Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.
Pere-Pau Vázquez is an Assistant Professor in AI for Visual Computing at the Computer Vision Lab, TU Wien, Austria . Previously, he held academic positions at the ViRVIG Group and Facultat d'Informàtica de Barcelona (UPC) , where he taught courses in Programming, Computer Graphics, and Visualization for over 20 years. His research focuses on Information Visualization, Scientific Visualization, Medical Data Visualization, Molecular Visualization, and AI applications to Visual Computing . Current Teaching : Data Visualization, Fast Realistic Rendering, Information Visualization, Medical Images, Scientific Visualization, Virtual Reality, and 3D Medical Visualization. Former PhD Students : Elena Molina, Alexandra Cortez, Jesús Díaz, Pedro Hermosilla, Eva Monclús. His scientific awards include the Best PhD Thesis Award (UPC, 2003), Best Student Paper Award (SPIE, 2012), and Best Paper Award (International Conference on Computer Graphics Theory and Applications, 2013). Recent publications explore AI integration in biomedical visualization, molecular data analysis, and interactive techniques for volume rendering. He serves on the EuroGraphics Executive Board as Secretary and is active in steering committees for EuroVis and Visual Computing for Biology and Medicine . His work bridges Computer Graphics, Artificial Intelligence, and Human-Computer Interaction , with applications in medical and molecular data analysis.
Roger Uceda Molera is an Associate Professor at the Universitat Politècnica de Catalunya (UPC) in the Department of Mechanical Engineering, affiliated with the Barcelona Higher Technical School of Industrial Engineering (ETSEIB). He is a member of the DigiFACT research group, focusing on advanced manufacturing technologies. His expertise spans entrepreneurship, 3D scanning, additive manufacturing, 3D printing, Industry 4.0, IoT, and mechanization. He has contributed to over 25 research activities, including articles, patents, and awards. Roger’s research emphasizes innovative additive manufacturing techniques, such as hybrid multi-material 3D printing and applications in medical prototyping. His work includes developing materials for concrete additive manufacturing and optimizing ceramic sintering processes. He has collaborated with companies like BCN3D Technologies and led projects funded by public-private partnerships. Key awards include the 2019 Premi Nacional al Partenariat Publicoprivat en R+I and the World to NYC Global Industry Challenge (W2NYC). He holds a patent for extrusion systems in cementitious material manufacturing. His research group, DigiFACT, drives advancements in digital factory technologies and industrial innovation.
Prof. Valerio Pruneri is an ICREA Professor and Group Leader at the Institute of Photonic Sciences (ICFO), holding the Corning Inc. Chair in Optoelectronics. He leads a research group focused on quantum optics, nanophotonics, and biomedical imaging. His academic background includes a PhD in Laser Physics from the University of Southampton (UK). Research interests span quantum communication technologies, plasmonic sensors, and nanomaterials for optical applications. Recent advancements include work on quantum key distribution systems, graphene-based devices, and super-sensitive phase imaging techniques. Articles highlight innovations in quantum-enhanced imaging, integrated photonic circuits, and hyperbolic metamaterials. His team collaborates on EU projects like NANO-GLASS ITN and FLIGHT, with a strong emphasis on translational research. Over 50 students and researchers are advised, many funded by national and international grants (e.g., Agencia Estatal de Investigación, CELLEX Foundation). Key lab facilities include state-of-the-art cleanrooms and optical characterization tools.
Mariano Cabezas is a researcher in medical imaging and computer vision, currently affiliated with Macquarie University and as an affiliate at the University of Sydney . His work focuses on automating brain MRI analysis for pathologies like multiple sclerosis, Alzheimer's disease, and tumors, with additional contributions to UAV image analysis. PhD in Computer Science (2013), University of Girona MSc in Automation, Computation, and Systems (2010), University of Girona BSc in Computer Science (2009), University of Girona Research Interests : Specializes in magnetic resonance imaging , lesion detection , deep learning , and image processing , with applications in multiple sclerosis , hearing loss , and UAV-derived ecological data . His recent work includes federated learning frameworks for cross-site MS lesion segmentation and pseudo-labeling techniques for longitudinal brain volume estimation. Publication Trends : Over the past five years, his research has emphasized federated learning (4 articles), lesion segmentation (9 articles), and UAV image analysis (3 articles), with a strong focus on clinical validation and cross-institutional collaboration. Labs & Collaborations : Contributed to the NIC-VICOROB group at the University of Girona and maintains affiliations with the Research Institute of the Hospital Vall d'Hebron (VHIR) in Barcelona and Macquarie University in Sydney. Actively develops open-source tools hosted on GitHub.
