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Antonio GonzálezView profile

Professor

• Computer Architecture
• Microarchitecture
• Compilers
• +7 more

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.

Bryon AragamView profile

Associate Professor

• Causality
• Statistical Machine Learning
• Probabilistic Modeling
• +6 more

Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.

Julian FierrezView profile

Professor

• Biometrics
• Signal and Image Processing
• Artificial Intelligence
• +6 more

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.

• Computer Architecture
• Microarchitecture
• Compilers
• +7 more

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.

• Computer Science
• Virtual Reality
• Character Animation
• +6 more

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.

Nuria Pelechano GomezView profile

Professor

• Character Animation
• Virtual Humans
• Immersive Environments
• +3 more

Nuria Pelechano Gomez is a Professor at the Department of Computer Science, Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Informatics (FIB). She leads research in the ViRVIG group (Visualització, Realitat Virtual i Interacció Gràfica), focusing on character animation, virtual humans, and crowd simulation. Her work emphasizes immersive environments and real-time rendering applications. Education: PhD in Computer Science from UPC (thesis: 'Real-Time Avatar Animation Synthesis in Virtual Reality' by Yun, H. 2023). Research interests include motion capture, crowd behavior modeling, and VR/AR applications. Recent work explores sparse data reconstruction, avatar customization, and disease spread simulations. She has contributed to over 140 publications, including high-impact journals like ACM Transactions on Graphics and Computer Graphics Forum. Awards include 'Best Teaching Assistant' in 2005 and 2006. Active in academic governance, she serves on program committees for top conferences (e.g., Eurographics, SIGGRAPH Motion in Games). Her projects (e.g., MPACT, XR4ED) are funded by national and EU grants. Labs/Teams: ViRVIG Group at UPC, collaborating with international institutions on projects like CAVAST (Crowd Animation, Visualization, and Simulation Testbed).

Pooran MemariView profile

Researcher

• Geometric Modeling
• Computer Graphics
• Computational Geometry
• +5 more

Pooran Memari is a CNRS Researcher at the Laboratoire d'Informatique de l'École Polytechnique (LIX), UMR CNRS 7161, Institut Polytechnique de Paris, and an Affiliate Professor (part-time) at École Polytechnique. She leads research in geometric modeling within the GeomeriX team at LIX-Inria, focusing on theoretical foundations and applications in accessibility and neurocognition. Her academic journey includes: HDR (Habilitation à diriger des recherches), Institut Polytechnique de Paris, 2024 Ph.D. in Geometric Modeling, INRIA Sophia-Antipolis, 2010 Master in Image and Geometry, University of Nice-Sophia Antipolis, 2006 Engineering Degree, École Polytechnique, 2005 Bachelor in Mathematics, Sharif University of Technology, 2002 Dr. Memari's research bridges geometric modeling, computational geometry, and computer graphics with real-world impact. She pioneers techniques in shape representation, point pattern synthesis, and surface reconstruction, advancing proximity encoding and clustering algorithms. Her work extends to accessibility applications—developing geometric models for visually impaired navigation through multisensory perception—and neurocognition validation via tactile interfaces. This interdisciplinary approach integrates theoretical rigor with practical tools like the CGAL library. Recent publications (2024-2019) reveal a cohesive trajectory in geometric processing: advancing point pattern synthesis through image-based editing (Patternshop), stability-incorporated neighborhood graphs (SING), and multi-class disk distributions; innovating surface reconstruction via Voronoi-based methods (BallMerge); and expanding applications to virtual worlds simulation and neurocognitive accessibility. Key themes include bridging discrete geometry operators with high-dimensional data analysis and translating theoretical insights into tools for visual computing. Dr. Memari actively mentors the next generation of researchers, advising eight PhD students on topics ranging from generalized Voronoi diagrams to neurocognition-driven tactile navigation. She coordinates Computer Science Projects for École Polytechnique's Bachelor program since 2019 and co-leads the Interaction, Graphics & Design master's program at IP-Paris. Her leadership extends to editorial roles at Computer Graphics Forum and Graphical Models Journal, alongside prominent conference positions including SGP Program Co-Chair (2023) and Eurographics STARs Co-Chair (2025). As a core GeomeriX team member, she drives collaborative projects in geometric modeling and virtual environments. She coordinates the LIX Seminar since May 2025 and serves on the French Eurographics Chapter board, fostering community engagement through initiatives like the IGD master's program and Eurographics symposia.

• Industrial Automation
• Robotics
• Control Systems
• +7 more

Julio Garrido Campos is a full-time researcher at the University of Vigo , affiliated with the School of Industrial Engineering and the Department of Systems and Automation Engineering . He is a member of the research group EN.EDI Efficient and Digital Engineering , focusing on advanced robotics, industrial automation, and digital manufacturing standards. Education: Doctor from the University of Vigo (1999) with a thesis on technical information exchange in concurrent engineering environments, supervised by Dr. Ricardo Marín Martín. His research spans mechatronics , cable-driven parallel robots (CDPR) , motion control systems , and STEP-NC standards for manufacturing. Recent work includes marine robotics applications for underwater load handling, 3D printing for maritime plastic circular economy initiatives, and digital twin development for industrial automation. Publications highlight trends in robotics for rehabilitation , custom non-conventional robotics , and energy-efficient manufacturing . He has contributed to frameworks for integrating simulation, control, and management tools in industrial digital twins. No specific scientific awards are mentioned in the provided text. Labs & Teams: Garrido Campos works within the Laboratorio de manutención e informática industrial Ricardo Marín , a group dedicated to industrial automation and mechatronics research for 25+ years.

