جست‌وجوی استاد و پژوهشگر

Antonio Gonzálezمشاهده پروفایل

استاد

• Computer Architecture
• Microarchitecture
• Compilers
• +۷ مورد دیگر

Antonio González is a full Professor at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Architecture. He leads the Microarchitecture and Compilers (ARCO) research group, focusing on robust and energy-efficient computing systems, including general-purpose processors, GPUs, and cognitive computing architectures. His research spans computer architecture, microarchitecture, compilers, GPU design, and deep learning acceleration, with a strong emphasis on energy efficiency and memory optimization. His work integrates hardware and compiler techniques to enhance performance in modern computing systems. The recent publications highlight a strong trend in energy-efficient DNN acceleration, GPU microarchitecture, memory systems, and near-data processing. His team explores novel quantization methods, adaptive caching, and architectural extensions for vision and AI workloads, published in top-tier venues such as MICRO, ISCA, and IEEE/ACM journals. ACM Fellow (2020) ICREA Academia Award (2014, 2019, 2024) UPC Duran Farell Award (2008) HiPEAC 2024 Paper Award (twice) González has supervised several PhD students and leads competitive R&D+i projects, including those funded by ICREA and the European Research Council. His research group collaborates extensively within UPC and with international institutions. He is actively involved in advancing computer architecture through innovation in simulation, hardware design, and AI acceleration. He is a member of IEEE and ACM, and his work continues to influence both academic and industrial developments in high-performance and energy-efficient computing.

Leland Bybeeمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing
• Econometrics
• +۲ مورد دیگر

Leland Bybee is an Assistant Professor of Finance at the University of Chicago Booth School of Business . He leverages machine learning and natural language processing to address economic and financial questions, particularly focusing on belief measurement with applications to asset pricing and behavioral economics. Ph.D. in Financial Economics, Yale School of Management (2024) M.S. in Statistics, University of Michigan (2017) B.A. in Economics, University of Chicago (2013) His research integrates computational methods with economic theory to analyze: Textual analysis of business news for macroeconomic tracking Narrative-driven asset pricing models Memory-based belief formation using kernel methods Macroeconomic determinants of currency returns He has received multiple awards including: Dimension Fund Advisors Distinguished Paper Award BlackRock Applied Research Award HEC Top Finance Graduate Award The Brattle Group PhD Candidates Award EFA Engelbert Dockner Memorial Prize Bybee teaches Machine Learning in Finance and participates in finance seminars, contributing computational tools like regIPCA (Python) and changepointsHD (R) to the research community.

Pere-Pau Vázquezمشاهده پروفایل

استادیار

• Information Visualization
• Scientific Visualization
• Medical Data Visualization
• +۶ مورد دیگر

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.

• High-dimensional statistics
• Bayesian statistics
• Statistical analysis of complex data
• +۴ مورد دیگر

David Rossell is an Associate Professor at the Department of Economics, Universitat Pompeu Fabra (UPF) in Barcelona, Spain. He is affiliated with the Statistics@UPF research group and directs the Master in Data Science at the Barcelona School of Economics (BSE). Previously, he held positions at IRB Barcelona as head of the Biostatistics Unit and at the University of Warwick's Statistics Department. He obtained his PhD in Statistics from Rice University, Houston (USA), and conducted postdoctoral research at M.D. Anderson Cancer Center under Professors Valen Johnson and Veera Baladandayuthapani. Research Interests: Rossell specializes in high-dimensional statistical inference, Bayesian methods, computational statistics, and applications in biomedicine and social sciences. His work emphasizes methodology for complex data integration, variable selection, graphical models, and experimental design. Key areas include non-local priors, scalable Bayesian computation, and the development of R packages for statistical analysis (e.g., casper , chroGPS , gaga ). Publications: His recent work focuses on advancing Bayesian variable selection, graphical models with external data, and causal inference. Themes include leveraging external datasets for improved model accuracy, robustness to model misspecification, and applications in healthcare and complex mixture analysis. His contributions span methodological innovation and computational tools for high-dimensional problems. Funding & Grants: Rossell has secured funding through Spanish and European grants, including Juan de la Cierva Fellowships, AGAUR fellowships, and Marie Slodowska-Curie Actions. He supports PhD and postdoctoral researchers through programs like La Caixa InPhD and Beca Beautriu de Pinós. Labs & Teams: He leads the BSE Data Science Center and contributes to interdisciplinary collaborations at UPF and IRB Barcelona, bridging statistical theory and practical applications in genomics, epigenomics, and health data analysis.