Julian Fierrez is a Full Professor at the School of Engineering, Universidad Autonoma de Madrid. With an h-index of 74 and over 20,000 citations, his work spans biometrics, signal/image processing, artificial intelligence, and human-computer interaction. Key research areas include: Biometric anti-spoofing and DeepFakes detection Mobile and behavioral biometrics Bias/fairness in AI systems Biometric applications in e-health and education Security in multimodal biometric systems His recent publications show strong focus on deep learning applications for biometric security, with specific subfields including fake detection, keystroke authentication, facial analysis for Parkinson detection, and privacy-preserving AI. He serves as Associate Editor for multiple IEEE and Elsevier journals. Scientific distinctions include: IAPR Young Biometrics Investigator Award (2017) Miguel Catalan Award to Best Researcher under 40 (2017) EURASIP Best PhD Award (2012) EBF European Biometric Industry Award (2006) Prof. Fierrez leads the BiDA Lab and supervises students like Ruben Tolosana and Aythami Morales. Current projects include BBforTAI (Biometrics and Behavior for Unbiased & Trustworthy AI) and PRIMA (Privacy Matters). He also contributes to standardization efforts in biometric evaluation.
Raul Sanchez Reillo is a Full Professor at Universidad Carlos III de Madrid (UC3M), affiliated with the Grupo Universitario de Tecnologías de Identificación (GUTI). His research focuses on biometric systems, mobile authentication, and security technologies. Key areas include presentation attack detection, vein recognition, and ECG biometrics. He leads projects involving smartphone-based biometric solutions, 3D printed markers, and standards development for biometric interoperability. Research interests span multiple modalities: fingerprint authentication, dynamic signature verification, gait recognition, and vascular biometrics. He emphasizes usability and accessibility in mobile environments, exploring ergonomics and user interaction challenges. His work integrates machine learning (transformers, RNNs) with hardware solutions like FPGA-based systems. Publications highlight innovations in spoofing detection, medical applications (ECG/vein analysis), and low-cost hardware implementations. He contributes to European standards (BioAPI, Hand Data Interchange Format) and evaluates security practices for R&D compliance with EU data protection regulations. Current initiatives include enhancing biometric systems for critical infrastructure security and improving accessibility for elderly users. Active in interdisciplinary collaborations, he leads the Mobile Pass project evaluating user interaction in biometric systems. His lab (GUTI) develops open testing methodologies for biometric performance under Common Criteria and environmental stressors. Recent work addresses vulnerabilities in mobile fingerprint sensors and the ethical implications of biometric-as-a-service models.
Andrea Meilán-Vila is an Assistant Professor in the Department of Statistics at Universidad Carlos III de Madrid since 2021, holding a Juan de la Cierva Fellowship since 2023. She earned her PhD in Statistics from Universidade da Coruña (2021) and previously served as a Postdoctoral Fellow at Universidade de Santiago de Compostela's Department of Statistics, Mathematical Analysis and Optimisation. Her research focuses on nonparametric methods for analyzing complex data types, including directional, spatial, and functional data. Key areas include kernel smoothing techniques, goodness-of-fit testing for regression models, and spatial trend estimation. She serves as an Associate Editor for the Journal of Nonparametric Statistics . Recent work emphasizes applications in climate science (temperature curve modeling), fluid dynamics (wake flow control), and biomedical imaging (hippocampus shape analysis). Her methodologies address challenges like sparse data estimation and spatial correlation in regression frameworks. Key Projects: STENED (Stein-based goodness-of-fit tests for non-Euclidean data) Awards: Juan de la Cierva Fellowship (2023) Publications span journals like Journal of Fluid Mechanics , Statistical Papers , and TEST , with a focus on methodological advancements in statistical modeling and computational validation.
