to contracts evaluating soil properties and vineyard carbon management systems. Research Stays and Collaborations : Completed research stays at the University of Regina (2012) and UNED (2003). She collaborates with journals like Acta Applicandae Mathematicae and participates in academic courts for professor nominations.

Rafael Barea del CerroView profile

Researcher

• Additive Manufacturing
• Materials Science
• Ceramic Engineering
• +3 more

Rafael Barea del Cerro is a Researcher at Nebrija University's Higher Polytechnic School within the Department of Manufacturing Process Engineering, focusing on advanced materials and manufacturing processes. His academic foundation includes a PhD in Materials Science from Universidad Autónoma de Madrid (2004). Education: PhD in Materials Science, Universidad Autónoma de Madrid (2004). Thesis: 'Thermal Conductivity of Biphasic Ceramic Materials' supervised by Dr. P. Miranzo. Dr. Barea del Cerro's research centers on additive manufacturing, materials optimization, and data-driven engineering design. He investigates mechanical and thermal properties of advanced materials including magnesium alloys, ceramic composites, and metal deposition systems. His work integrates computational modeling with experimental validation to enhance manufacturing efficiency and material performance across industrial applications. Analysis of his 2020-2025 publications reveals dominant themes in additive manufacturing process optimization (laser-wire deposition, powder bed fusion), material behavior under extreme conditions (dynamic strain aging, compression testing), and sustainable thin-film engineering. Key methodologies include in situ diffraction, acoustic emission monitoring, and AI-driven shape optimization. No scientific awards are documented in available sources. Information regarding student supervision or research grants is not publicly specified in current academic profiles. His work appears primarily self-directed within institutional research frameworks. He actively contributes to the MOD3RN Nebrija Research Group, specializing in Material Optimization for Data Driven Design in non-linear engineering applications, where he develops computational and experimental approaches for next-generation manufacturing solutions.

• Operations Research
• Mathematical Programming
• Transportation Planning
• +7 more

Eva Barrena Algara is a Professor at the Department of Economics, Quantitative Methods, and Economic History at the University Pablo de Olavide. Her work bridges operations research, transportation planning, and mathematical optimization, with a focus on urban rail systems and network design. Her research interests include: Railway timetabling and scheduling under dynamic passenger demand Mixed-integer programming for transportation network optimization Multiplex network analysis in collective transportation systems Heuristic and metaheuristic algorithms for coordinated vehicle routing Waste logistics and humanitarian relief routing applications Her publications since 2013 demonstrate expertise in train unit scheduling, demand-adapted timetables, and network transferability analysis, often using Gröbner bases and adaptive algorithms. She collaborates with researchers like Gilbert Laporte and David Canca, with papers appearing in journals such as Computers & Operations Research and European Journal of Operational Research . Key application areas include metro systems, disaster response logistics, and waste collection optimization. She serves on the editorial board or as reviewer for transportation and operations research journals, and her work has been cited over 45 times. Her methodological contributions span exact formulations, biased-randomized heuristics, and stochastic modeling for time-dependent problems.

• Neuroimaging
• Neuropsychology
• Parkinson's Disease
• +3 more

Naroa Ibarretxe Bilbao is a Professor at the Department of Psychology, College of Health Sciences, University of Deusto. She earned her Psychology degree (2005) from the University of Deusto and a PhD in Medicine (2009) from the University of Barcelona, focusing on limbic brain changes in Parkinson's disease using MRI. She conducted predoctoral research at the University of Oxford (FMRIB) in 2007 and leads projects in the Neuropsicología de los trastornos médicos severos team at Deusto. Her research spans Neuroimaging in Parkinson's and multiple sclerosis Cognitive rehabilitation and brain connectivity Neuropsychological effects of prematurity Transcranial stimulation for creativity and language Quality of life in neurodegenerative diseases Her recent publications analyze fatigue networks in Parkinson's (2025), cortical thickness differences in preterm individuals (2024), and transcranial random noise stimulation effects on cognition (2023-2022). Awards include the 2010 Premio Lluis Barraquer (best thesis) and membership in Jakiunde Academy. She mentors students, including Eneritz Bengoetxea (2013 thesis on cognitive rehabilitation in schizophrenia), and directs the University of Deusto's Clinical Neuropsychology Master's program. Her work integrates MRI, neuropsychological assessment, and non-invasive brain stimulation across neurological and psychiatric populations.