Frank NIELSENمشاهده پروفایل

استاد

• Data science
• Geometric science of information
• Information geometry
• +۴ مورد دیگر

Frank NIELSEN is a Professor at École Polytechnique with expertise in information geometry, data science, and machine learning. He holds a PhD (1996) and HDR (2006) in computer science and has established himself as a leading researcher in geometric approaches to information science. His educational background includes a PhD in computer science (1996) followed by a Habilitation à Diriger des Recherches (HDR) in 2006, the highest academic qualification in France that qualifies one to supervise doctoral candidates. Dr. NIELSEN's research focuses on the Geometric Science of Information , where he develops theoretical frameworks for understanding data through geometric and information-theoretic lenses. His work bridges Computational information geometry Statistical manifold theory Bregman divergences and their applications Machine learning with geometric foundations High-dimensional data analysis He aims to address the challenge of inappropriate data representation in current Data Science by building a theory of Computational Information Geometry to enable Intrinsic Data Science with principled distances. His extensive publication record shows a clear trend toward developing geometric frameworks for understanding statistical divergences, with recent work focusing on Bregman geometry, Fisher-Rao metrics, and their applications in machine learning. His research spans theoretical developments in information geometry to practical implementations like the pyBregMan Python library, demonstrating both theoretical depth and practical relevance. Dr. NIELSEN has made significant contributions through his teaching and publications. He has taught courses at École Polytechnique including INF442, INF517, and INF591. His authored textbooks include Introduction to HPC with MPI for Data Science (2016), A Concise and Practical Introduction to Programming Algorithms in Java (2009), and Visual Computing: Geometry, Graphics, and Vision (2005). He has also edited influential volumes such as Computational Information Geometry for Image and Signal Processing (2016) and Geometric Theory of Information (2014). He actively organizes and participates in academic events, serving on program committees for major conferences including GSI (Geometric Science of Information), CVPR, and ICCV. His work has established him as a key figure in the growing field of geometric approaches to information science.

Julian Fierrezمشاهده پروفایل

استاد

• Biometrics
• Signal and Image Processing
• Artificial Intelligence
• +۶ مورد دیگر

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.

Miguel Mascaró Portellsمشاهده پروفایل

مدرس ارشد

• Computer Science
• Web Development
• Cloud Computing
• +۷ مورد دیگر

Dr. Miguel Mascaró Portells is a Senior Lecturer at the University of the Balearic Islands in the Department of Mathematics and Computer Science. He holds a PhD in Computer Science and actively contributes to research groups focused on computer graphics, AI, and multimedia technologies. Research Focus: His work encompasses web development, cloud computing, Big Data applications, neural vision systems, multimedia content management, and geolocation technologies. Specific interests include: Object-Oriented Programming (OOP) and SOA services Mobile device programming and TDT visualization Cloud-based multiprocessing systems Home automation and control systems Teaching: Current courses include: Advanced Algorithms Programming - Computer Science I Final Degree Project supervision SOA solutions for tourism Affiliations: Active member of: Computer Graphics, Vision and AI Unit (UGIVIA) Multimedia Information Technology (TIM) Research Group