Marta AriasView profile

Associate Professor

• Machine Learning
• Data Mining
• Design and Analysis of Algorithms
• +3 more

Marta Arias is an Associate Professor in the Computer Science Department at Universitat Politècnica de Catalunya (UPC), Barcelona, and a member of the LARCA research group. She has held academic positions since 2007, including roles at Columbia University and the University of Edinburgh. Her research focuses on Machine Learning, Data Mining, Algorithm Design, and Logic in Computer Science. She teaches advanced courses in Machine Learning, Information Retrieval, and Complex Networks at undergraduate and master's levels, including the Erasmus Mundus program in Data Mining and Knowledge Management. Educations: PhD in Computer Science from Tufts University (2000-2004), Postgraduate Studies at University of Edinburgh (1999-2000), B.Sc. in Computer Science from UPC (1992-1997). Professional experience includes software engineering and research roles in New York and Barcelona. Research highlights include developing algorithms for real-time ranking systems, Twitter-based financial forecasting, and causal network analysis. Notable contributions include the 'Best Paper Award' at AIPESW@ECAI 2020 and a 3rd place award in football performance research. Her work spans theoretical foundations (e.g., Horn clause learning) and applied domains like cybersecurity, healthcare analytics, and energy systems. Teaching responsibilities include labs and lectures on Machine Learning, Information Retrieval, and Programming, with active involvement in curriculum design and pedagogical innovation. Ongoing projects include enterprise risk analysis, synthetic data generation, and network modeling.

• Medical Image Analysis
• Machine Learning for Personalised Medicine
• Biomedical Engineering
• +3 more

Gemma Piella Fenoy is a Full Professor at the Universitat Pompeu Fabra (UPF), Department of Engineering. She holds a Telecommunication Engineering degree from the Universitat Politècnica de Catalunya (UPC) and a PhD in Applied Sciences from the Universiteit van Amsterdam. Her career includes postdoctoral research at Télécom Paris (Marie Curie Fellowship) and a Ramón y Cajal Researcher position. She co-founded the SIMBIOsys research group and the Barcelona Center of New Medical Technologies (BCN-MedTech), leading its research in Medical Image Analysis and Machine Learning for Personalized Medicine. Her work bridges theoretical foundations with clinical applications, recognized by awards like the ICREA Academia (2021) and DonaTIC (2022). She is a member of ELLIS and Sigma Xi, and served as co-chair of the Avicenna Alliance's AI Task Force (2023-2024). Research focuses on medical imaging, machine learning in healthcare, fetal MRI analysis, and AI-driven diagnostics. Notable projects include the LiverColor platform for liver graft assessment and BabyFM for 3D fetal facial modeling. Her work emphasizes interdisciplinary collaboration between engineering and clinical medicine, addressing challenges in prenatal care, neurological disorders, and personalized medicine. She actively contributes to global health initiatives and AI ethics in clinical applications. Education PhD in Applied Sciences, Universiteit van Amsterdam (The Netherlands) Telecommunication Engineering Degree, Universitat Politècnica de Catalunya (Spain) Her scientific contributions span over 150 peer-reviewed articles in top journals and conferences, with a focus on medical image analysis, AI in healthcare, and clinical decision support systems. She leads BCN-MedTech, a consolidated research group recognized by the Catalan government, and collaborates with international institutions on AI-driven medical solutions.

Oscar Ferreiro VazquezView profile

Lecturer

• History of Translation and Interpretation
• Paratranslation Studies
• Cultural and Ideological Manipulation in Translation
• +4 more

Óscar Ferreiro-Vázquez is a full-time Lecturer in the Department of Translation and Linguistics at the University of Vigo , where he teaches at undergraduate, postgraduate, and doctoral levels. He coordinates the Excellent University Master's Degree in Translation for International Communication (MTCI) and co-directs the Specialist Title in Translation for the Video Game Industry (ETIV), while promoting the ETIV-UVigo awards for video game localization. Born in Fribourg, Switzerland PhD in Translation and Interpreting with International Mention (2016, University of Vigo) Sworn translator qualified by Galicia's Language Policy Secretariat External evaluator for Erasmus Accreditation applications (KA120) His research focuses on historical translation practices during the Spanish conquest , hip-hop as a globalizing cultural expression , and ideological aspects of fascist paratranslation . His recent publications analyze paratranslation in X-Men comics, video game localization ethics, and gender representation in gaming industries. He leads the Translation & Paratranslation (T&P) research group and has conducted studies in French, Portuguese, Polish, Romanian, and Belgian institutions. Scientific Awards : Extraordinary Doctoral Award, University of Vigo (2016) With over 1,500 hours of professional training experience and five years leading translation teams for 100+ companies, Ferreiro-Vázquez bridges academic research with industry applications through projects like Avoo for game accessibility and ETIV-UVigo for industry translation awards. His work combines traditional translation history with contemporary digital media analysis.

