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Antonio Agudo Martínez is a Research Scientist at the Institut de Robòtica i Informàtica Industrial (IRI), a joint center of the Spanish National Research Council (CSIC) and Polytechnic University of Catalonia (UPC). His work spans computer vision, robotics, and machine learning with applications in medical rehabilitation, sports analytics, and renewable energy systems. He holds advanced degrees in Industrial Engineering, Computer Science, and a PhD in Computer Vision and Robotics from the University of Zaragoza. His research focuses on non-rigid structure from motion , 3D reconstruction , and deformation analysis , with significant contributions to medical applications (stroke rehabilitation), sports analytics (soccer trajectory modeling), and industrial systems (wind turbine monitoring). His publication record shows consistent high-impact output at top venues like CVPR, ICCV, and ECCV, with recent work emphasizing uncertainty quantification in diffusion models and multi-agent trajectory prediction. Notable scientific recognition includes a Best Paper Award Honorable Mention at ECCV 2018 for GANimation: One-Shot Anatomically Consistent Facial Animation. His research portfolio includes leadership of national projects like GreenVAR (renewable energy systems) and GRAvatar (realistic avatar generation), alongside contributions to SMARTGAZE II for low-vision mobility assistance. Dr. Agudo actively supervises doctoral research in computer vision applications, with current PhD candidates focusing on multimodal tracking for autonomous vehicles, soccer video understanding, sports metrics, and avatar generation. His international collaborations include work at Harvard University, Queen Mary University of London, University College London, Bordeaux University, and National University of Entre Ríos.

• Computer Vision
• Robotics
• Non-Rigid Structure from Motion
• +3 more

Emiliano Pereira González is a Professor at the Department of Signal and Communication Theory at Universidad de Alcalá (UAH). He holds a Ph.D. from Universidad de Castilla-La Mancha awarded in 2009, supervised by Dr. Vicente Feliú Batlle. His research focuses on vibration control, mechanical systems optimization, and the application of advanced control strategies to structural dynamics and robotics. He is affiliated with the TM Tecnologías Mecánicas, Eléctricas y Térmicas research group, specializing in mechanical, electrical, and thermal engineering technologies. Key research interests include active vibration control for pedestrian structures, optimization algorithms (e.g., Coral Reefs Optimization), and the design of assistive robotics systems like stair-climbing wheelchairs. His work integrates machine learning with metaheuristics to enhance mechanical system performance and reliability. Recent studies emphasize practical implementation challenges in RF power systems and cryogenic testing environments. Publications highlight contributions to MIMO control systems, stick-slip vibration mitigation in drill-strings, and submerged arch design optimization. While no specific awards are listed, his extensive publication record reflects sustained academic impact. He has advised no officially documented students in the provided texts, though his research group likely involves collaborative projects. Current work trends prioritize adaptive control strategies for nonlinear systems and biomimetic algorithm applications in structural engineering.

• Mechanical Engineering
• Control Systems
• Structural Vibration Control
• +3 more

Xavier Lladó Bardera is a Full Professor and ICREA Academia at the University of Girona, affiliated with the Department of Computer Architecture and Technology and the Computer Vision and Robotics Institute (VICOROB). He holds a PhD in Computer Engineering from the University of Girona and completed postdoctoral research at Queen Mary, University of London. B.S. in Computer Science, University of Girona (1999) Ph.D. in Computer Engineering, University of Girona (2004) Post-doctoral Research Assistant, Queen Mary, University of London (2004–2006) His research centers on medical image analysis, particularly in brain MRI, multiple sclerosis, prostate imaging, and deep learning. He has made significant contributions to lesion segmentation, tissue classification, and image registration, with a focus on clinical translation. His work integrates advanced computer vision techniques with biomedical applications, leveraging deep learning, non-rigid modeling, and multimodal imaging. The recent publications reflect a strong trend in deep learning for medical image analysis, especially in stroke, multiple sclerosis, and neonatal imaging. Key themes include lesion segmentation, hematoma expansion prediction, brain atrophy quantification, and end-to-end deep learning frameworks. There is a clear emphasis on clinical applicability, model interpretability, and handling real-world imaging challenges. Scientific Awards and Recognition: Best Project Prize – MAIA Master (Mladen Rakic, 2019) Best Project Prize – VIBOT Master (Jose Bernal, 2017) Best Project Prize – EINF Degree Project (E. Roura, 2011) Best Project Prize – EINF Degree Project (M. Cabezas, 2009) Best Project Prize – ETIG Degree Project (C. Fontanella, 2009) Best Paper Prize – Pattern Recognition (J. Salvi et al., 2010) Dr. Lladó has supervised over 20 PhD and master’s students, many of whom have continued in academia or industry (e.g., Icometrix, Johns Hopkins). He has been involved in numerous research grants and technology transfer initiatives, particularly in CAD systems for breast imaging and MS monitoring tools. His group actively collaborates with clinical partners, ensuring translational impact. He leads the NIC group at the VICOROB Institute, focusing on neuroimage computing and deep learning applications in neurology. The team develops open-source tools and participates in international challenges (e.g., BraTS, WMH), contributing to standardized evaluation in medical image analysis.

• Medical Image Analysis
• Computer Vision
• Image Processing
• +11 more

Diego Borro is a Full Professor (Catedrático) in Computer Science and Artificial Intelligence at TECNUN, Technological Campus of the University of Navarra , where he has been part of the faculty since 2004. He is a leading researcher at CEIT since 2003, focusing on Robotics, Virtual/Augmented Reality, Computer Vision, and Artificial Intelligence. His academic credentials include a PhD in Computer Science (2003) and an MS in Computer Science (2000) from the University of Navarra and University of Basque Country respectively. His research spans from 3D tracking and haptics to industry 4.0 applications and medical robotics, with over 34 journal papers and 65 conference articles. He has supervised 14 doctoral theses and participated in 55+ research projects. His leadership roles include heading CEIT's Simulation Unit (2012-2016) and Vision and Robotics (V&R) research line (2016-2022), currently serving as main researcher at Intelligent Systems for Industry 4.0 group (SS4I4). Accredited as Full Professor (Catedrático) by ANECA (3 sexenios) Member of IEEE, ACM, and Eurographics societies Key projects: STEPbySTEP exoskeleton benchmark, WARM AR maintenance systems, and inner ear drug delivery research

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +6 more