JOSE ANGEL TABOADA GONZALEZView profile

Professor

• Computer Science
• Biomedical Engineering
• Data Engineering
• +3 more

Professor José Ángel Taboada González holds a position at the University of Santiago de Compostela (USC) within the Department of Electronics and Computing at the Higher Technical School of Engineering. He earned his doctorate from USC in 1996 with a thesis on multipatient monitoring systems in intensive care units using real-time distributed instrumentation. His research focuses on computer graphics, data engineering, and interdisciplinary applications of computational methods. Notable areas include biomedical engineering (e.g., patient monitoring systems), material science (nanomaterial synthesis), and environmental systems (e.g., agricultural mulches and energy optimization). His work bridges theoretical and applied domains, leveraging neural networks, data integration, and sensor technologies. Recent publications span diverse fields such as quantum physics (Bloch oscillations in 2D materials), clinical trials (phytodrug efficacy), and cultural heritage (medieval toponym recognition). His research group, COGRADE (Computer Graphics and Data Engineering), emphasizes data-driven solutions for complex systems. No scientific awards are explicitly cited, but his extensive publication record reflects significant contributions to multiple disciplines. He has advised doctoral research in biomedical systems and collaborates on projects involving sensor networks and environmental modeling. His work integrates engineering, computer science, and domain-specific challenges, exemplified by contributions to fusion energy diagnostics (ASDEX Upgrade tokamak) and sustainable agriculture.

Felix Luis Belzunce TorregrosaView profile

Professor

• Probability Theory
• Statistics
• Operations Research
• +3 more

Félix Belzunce Torregrosa is a Full Professor at the University of Murcia, affiliated with the Department of Statistics and Operational Research within the Faculty of Mathematics. He earned his doctorate from the University of Murcia in 1996 with a thesis on 'Ordering in Dispersion and Concentration of Truncated Distributions.' His research focuses on stochastic orders, reliability theory, actuarial science, and multivariate analysis. He has co-authored over 70 publications in top-tier journals such as Statistics & Probability Letters and Probability in the Engineering and Informational Sciences . Notable contributions include foundational work on stochastic comparisons, hazard rate ordering, and applications of stochastic orders in risk assessment. He has collaborated extensively with researchers like José-María Ruiz, Carolina Martínez-Riquelme, and Franco Pellerey. His work bridges theoretical probability with practical applications in finance, engineering, and actuarial science. Belzunce has led research groups such as 'Characterization, Ordering and Classification of Distributions,' and his studies on multivariate mixture models and nonhomogeneous processes have influenced reliability engineering and insurance mathematics. He has also contributed to developing methodologies for analyzing dependent random variables and optimizing maintenance policies in systems engineering.

José R. HerreroView profile

Associate Professor

• High Performance Computing
• Parallel Computing
• Dense Linear Algebra Algorithms
• +3 more

José R. Herrero is an Associate Professor in the Computer Architecture Department (DAC) at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona School of Informatics (FIB). His primary research area is High Performance Computing (HPC), focusing on parallel algorithms, dense linear algebra, and multicore processor optimization. He has held administrative roles including Vice-Dean for Academic Studies (2010–2013) and Vice-Dean for Institutional and International Relations (2013–2015) at FIB. Education: PhD in Computer Science from UPC (2006), Postgraduate in Training of University Professors (1997), and a Computer Science degree (1993). Teaching experience includes over 15 courses in Computer Architecture, Operating Systems, and Parallel Programming at both undergraduate and graduate levels. Research interests span HPC, parallel computing, and algorithm design. His work emphasizes optimizing matrix computations and linear algebra libraries for modern architectures. Notable contributions include advancements in sparse Cholesky factorization, task-parallel algorithms, and energy-efficient computing. Recognition includes UPC's Teaching Mention for Outstanding Quality (2009, 2014, 2019) and a Certificate of Merit for contributions to scientific computing workshops. He advises numerous PhD students and collaborates internationally, including visiting roles at GeorgiaTech and École Polytechnique de Montréal.