• Artificial Intelligence
• Computer Science
• Swarm Robotics
• +۵ مورد دیگر

Ramón Luis Rizo Aldeguer is a University Professor in the Department of Computer Science and Artificial Intelligence at the Higher Polytechnic School of the University of Alicante. He has held this position since 1996 and continues to be actively involved in teaching and research as recently as 2025. He previously served in various leadership roles including Director of the Department of Computer Science and Artificial Intelligence (1997-2004) and Deputy Director of the Institutional Projects Area at the University of Alicante (2012-2020). His educational background includes a PhD in Computer Science from the Polytechnic University of Valencia (1992) and a degree in Mathematics from the University of Valencia (1977). He has been a member of the Spanish Association for Artificial Intelligence since 1990 and has held leadership positions within the organization. Rizo Aldeguer's research focuses on artificial intelligence with particular emphasis on swarm robotics, UAV deployment, and deep reinforcement learning. His work bridges theoretical foundations with practical applications in robotics and autonomous systems. He has made significant contributions to educational methodologies, particularly in integrating computational tools into engineering education. His publication record shows a consistent trajectory in swarm intelligence and robotics, with recent publications (2018-2023) demonstrating increasing sophistication in applying deep reinforcement learning to complex multi-agent systems. His research spans both theoretical advancements and practical implementations in robotics and autonomous systems. Fifteen five-year research periods (trienios) Six teaching merit periods Five six-year research periods (sexenios) President of Organizing Committee of VI Conference of Spanish Association for Artificial Intelligence (1995) President of Scientific Committee of CAEPIA (1999) Rizo Aldeguer has supervised 14 doctoral theses, with many receiving the highest honors (SOBRESALIENTE CUM-LAUDE). He has participated as a researcher in over 30 competitive public research projects, serving as principal investigator in 12 of them. His educational projects include innovative teaching methods and the development of computational tools for engineering education. He has been instrumental in the design and implementation of computer science programs at both the University of Alicante and the Polytechnic University of Valencia. He is a founding member of the University Institute for Computer Research and directed the Industrial Computing and Artificial Intelligence research group from 1992 to 2004. His current research continues to focus on swarm robotics and intelligent systems, with active participation in the Valencian Graduate School and Research Network of Artificial Intelligence since 2021.

• Digital Sociology
• Social Media Analysis
• Disinformation and Misinformation
• +۳ مورد دیگر

Francisco Javier Canton Correa is a researcher at the Universidad de Granada, specializing in sociology. He earned his PhD in 2019 with the thesis Socialización digital y creatividad audiovisual , supervised by Dr. Jordi Alberich Pascual. Education: PhD in Sociology (2019), Universidad de Granada Research Interests focus on digital sociology, social media analysis, and the societal impact of artificial intelligence. His work explores disinformation combat, visual communication, and urban culture through computational methods. Recent Publications highlight AI-driven tools for misinformation detection, social media analytics, and critical perspectives on digital humanities. Key trends include cross-platform verification systems and sociological risk frameworks for global disinformation. Labs & Collaborations include Medialab UGR, where he contributes to cross-media communication experiments.

• Computer Architecture
• Microarchitecture
• Compilers
• +۷ مورد دیگر

Antonio Maria Gonzalez Colas is a Full Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Faculty of Computer Science of Barcelona (FIB). He leads the ARCO research group focused on Microarchitecture and Compilers and is actively engaged in high-impact research in computer architecture, GPUs, and energy-efficient computing. His collaborations extend to the Barcelona Supercomputing Center and various national and European research initiatives. Research Interests: His primary research areas include computer architecture, microarchitecture, compilers, GPUs, and processor design. He focuses on energy-efficient computing, deep neural network (DNN) accelerators, GPU simulation and optimization, memory systems, and architectural support for machine learning and autonomous systems. His work often integrates compiler techniques with hardware design for performance and efficiency. Scientific Production Trends: His recent publications demonstrate a strong focus on energy-efficient hardware for AI workloads, particularly DNN and speech recognition acceleration, GPU architectural innovations, memory optimization, and real-time rendering. He frequently publishes in top-tier venues such as ISCA, MICRO, HPCA, and IEEE/ACM journals. ICREA Academia Award 2024 HiPEAC 2024 Paper Award ACM Senior Member (2020) Advising and Grants: He has advised numerous PhD students whose theses cover topics like energy-efficient architectures for autonomous driving, speech recognition, and neural networks. He leads competitive R&D projects, including an ERC Advanced Grant and projects funded by the Spanish National Program and the ICREA Academia program, focusing on domain-specific architectures and cognitive computing units. Labs and Teams: He is the principal investigator of the ARCO (Microarchitecture and Compilers) research group at UPC, a leading team in computer architecture research in Spain. The group is part of a larger collaborative network within UPC and with international partners.