Javier Gomez Fernandez is a researcher at the Nanobioengineering Group within the Institute for Bioengineering of Catalonia (IBEC), affiliated with the University of Barcelona. His work bridges nanotechnology and biomedical applications, focusing on advanced bioimaging and sensor development. Research Focus: Nanoscale bioelectrical characterization, smart nano-bio-devices, and molecular imaging Technological Impact: Development of low-power gas sensors and nanoscale membrane analysis tools His interdisciplinary approach contributes to fields like biomedical signal processing, biomaterials, and precision medicine. Recent projects highlight collaborations with clinical institutions and industrial partners to address challenges in muscular dystrophy and antimicrobial therapies. Key contributions include: 2020 IEEE Access paper on energy-efficient gas sensors 2010 PNAS study on nanoscale cell membrane characterization
Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).
Irene del Canto Serrano is a Researcher in the Department of Electronic Engineering at the School of Engineering, Universitat de València. Her work integrates biomedical engineering with cardiac electrophysiology, focusing on the interaction between mechanical forces and electrical activity in the heart. She is actively involved in two key research groups: GRELCA (Cardiac Electrophysiology group) and i2N (Electronic Instrumentation in Medical and Nuclear Physics), reflecting her dual expertise in physiology and instrumentation. Education: PhD in Biomedical Engineering, Universitat Politècnica de València (2015). Thesis: Estudio de las modificaciones farmacológicas de los efectos electrofisiológicos producidos por el estiramiento local miocárdico a partir de técnicas dinámicas de cartografía eléctrica, en un modelo experimental de corazón aislado de conejo , supervised by Dr. David Moratal Pérez and Dr. Francisco Javier Chorro Gascó. Her research interests center on cardiac electrophysiology , particularly mechanoelectric feedback , myocardial stretch , arrhythmia mechanisms , and pharmacological modulation using experimental models. She also explores cardiac imaging , especially cardiac MRI for strain and deformation analysis, and applies machine learning to improve detection and classification in myocardial infarction. Her recent publications highlight a strong trend toward integrating biomarkers (e.g., ferritin), iron therapy , and cardiac function recovery in heart failure, showing translational relevance. Her 15 most recent publications reflect a consistent focus on experimental cardiology using isolated heart models, pharmacological interventions (ranolazine, GS967, eleclazine), and advanced imaging techniques. She investigates how drugs affect stretch-induced arrhythmias, evaluates MRI-based strain changes post-iron therapy, and develops AI tools for cardiac image analysis. These works span basic science (e.g., CaMKII inhibition) to clinical applications (e.g., Myocardial-IRON trial analysis). Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: While no formal students or grants are listed, her role as a postdoctoral researcher and active publication record suggest involvement in mentoring junior researchers and contributing to funded projects, particularly within the GRELCA and i2N groups. She has co-authored numerous experimental studies, indicating strong collaborative and project-based research activity. Labs and Teams: Irene is affiliated with two prominent research groups at Universitat de València: GRELCA (Cardiac Electrophysiology group) , which studies arrhythmia mechanisms and therapeutic interventions, and i2N (Electronic Instrumentation in Medical and Nuclear Physics) , which develops advanced tools for medical diagnostics. These affiliations underscore her interdisciplinary approach, combining physiology, engineering, and data science.