• Methodology of Behavioral Sciences
• Applied Statistics
• Data Mining
• +7 more

Rafael Jiménez López is a full Professor in the Department of Psychology at the University of the Balearic Islands (UIB), affiliated with the Faculty of Psychology. He specializes in the Methodology of Behavioral Sciences and is a member of the Data Analysis (GRAD) research group at UIB. Education: Bachelor’s in Psychology, University of the Balearic Islands, 1998 (Extraordinary Degree Award) PhD in Psychology, University of the Balearic Islands, 2003 Rafael Jiménez’s research focuses on advanced statistical methodologies and techniques, particularly data mining and statistical modeling, applied to behavioral, social, and health sciences. His work spans digital health interventions, evidence-based practice, and substance use. His recent publications (2022–2025) emphasize digital interventions for type 2 diabetes prevention (PREDIABETEXT), mental health in healthcare workers (PsyCovidApp), and the application of artificial neural networks in behavioral research. He has contributed significantly to the development and validation of research instruments in education and psychology. The trend in his recent articles shows a strong interdisciplinary focus, combining psychology, statistics, and digital health. His work increasingly applies machine learning and data mining to public health challenges, particularly in chronic disease prevention and mental health. He frequently collaborates on large-scale clinical trials and validation studies. Scientific Awards: Extraordinary Degree Award in Psychology, UIB, 1998 Rafael Jiménez has extensive teaching experience across undergraduate, master’s, and doctoral levels, teaching courses in applied statistics, data mining, evidence-based psychology, and survey design. He has supervised master’s and doctoral theses. He has participated in five national competitive research projects and several funded by the Balearic Islands Health Research Institute (IdISBa), demonstrating sustained grant acquisition. His academic leadership includes serving as vice-dean and head of studies at the Faculty of Psychology from 2007 to 2016. He is an active member of the Data Analysis (GRAD) research group at UIB, which focuses on applying statistical and data mining techniques to behavioral and health sciences. His collaborative network includes researchers in psychology, nursing, physiotherapy, and public health.

• Acoustics
• Finite Element Analysis
• Ultrasonics
• +7 more

Marc Arnela Coll is an Assistant Professor at the Engineering Department of La Salle Digital Engineering School, where he actively contributes to research in acoustics, vibration control, and sustainable building technologies. His work spans interdisciplinary domains, integrating engineering, environmental science, and human comfort in architectural contexts. His research interests focus on acoustics , finite element analysis , ultrasonics , and sustainable materials , with applications in noise and vibration reduction, sound insulation, and eco-friendly construction. He explores innovative solutions such as acoustic black holes, recycled concrete walls, and ultrasonic waste classification. The trends in his recent publications (2022–2025) reflect a strong emphasis on both theoretical and applied acoustics, with increasing integration of sustainability and human-environment interaction. His work appears in high-impact journals such as Applied Acoustics , Waste Management , and Chaos, Solitons and Fractals , covering topics from urban soundscapes to biomedical voice modeling. Scientific Awards: No scientific awards listed in the provided text. Advising and Grants: While no formal students are listed, Marc Arnela Coll leads and participates in multiple funded research projects. He serves as Principal Investigator (PI) for projects such as Bettair V and Aria , and as a key researcher in initiatives like ABHSSYS and Inhabiting Gaudí . These projects are supported by internal grants, research contracts, and collaborative agreements, reflecting strong institutional and interdisciplinary support. Labs and Teams: He is a core member of the Human-Environment Research group at La Salle Digital Engineering School, collaborating closely with researchers such as O. Guasch, R. M. Alsina-Pagès, and M. Freixes Guerreiro. His work is deeply embedded in team-based, project-driven research environments focusing on acoustic innovation and sustainable design.

• Advanced Statistical Methodologies
• Data Mining
• Advanced Statistical Modeling
• +4 more

Rafael Jiménez López is a Full Professor in the Department of Psychology at the University of the Balearic Islands (UIB), specializing in Methodology of Behavioral Sciences. He has extensive teaching experience across undergraduate, master's, and doctoral programs, focusing on applied statistics, data mining, and evidence-based psychology. Previously, he served as Vice Dean and Head of Studies at the Faculty of Psychology from May 2007 to October 2016. Education: Psychology Degree from UIB (1998), awarded the extraordinary degree prize PhD in Psychology from UIB (2003) Dr. Jiménez's research centers on advanced statistical methodologies and data mining techniques applied across various fields. His work emphasizes developing and applying sophisticated statistical models to extract meaningful patterns from complex datasets. He has particular expertise in applying these methods to healthcare research, educational assessment, and behavioral science. His methodological contributions help bridge the gap between theoretical statistics and practical applications in substantive research areas. His recent publication record demonstrates a strong focus on applying data science techniques to healthcare interventions, particularly diabetes prevention (PREDIABETEXT project), as well as educational research and evidence-based practice. The work shows integration of traditional statistical methods with modern data mining approaches, often in collaborative, interdisciplinary research teams. Scientific Awards: Extraordinary degree prize for Psychology degree Dr. Jiménez actively supervises thesis work at the doctoral level and has directed numerous master's and bachelor's theses. His teaching portfolio includes advanced statistics, data mining, and evidence-based psychology courses. He has participated as a researcher in 5 national competitive research projects and several projects awarded by IdISBa (Balearic Islands Health Research Institute), demonstrating strong grant acquisition capabilities. He is a member of the Data Analysis (GRAD) research group at UIB, a consolidated R&D&I structure focused on advanced statistical methodologies and their applications across various disciplines. This group provides a collaborative environment for methodological innovation and interdisciplinary research.

