جست‌وجوی استاد و پژوهشگر

• Deep Learning
• Machine Learning
• Time Series Prediction
• +۱ مورد دیگر

Alejandro Polo Molina is a Predoctoral Researcher at the Intelligent Systems Area of the Instituto de Investigación Tecnológica (IIT), part of Comillas Pontifical University's Higher Technical School of Engineering. He joined IIT in September 2022 after completing advanced degrees in data science and holding industry positions at Repsol and Accenture. His academic credentials include a Bachelor's degree in Mathematics from the University of Granada (2020), a Master's in Big Data and Advanced Analytics from Comillas Pontifical University (2021), and a Master's in Big Data & Visual Analytics from UNIR (2021). Bachelor of Mathematics, University of Granada (2020) Master in Big Data and Advanced Analytics, Comillas Pontifical University (2021) Master in Big Data & Visual Analytics, International University of La Rioja (2021) Polo Molina's research spans Deep Learning, Machine Learning, Time Series Prediction, and Graph Machine Learning, with applications in healthcare analytics, automotive safety, and theoretical neural network guarantees. His work emphasizes interpretable AI models for clinical decision support and physical system modeling, particularly through Kolmogorov-Arnold Networks for certified monotonicity in ethical AI applications. He develops practical solutions for time-series forecasting in energy markets and patient mobility analysis using wearable sensors. His publication record (2023-2025) reveals strong interdisciplinary trends, bridging machine learning with biomedical engineering and automotive safety. Key themes include clinical condition prediction for chronic patients using wearable data, interpretable thoracic injury modeling in car crashes, and mathematical certification frameworks for neural network behavior. His work consistently connects theoretical guarantees with real-world applications in high-stakes domains. Polo Molina has secured research funding through multiple industry and government projects, including Endesa Medios y Sistemas SL for residual demand curve forecasting, Innomerics S.L. for green hydrogen plant methodologies, and the Spanish Ministry of Science for chronic patient movement analysis. These projects demonstrate his ability to translate academic research into industrial solutions while maintaining rigorous scientific standards. As an emerging researcher at IIT, he actively contributes to the Intelligent Systems group through conference presentations at venues like IRCOBI Europe and SEIO, invited seminars on neural network theory, and collaborative projects spanning healthcare, energy, and automotive sectors. His trajectory shows rapid progression from industry data science roles to cutting-edge academic research with significant practical impact.

• Diagnostic Imaging
• Radiology
• Medical Imaging

Hector Lajusticia Andres serves as an Associate Professor in the School of Medicine at the University of the Balearic Islands (UIB), actively teaching Diagnostic Imaging (course code 23023) for the Medical Degree program in Mallorca. His current responsibilities span academic years 2024-25 and 2025-26, with continuous instruction in this subject documented over the past five years. His academic focus centers on Diagnostic Imaging , a critical discipline within clinical medicine that utilizes advanced imaging technologies—including X-ray, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound—for disease diagnosis and treatment monitoring. This field demands expertise in interpreting visual data to guide precise clinical interventions, directly impacting patient care pathways in modern healthcare systems.

• Optics
• Physics
• Biomedical Optics
• +۳ مورد دیگر

Arturo Vicente Jaen is a predoctoral researcher at the University of Murcia, affiliated with the Department of Physics under the Faculty of Chemistry. He is a member of the Optics Laboratory research group, focusing on optical instrumentation, vision science, and computational methods in biomedical imaging. His research spans interdisciplinary areas combining Optics and laser scanning Machine learning for visual correction systems Biomedical optics and volumetric data reconstruction His recent work demonstrates expertise in GPU optimization, neural networks for gaze estimation, and development of OCT data processing tools. The research aligns with applications in ophthalmology and adaptive optical systems.

• Pediatrics
• Clinical Research
• Neurodevelopmental Disorders
• +۷ مورد دیگر

Ana Checa Ros is a Spanish Associate Professor at CEU Cardenal Herrera University's Department of Medicine and Surgery, with dual expertise in clinical pediatrics and biomedical research. Holding a Cum Laude PhD in Medicine from the University of Granada (2017) and a six-year research grant from CENAI (2023), she leads the emerging Cardiorenal and Metabolic Diseases research group alongside Dr. D'Marco. Medical Degree: University of Granada (End of Degree Award, 2011) PhD: Cum Laude, University of Granada (2017) Postdoctoral Research: Aston University (2019-2021) Her research focuses on melatonin's anti-inflammatory/antioxidant properties, particularly in neurodevelopmental disorders and chronic kidney disease. She has coordinated clinical trials like NCT04076410 for photosensitive epilepsy and participated in the H2020 DYNAHealth project investigating maternal nutrition effects on neurodevelopment. Scientific contributions include 15+ JCR-indexed publications (2020-2025) spanning cardiorenal diseases, ADHD neuroimmunology, and metabolic disorders. Her work combines clinical practice with translational research, maintaining active teaching roles since 2012 and serving as guest editor for journals like Healthcare. End of Degree Award (University of Granada, 2011) Cum Laude Doctoral Thesis (University of Granada, 2017) CENAI Six-Year Research Grant (2023)