Belen Masiaمشاهده پروفایل

دانشیار

• Computational Imaging
• Applied Perception
• Virtual Reality
• +۴ مورد دیگر

Belen Masia is a tenured Associate Professor in the Computer Science Department at Universidad de Zaragoza , Spain. She is affiliated with the Graphics & Imaging Lab (part of the I3A Institute ) and the Vision, Image and Neurodevelopment Group (within the IIS Aragon Institute ). Her research bridges computational imaging , applied perception , and virtual reality , focusing on modeling human visual behavior and improving graphics/vision algorithms through perceptual insights. Education : Ph.D. in Computer Science (Eurographics PhD Award 2015), postdoctoral work at Max Planck Institute for Informatics . Research Highlights : Virtual Reality : Studying user behavior, saliency prediction, multimodal perception, and cinematography in VR. Appearance Modeling : Developing intuitive material representations and metrics for editing. Applied Perception : Leveraging human vision insights to diagnose defects in non-verbal patients. Computational Displays : Exploring HDR imaging and display optimization. Scientific Awards : Eurographics Young Researcher Award 2017 Eurographics PhD Award 2015 MIT Technology Review Top Ten Innovators Below 35 in Spain 2014 NVIDIA Graduate Fellowship 2012 Leonardo Fellowship from BBVA Foundation 2020 Leadership & Editorial Roles : Co-chair of Full Papers track at Eurographics 2026 Associate Editor for ACM Transactions on Graphics, Computers and Graphics, and ACM Transactions on Applied Perception Co-founder of DIVE Medical , a startup for automated visual function diagnosis PhD Students : Dario Lanza (2025, Modeling, Perception and Editing of Volumetric Materials ) Daniel Martin (2024, Computational Models of Visual Attention in VR , Best PhD Thesis Award EGSE) Julia Guerrero-Viu (2023, WiGRAPH Rising Star) Sandra Malpica (2023, VR Gaze Behavior ) Manuel Lagunas (2021, BBVA/SCIE Young Researcher Award) Ana Serrano (2019, Eurographics PhD Award & Unizar Outstanding Thesis) Collaborations & Grants : Involved in the EU-funded PRIME Innovative Training Network (predictive rendering and appearance reproduction) and leading projects on deep learning for pediatric visual diagnosis.

• Computer Graphics
• Virtual Reality
• Cultural Heritage Visualization
• +۷ مورد دیگر

Carlos Antonio Andújar Gran is a faculty member at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Science. He actively contributes to the academic community through teaching and supervising numerous student projects, particularly in advanced computing domains. His research interests center on the application of computer graphics, virtual reality, and artificial intelligence to real-world problems. Key areas include the 3D visualization and virtual reconstruction of cultural heritage, physically accurate rendering, intelligent segmentation of images, and the use of machine learning and reinforcement learning in sports analytics, particularly for padel. His work bridges technical innovation with practical applications in cultural preservation and sports technology. The recent publications under his supervision reflect a strong trend in digital cultural heritage, with multiple projects focused on tools for virtual visits, reconstruction, lighting simulation, and web-based 3D visualization of heritage models. Another significant trend is the application of AI to padel, including ball and player tracking, virtual coaching, and training virtual agents using reinforcement learning. These projects demonstrate a consistent focus on computer vision, interactive systems, and data-driven modeling. Carlos Antonio Andújar Gran has supervised a substantial number of students, guiding both undergraduate and master's theses. While specific grant information is not available in the text, his sustained supervision across many years suggests active involvement in research projects. He plays a key role in mentoring the next generation of computer scientists at UPC. His work is closely tied to the Department of Computer Science at FIB, where he collaborates with other faculty members such as Imanol Muñoz Pandiella, Núria Pelechano Gómez, and Mohammadreza Javadiha on various student projects, indicating a collaborative research environment focused on graphics, AI, and VR applications.