Gilles SchaefferView profile

Research Professor

• Combinatorics
• Algorithmics
• Enumerative Topology
• +3 more

Gilles Schaeffer is a Senior Researcher at CNRS and Professor at École Polytechnique, where he served as Director of the Computer Science Laboratory (LIX) from 2019-2025. He leads the Combinatorial Models group within the Combinatorics and Computer Algebra division. His research spans combinatorial methods including map enumeration, random discrete structures, and compact data representations, with applications in algorithmics, topology, and statistical physics. He has supervised PhD students on topics ranging from combinatorial maps to mesh compression algorithms. Schaeffer secured an ERC Starting Grant for the ExploreMaps project (2008-2013) and coordinated the GeoComp research initiative. He serves on editorial boards for Combinatorial Theory, Annales de l'Institut Henri Poincaré D, and PuMA journals.

• Behavioral economics
• Decision theory
• Bounded rationality
• +4 more

Jose Apesteguia is an ICREA Research Professor at the Department of Economics and Business , Universitat Pompeu Fabra (Barcelona). His research bridges behavioral economics and decision theory , focusing on bounded rationality and stochastic choice modeling. PhD in Economics (Public University of Navarra, 2001) Postdoctoral work at University of Bonn Academic career at UPF since 2006 His work examines how individuals deviate from classical rationality through random utility models , reference dependence , and sequential decision rules . Articles in journals like Econometrica and Journal of Political Economy analyze the computational and empirical foundations of behavioral heterogeneity. Recent studies include air pollution's impact on adolescent attention and stochastic representative agent models . Collaborations span Miguel A. Ballester, Albert Costa, and Jörg Oechssler across economics, psychology, and business domains.

• Algorithms
• Data Structures
• Combinatorics
• +9 more

Conrado Martinez Parra is a Professor in the Department of Computer Science at the Faculty of Computer Science, Universitat Politècnica de Catalunya (UPC). He is a core member of the ALBCOM research group, which focuses on Algorithmics, Bioinformatics, Complexity, and Formal Methods. Affiliation : Department of Computer Science, Faculty of Computer Science (FIB), UPC Research Group : ALBCOM - Algorísmia, Bioinformàtica, Complexitat i Mètodes Formals Email : conrado@cs.upc.edu ORCID : 0000-0003-1302-9067 Researcher ID : G-4629-2015 His research spans theoretical computer science with a strong emphasis on the design and analysis of algorithms and data structures. His work includes average-case analysis of algorithms, combinatorial generation, probabilistic methods in algorithmics, and applications in information retrieval and data stream processing. He has extensively studied multidimensional data structures such as quadtrees, K-d trees, and skip lists, analyzing their performance under various query models including partial match and orthogonal range searches. His recent publications reveal a sustained focus on algorithmic efficiency, sampling techniques, and probabilistic modeling in data structures. Trends indicate a deep engagement with randomized algorithms, unbiased estimation, and cache-efficient selection methods, reflecting both theoretical rigor and practical applicability in modern computing environments. Scientific Contributions Extensive publication record spanning over three decades, from 1989 to 2024. Active in major algorithmic conferences such as ANALCO, AofA, and AAAI. Contributions to foundational algorithm analysis including Hoare’s FIND, Quickselect variants, and deletion in binary search trees. Collaborative research with prominent figures in theoretical computer science across Europe. Professor Martinez Parra has advised or collaborated with several doctoral students, including Gustavo Lau, whose thesis on partial match queries he supervised. He has participated in numerous competitive R&D projects funded by national and regional programs, focusing on large-scale information processing and graph-based computing models. His work is supported by long-standing grants from Spanish and Catalan research councils. He is affiliated with the ALBCOM research group, a leading team in algorithmic research at UPC, contributing to both theoretical advances and practical implementations in combinatorics and data structure optimization.