David Ryan Glowackiمشاهده پروفایل

استاد پژوهشی

• Virtual Reality
• Molecular Dynamics
• Drug Discovery
• +۷ مورد دیگر

David Ryan Glowacki is a cross-disciplinary Research Professor at Universidad de Santiago de Compostela, specializing in the intersection of virtual reality, molecular dynamics, and computational chemistry. He is the founder of the Intangible Realities Laboratory (IRL), a research group working at the immersive frontiers of scientific, aesthetic, computational, and technological practice. His educational background includes a B.A. from the University of Pennsylvania (2003), an M.A. in cultural theory from Manchester University (2004), and a Ph.D. in molecular physics from Leeds University (2008). His diverse academic training spans chemistry, mathematics, philosophy, comparative literature, and religions, reflecting his interdisciplinary approach. Glowacki's research focuses on interactive virtual reality applications for scientific simulation and visualization, particularly in molecular dynamics and drug discovery. He has pioneered the development of interactive molecular dynamics in virtual reality (iMD-VR) as a tool for flexible substrate and inhibitor docking, reaction network exploration, and computational drug design. His work bridges computer science, nanoscience, aesthetics, and cultural theory, creating innovative approaches to scientific problems. An analysis of his recent publications reveals a strong trend toward applying virtual reality technologies to solve complex problems in computational chemistry and drug discovery. His work on iMD-VR has been particularly influential, demonstrating how immersive technologies can enhance molecular modeling, protein-ligand binding studies, and educational approaches in chemistry. He has made significant contributions to understanding reaction networks, SARS-CoV-2 protease inhibition, and the application of machine learning to molecular systems. Royal Society Research Fellowship Philip Leverhulme award ERC grant SIG-CHI best paper award Glowacki has secured substantial research funding through prestigious grants including an ERC grant and Royal Society Fellowship, enabling his innovative work at the intersection of science and technology. His Narupa framework provides an open-source, multi-person VR environment that has been applied across multiple research domains. While specific student advising isn't detailed in the provided information, his educational publications suggest active engagement in teaching computational chemistry through innovative VR approaches. As founder of the Intangible Realities Laboratory, Glowacki leads a team exploring how immersive technologies can transform scientific practice. The lab's work spans from fundamental molecular dynamics research to applications in drug discovery and mental health, demonstrating the broad impact potential of interactive VR technologies. Their citizen science approach to distributed VR experiments represents a novel methodology for conducting large-scale psychological research.

Manuel Mucientes Molinaمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Manuel Mucientes Molina is a Full Professor at the Research Center on Intelligent Technologies (CiTIUS) within the University of Santiago de Compostela . His research focuses on Artificial Intelligence , particularly in Computer Vision and Machine Learning , with applications in object detection, process mining, and healthcare diagnostics. Research Areas : Machine learning, Computer vision, Process mining, Deep learning, AI for healthcare. Projects : Protonterap-IA (2025), AZOR (2024), RAI4P (2021), eXplica-IA (2018), DronePlan (2014), SoftLearn (2012). Publications highlight advancements in few-shot object detection, small object tracking, and AI-driven conformance checking. Notable collaborations include work on X-ray vision systems and medical mask detection in operating rooms. Awards : Best Student Paper Nomination (2015), Runner-up best industry-oriented paper award (2008). Teaching includes courses on Statistical Learning, Deep Learning, and Automata Theory at the M.Sc. and B.Sc. levels.

Sergio Luna Lozanoمشاهده پروفایل

پژوهشگر

• Visual Arts
• Contemporary Art
• Photography
• +۴ مورد دیگر

Sergio Luna Lozano is a contemporary visual artist and researcher affiliated with the Polytechnic University of Valencia, where he graduated in Fine Arts (2003) and completed his doctoral thesis on synthetic faces in contemporary art (2020, Cum Laude). His work explores representation models through painting, photography, film, and digital platforms. Education: MFA, Polytechnic University of Valencia (2003); PhD, Polytechnic University of Valencia (2020) Research focuses on synthetic faces, digital/analog representation systems, optical devices, and identity construction. His artistic practice bridges disciplines like photography, film, and internet culture, often questioning visual conventions and identity frameworks. Key exhibitions : Memories of the Future (2021), Phantoms (2021), Album (2017), Out of Focus (2014, as collaborative work with Yasmina Morán). His Composites series investigates facial averaging techniques from Francis Galton to digital morphing. Awards: 3CMCV Production Grant (2013), XXXVII Vila de Pego National Painting Prize (2013), X Virgen de las Viñas Cultural Award (2011) Works held in collections including DKV Collection, Ibercaja, and Real Academia de Bellas Artes de San Carlos. Collaborated with Yasmina Morán on projects like Out of Focus , manipulating Google Street View through fictional interventions.