• Computer Science
• Virtual Reality
• Character Animation
• +۶ مورد دیگر

Núria Pelechano Gómez is a Professor at the Universitat Politècnica de Catalunya (BarcelonaTech) , affiliated with the Faculty of Informatics of Barcelona (FIB) and the Department of Computer Science (CS) . Her work focuses on Virtual Reality , Crowd Simulation , and Character Animation , with a particular emphasis on immersive environments and user interaction. Education: Master's Degree in Innovation and Research in Computer Science (2012) Degree in Computer Engineering (2010) Master's Degree in Computing (2006) Her research explores the integration of Virtual Reality with Artificial Intelligence to enhance user experiences through dynamic crowd modeling, realistic animations, and adaptive navigation techniques. Recent projects highlight her expertise in Motion Matching , Immersive Simulation , and Physics-Based Animation . Key trends in her publications include: Advancements in Virtual Environments and 3D Modeling . Applications of Machine Learning in Navigation Interfaces . Development of Realistic Crowd Behavior and Social Interaction Systems in VR. Focus on User-Centric Design and Embodiment Techniques . Núria has supervised numerous students on topics ranging from Emergency Scenario Modeling to MR Application Development for immersive systems, contributing to the evolution of Immersive Simulation and Game Development methodologies.

• Sustainable Engineering
• Graphic Expression in Engineering
• Industrial Design
• +۵ مورد دیگر

María Elena Arce Fariña is a Professor in the Department of Industrial Engineering at the Escola Politécnica de Enxeñaría de Ferrol, Universidade da Coruña (UDC). Her academic profile demonstrates extensive involvement in both teaching and research activities within the field of engineering education and sustainable technologies. Her research interests span multiple domains including Sustainable Engineering, Graphic Expression in Engineering, Industrial Design, Energy Efficiency, Textile Technology, Building Energy Analysis, and Computer-Aided Design. These research areas are reflected in her diverse publication record and collaborative projects. Dr. Arce Fariña's recent scholarly output shows a strong focus on interdisciplinary research connecting engineering education with sustainability challenges. Her publications reveal consistent contributions to high-impact journals in materials science, energy, sensors, and engineering education, demonstrating her ability to bridge theoretical knowledge with practical applications in sustainable industrial design and energy efficiency. She actively supervises bachelor's and master's theses, with recent projects focusing on luminaire design, energy analysis of buildings, industrial component replication through reverse engineering, and sustainable textile product development. Her teaching portfolio includes courses such as Digital Design and Development of Textile Products (Master's Degree in Textile Technology and Sustainable Fashion), Graphic Expression (across multiple engineering degrees), and supervision of Final Degree Projects and Master's Theses in Industrial Engineering programs. Dr. Arce Fariña participates in numerous research projects funded by entities including the European Commission, Consejo de Seguridad Nuclear, Fundación Española para la Ciencia y la Tecnología, and regional Galician organizations, demonstrating her ability to secure competitive research funding and collaborate across institutional boundaries.

• Human-Computer Interaction
• Educational Technology
• Computer Science Education
• +۳ مورد دیگر

Francisco Javier Oliver Bernal is a Lecturer at the University of Deusto in Bilbao, Spain, within the Faculty of Education and Sport and the Department of Physical Activity and Sports Sciences. He teaches across Computer Engineering, Physical Activity and Sports Sciences, and Primary Education bachelor's programs, as well as the Master's in Secondary Education. He earned his Doctor of Medicine and Surgery from the University of the Basque Country. His research spans Human-Computer Interaction, Educational Technology, and Science Education, with a strong emphasis on accessibility for visually impaired users. He has developed tools for e-learning, digital resource centers, and innovative teaching methodologies in computer science and natural sciences, aiming to enhance educational experiences through technology. His scholarly output, spanning from the 1990s to 2023, demonstrates a consistent focus on technology-enhanced learning, evolving from early work in 3D interfaces and computer graphics to recent applications in health, music, and interdisciplinary educational contexts. Key trends include the integration of accessibility features, the development of domain-specific educational tools (e.g., for biology and astronomy), and responses to contemporary challenges like the COVID-19 pandemic. He has supervised multiple theses on digital accessibility and cooperative systems, though student names were not listed. Details on research grants were not provided in the available text. As a member of the eVida research group (officially recognized by the Basque Government), he contributes to projects advancing accessible educational technologies, including the ACCE project for audiovisual accessibility and READIS digital resource centers for visually impaired users.