Carlos Platero Dueñas is a Full Professor at the Department of Electrical, Electronic and Automatic Engineering and Applied Physics at the Universidad Politécnica de Madrid (UPM), where he has served for 31 years. He leads the research group Tecnologías para Ciencias de la Salud since 2015 and contributes to interdisciplinary research at the intersection of biomedical engineering, neuroscience, and artificial intelligence. Department: Electrical, Electronic and Automatic Engineering and Applied Physics Research Group: Tecnologías para Ciencias de la Salud (Health Science Technologies) Teaching: 34 years of academic experience, including 128 final projects supervised His research focuses on applying computational methods to neurodegenerative diseases , particularly Alzheimer's and Parkinson's, through neuroimaging analysis, predictive modeling, and hippocampal segmentation. Recent work includes AT(N) profiles for dementia prediction and machine learning techniques for clinical data modeling. The 15 most recent publications reveal a strong emphasis on Alzheimer's disease progression , hippocampal segmentation , and predictive analytics using neuroimaging and clinical markers. Key methodologies involve graph cuts algorithms, longitudinal modeling, and label fusion techniques applied to MRI and CT scans. Teaching contributions include: 128 final projects supervised (undergraduate and master's) 2 doctoral theses directed Active participation in university governance through the School Council and Researcher Staff Committee
Angel Merchan Perez is a faculty member at the Universidad Politécnica de Madrid , affiliated with the College of Computer Science and the Computer Systems Architecture and Technology Department . He is a key member of the Center for Biomedical Technology (CTB) since 2011 and the Technologies for Health Sciences Research Group since 2018. His work bridges neuroscience and computational technologies, focusing on ultrastructural analysis of the brain. Doctoral Postdoc: Harvard Medical School (1992-1995) Current Projects: Cajal Blue Brain Project, Human Brain Project His research focuses on developing advanced 3D electron microscopy techniques (FIB-SEM) for synaptic reconstruction, enabling quantitative analysis of synapse distribution and density in rat, mouse, and human cerebral cortex . He also contributed to image-analysis software like Espina for automated synapse detection. Recent publications highlight his expertise in: 3D Synaptic Mapping in Hippocampal Neurons Neurodevelopmental Disorder Pathology (Schizophrenia, Autism) Thalamocortical Circuit Complexity Mitochondrial Distribution in Neuropil Software Tools for Electron Microscopy
Prof. Daniel Ortega Ponce is a Senior Lecturer at the University of Cádiz's Condensed Matter Physics Department. He holds a PhD in Condensed Matter Physics from the University of Cádiz (2007) and has held positions including Ramón y Cajal Researcher (2020-2024), Marie Curie Fellow at University College London (2009-2012), and leadership roles in institutions like IMDEA Nanoscience and INiBICA. His research focuses on magnetic nanoparticles for biomedical applications, including hyperthermia, tissue engineering, and nanomedicine. Education: BSc in Chemistry of Materials (University of Cádiz, 2001) MSc in Industrial Process Engineering (2003) PhD in Condensed Matter Physics (2007) Research interests span nanomaterials for hyperthermia, magnetic nanoparticle synthesis, and in vivo thermal diagnostics. He leads the Nanoteranostics group at INiBICA and coordinates national and European networks in nanomedicine. Awards include EPSRC Peer Review College membership and Marie Curie fellowships. His work bridges physics, materials science, and clinical translation, with over 60 publications and 15 invited conference talks. Scientific awards include: Ramón y Cajal Researcher (2020-2024) EPSRC Peer Review College Member COST Action Coordinator (RADIOMAG, 2014-2018) Grants and collaborations involve leadership in the RedLab In Silico Electromagnetic Testing Lab and advisory roles for EU and international funding bodies. His research emphasizes computational modeling (in silico) for hyperthermia safety and efficacy, alongside experimental advancements in nanoparticle design.
Ignacio Cifre León is an Associate Professor in the Psychology and Speech Therapy Department at the Blanquerna School of Psychology, Education and Sports Sciences, Universitat Ramon Llull. His research focuses on neuroscience, functional connectivity, chronic pain, fibromyalgia, Alzheimer’s disease, and health communication, using advanced neuroimaging techniques like fMRI and EEG. His research interests center on understanding brain dynamics in neurological and psychological conditions. He investigates functional connectivity patterns in Alzheimer’s, fibromyalgia, and chronic pain, and explores brain complexity related to sleep and aging. His work also extends to mental health in high-risk populations, such as refugee rescue workers, and the psychometric adaptation of clinical tools for aphasia. The recent articles highlight a strong trend in applying nonlinear and multiscale methods to neuroimaging data, integrating fractal analysis, functional connectivity, and brain network dynamics across diverse conditions. His work bridges neuroscience, psychology, and biomedical engineering, with applications in clinical assessment and intervention. He leads and participates in several funded research projects, including FluctCoFuNLin, FASTCONN, and COMSAL, supported by national agencies such as Agencia Estatal de Investigación and MINECO. These projects focus on dynamical functional connectivity, health communication, and objective brain dynamics measurement. He is a core member of the 'Comunicació i Salut' (COMSAL) research group, collaborating with interdisciplinary teams across psychology, speech therapy, and neuroscience. His work involves both primary investigation and collaborative research with experts in trauma, aging, and language disorders.