• Computer Graphics
• Multimedia Computing
• Real-Time Visualization
• +۳ مورد دیگر

Dr. Celso Campos Bastos is a Full-Time Researcher in the Department of Computer Science at the University of Vigo's School of Computer Engineering. His work focuses on real-time artistic visualization techniques, particularly for plant species representation. PhD in Computer Science (University of Vigo, 2004) Research Group: SI6 Graphics and Multimedia Computing Group (Gig) Research interests span: Computer graphics and multimedia systems Scientific visualization methodologies Interactive rendering algorithms Botanical modeling applications

• Machine Learning
• Statistics
• Operations Research
• +۴ مورد دیگر

Jose Maria Matias Fernandez is a Full Professor in the Department of Statistics and Operations Research at the School of Industrial Engineering, Universidade de Vigo. His research spans machine learning, structured deformations in continuum mechanics, wind energy modeling, and mineral resource management. Doctorate from University of Santiago de Compostela (2003): Thesis on neural networks for regression/classification His work focuses on global relaxation methods for hierarchical structured deformations, asymptotic analysis of thin structures, and applications of machine learning to environmental and industrial problems. Recent publications (2023-2025) emphasize multiscale geometrical modeling and energy minimization in material science. He has contributed to interdisciplinary fields including: Wind power density estimation using support vector machines Heavy metal adsorption modeling in soils 3D laser scanning applications for slate/wood-pulp characterization Bayesian networks for risk assessment in mining and transportation His research group GESSMin specializes in sustainable mineral resource management. Key collaborations involve electrical engineering problems (e.g., plug-in vehicles' impact on grids) and astrophysical studies of planetary nebulae.

Jose A. Boludaمشاهده پروفایل

دانشیار

• Computer Vision
• Hardware Design
• Image Processing
• +۴ مورد دیگر

Dr. Jose A. Boluda is an Associate Professor in the Department of Computer Engineering at the University of Valencia's School of Engineering. He holds a B.S. in Physics (Electricity, Electronics and Computer Science, 1992) and a Ph.D. (2000) from the same institution. With 6 teaching quinquenios and 4 research sexenios, his academic career spans over two decades. His research focuses on: Computer vision hardware design Smart vision sensors and neuromorphic computing Reconfigurable architectures (FPGA) High-speed motion analysis and change-driven processing Biomimetic visual sensing strategies He has authored over 50 international publications and participated in 15 research projects. His publications predominantly explore: Event-based vision sensors Hardware-accelerated image processing Neuromorphic engineering applications Real-time systems for robotics and 3D scanning Low-power circuit design for computer vision Awards include: Fernando Sapiña Award 2023 for Valencian teaching materials Fernando Sapiña Award 2021 for English teaching materials Fernando Sapiña Award 2021 for Valencian teaching materials He has directed 2 doctoral theses and supervised multiple master's projects. Research includes international collaborations at the University of Virginia, University of Macedonia, and Universitat Jaume I. His lab focuses on developing novel vision sensors and processing architectures.

• Learning Analytics
• Artificial Intelligence in Education
• Educational Technology
• +۲ مورد دیگر

Pedro Manuel Moreno Marcos serves as an Associate Professor in the Department of Telematics Engineering at Charles III University of Madrid, where he maintains an active research profile in educational technology. His academic work bridges telecommunications engineering with data-driven educational innovation, focusing on the practical implementation of analytics in real-world learning environments across Spanish and European higher education institutions. His research centers on learning analytics and artificial intelligence applications in education, with particular expertise in student behavior modeling, dropout prediction, and AI-enhanced learning environments. Key contributions include developing predictive models using multi-source data, creating tools like Statoodle for cheating prevention in LMS platforms, and pioneering human-centered generative AI applications through projects like GENIE Learn. His methodological approach combines machine learning algorithm evaluation with institutional ethnography to address adoption challenges in learning analytics. Analysis of his 15 most recent publications reveals an accelerating focus on generative AI's educational potential since 2023, with increasing attention to ethical implementation frameworks and micro-credentialing systems. His work consistently addresses practical barriers in learning analytics adoption while maintaining strong connections to Spanish higher education contexts through projects like PALABRIA-CM-UC3M. No scientific awards were documented in the provided materials. While specific student supervision details aren't disclosed, his research methodology frequently involves multi-institutional collaborations across European higher education settings. Current projects indicate active grant funding for initiatives including SHEILA (Support Higher Education to Integrate Learning Analytics) and PALABRIA-CM-UC3M, though specific grant amounts and durations aren't specified in the source text. Dr. Moreno Marcos leads research within the university's learning analytics ecosystem, contributing to frameworks like SHEILA that inform institutional policy. His work with telepresence classrooms and IoT-enabled educational scenarios demonstrates engagement with emerging technology infrastructure, while his focus on multi-source data integration suggests leadership in developing comprehensive analytics platforms for complex educational environments.