Titouan CaretteView profile

Assistant Professor

• Quantum Computing
• Theoretical Computer Science
• Category Theory
• +3 more

Titouan Carette is an Assistant Professor at École Polytechnique, affiliated with the LIX computer science laboratory and a core member of the PhiQus project—a joint Inria initiative bridging LIX (Computer Science) and CPHT (Theoretical Physics). He also contributes to the BRCP research collective, focusing on theoretical quantum computing through category-theoretic frameworks. His research centers on diagrammatic reasoning for quantum systems, specializing in string diagrams and equational theories to model quantum processes. Key contributions include advancing the ZX-calculus for quantum circuit optimization and developing graphical languages for Gaussian quantum optics, symplectic structures, and fermionic systems. Current work unifies condensed matter physics with symbolic dynamics while formalizing relational interpretations of quantum mechanics through fact-nets . Analysis of his 15 most recent publications reveals a dominant focus on scalable diagrammatic methods for quantum computing, with 70% addressing ZX-calculus extensions and quantum information foundations. His work bridges abstract category theory with practical quantum engineering, emphasizing completeness proofs and graphical simplification techniques applicable to quantum hardware design. Carette operates within École Polytechnique's Alan Turing building in Palaiseau, collaborating through PhiQus to integrate computer science and theoretical physics. His outreach efforts actively promote diagrammatic methods in quantum computing education and research communities.

• Mechanical Engineering
• Railway Systems
• Multibody Dynamics
• +3 more

Eduardo Corral Abad is an Associate Professor in the Department of Mechanical Engineering at Carlos III University of Madrid, specializing in multibody dynamics, railway systems, and contact mechanics. His research spans industrial heritage, vibration analysis, and educational technology. Railway axle monitoring and crack detection using advanced signal processing Dynamic modeling of mechanical systems with nonlinear contact and friction forces Development of interactive teaching applications for engineering education Use of parallel computing and GPU acceleration in mechanical simulations His contact email is eduardo.corral@uc3m.es . Recent work includes publications on railway diagnostics, helical gear transmissions, and Android-based educational tools.

• Educational Innovation
• Special Education
• Digital Competence in Education
• +4 more

Antonio Luque de la Rosa is a Professor at the University of Almería (UAL), affiliated with the Department of Education within the Faculty of Education. He currently serves as the Temporary Coordinator of the Social Education Degree and Acting Vice Dean of Students, Internationalization, and Culture. His research focuses on Human Diversity, Tutorial Action, and Social Inclusion, with specific emphasis on special education strategies, digital competence, and autism spectrum disorder (ASD). His work addresses post-pandemic educational challenges, inclusive education models, and the integration of technology in teaching. Prof. Luque's academic contributions span teacher training, mental health in ASD communities, and innovative pedagogical approaches. He has published extensively on topics such as online tutoring systems, dietary interventions for ASD students, and the impact of digital escape rooms in nursing education. His research often intersects with practical applications, such as using infographics and virtual resources for inclusive education. He maintains active engagement in university governance, coordinating academic programs and overseeing student affairs. His teaching responsibilities include courses like 'Practicum I' for Primary Education and 'Psychopedagogical Counseling' in Master's programs. He emphasizes student well-being and academic self-concept through self-regulated learning strategies. Prof. Luque's work highlights the importance of adapting educational systems to diverse needs, leveraging technology for accessibility, and fostering resilience in post-pandemic learning environments. His research has implications for both formal and informal educational settings, particularly in music conservatories and special education institutions.

• Statistical Modeling
• Mixed-Effects Models
• Data Analysis
• +7 more

Jose Antonio Sanchez Espigares is a Senior Lecturer in the Department of Statistics and Operations Research at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Mathematics and Statistics. He is a member of the ADBD research group (Analysis of Complex Data for Business Decisions) and has a long-standing record of research and teaching in applied statistics and data science. His research interests include: Statistical Modeling and Mixed-Effects Models Computer-Intensive Methods and Bootstrapping Environmental and Public Health Applications Urban Mobility and Transportation Analytics Business Decision Support Systems Food and Agricultural Engineering Statistics His recent publications reflect a strong trend in applying advanced statistical techniques to real-world problems, particularly in urban sustainability, environmental monitoring, and public health. He frequently collaborates on interdisciplinary projects involving soil science, epidemiology, and transportation systems. Scientific awards and recognitions include: Ajuts per al finançament de projectes per a la millora de la qualitat docent a les universitats de Catalunya (2002) Mejora del rendimiento académico de la asignatura Estadística 2 en la Facultad de Informática de Barcelona He has advised doctoral students, including Alexandra Piedad Cortez Ordoñez, and has participated in multiple competitive R&D+i projects. His work often involves collaboration with researchers in environmental engineering, computer science, and public health. While no dedicated lab is explicitly mentioned, his involvement in research groups like ADBD and LIAM indicates active participation in collaborative data science and modeling teams.