• Artificial Intelligence
• Multi-Agent Systems
• Computer Science Education
• +۳ مورد دیگر

Miguel Rebollo Pedruelo is a researcher at the Polytechnic University of Valencia, specializing in Computer Science and Artificial Intelligence. He has published extensively on multi-agent systems, educational technology, and social media applications in teaching. Research Focus : AI for education, model-driven development, and social network analysis. Key Contributions : Pioneering consensus algorithms for MAS, transmedia educational frameworks, and sentiment analysis tools. His work bridges artificial intelligence with pedagogical innovation, evidenced by 15+ peer-reviewed publications (2016-2024) and editorial roles in conferences like JENUI and CAEPIA. He has directed three doctoral theses and co-authored 20+ collective works.

• Neuroscience
• Clinical Neurology
• Cognitive Neuroscience
• +۷ مورد دیگر

Bryan Strange is a Professor at the Department of Photonic Technology and Bioengineering, Universidad Politécnica de Madrid (UPM), and a member of the Center for Biomedical Technology (CTB) since 2011. His research focuses on neuroscience, particularly in memory mechanisms, neurodegenerative diseases, and neuroimaging techniques. Neuroscience Clinical Neurology Cognitive Neuroscience Neuroimaging Neurodegenerative Diseases Medical Imaging His work explores hippocampal-amygdala interactions in emotional memory, deep brain stimulation (DBS) for psychiatric disorders, and neuroimaging biomarkers for Alzheimer's disease and aging. Recent studies address superagers' resistance to age-related brain changes, genetic factors in hippocampal atrophy, and advanced MEG/CT/MRI methodologies. Analysis of his 15 most recent publications reveals trends in neuroimaging (MRI, MEG, CT), DBS applications, and computational psychiatry, with subfields spanning dementia risk prediction, emotional memory modulation, and cortical connectivity modeling. His contact email is bryan.strange@upm.es . He has not received explicit awards or honors in the provided data and has no listed advisees.

• Economics of Longevity
• Industrial Systems Diagnostics
• Prognostics
• +۳ مورد دیگر

Pablo Calvo Báscones serves as an Assistant Professor at Comillas Pontifical University's Faculty of Economics and Business (ICADE) within the Department of Quantitative Methods, teaching data science and analytics courses since 2022 after 9 years of cumulative university service. His academic credentials include: PhD in Industrial Engineering (Comillas Pontifical University, 2022) Master's Degree in Industrial Engineering (Comillas Pontifical University) Electromechanical Engineering degree (Comillas Pontifical University) Research focuses on Economics of Longevity and Data-driven Industrial Diagnostics , integrating digital twin ecosystems with machine learning for anomaly detection. His methodology bridges industrial prognosis (2020-2023) and socioeconomic frameworks like the Senior Economy Tracker (2024), demonstrating evolution from component-level diagnostics to macroeconomic policy tools. Recent publications reveal interdisciplinary expansion into energy resource assessment and demographic transition metrics while maintaining core expertise in behavioral pattern recognition for industrial systems. Scientific recognition includes: Distinción Honorífica a la mejor Tesis Doctoral en Ingeniería (2024) for "Inclusive methodologies for anomaly detection and prognosis of industrial systems" Secured research funding from EU Horizon 2020 programs and private sector partners including Airbus and Leiden University Medical Centre. Supervises Final Degree Projects while teaching Data Analysis and Visualization courses. Maintains active industry collaboration through the Smart Management for Sustainability research group and international engagement as Visiting Professor at TU Delft (December 2023).

• Architecture
• Urban Studies
• Archaeology
• +۲ مورد دیگر

Federico Luis del Blanco Garcia is an Assistant Professor at the Universidad Politécnica de Madrid , affiliated with the Department of Architectural Construction and Technology. He is actively involved in research groups focused on Architectural Heritage and Architectural Computing and Design for Construction , and contributes to the Comprehensive Home Automation Center (CEDINT) as a member. Research Interests: Architecture, Urban Studies, Archaeology, Building and Construction, and Visual Arts and Performing Arts. Professional Roles: Assistant Professor, Research Group Member, Innovation Group Coordinator, and Research Center Member.