Dr. Chuanxia Zheng is a Marie Skłodowska-Curie Actions (MSCA) Fellow and Research Fellow at the Visual Geometry Group (VGG) within the Department of Engineering Science at the University of Oxford, working with Professors Andrea Vedaldi and Andrew Zisserman. He holds a PhD from Nanyang Technological University (NTU), where his thesis on 'Synthesizing Photorealistic Images' earned the NTU Outstanding PhD Thesis Award in 2022. Starting Fall 2025, he will assume the position of Nanyang Assistant Professor at NTU's College of Computing and Data Science, leading the Physical Visual Group. His research focuses on Creative AI , emphasizing systems that perceive, reconstruct, and interact with the physical world. Key areas include 3D/4D reconstruction, generative models, and digital twins integrating geometric, dynamic, and physical properties. He has pioneered methods like feed-forward 3D reconstruction (Flash3D), amodal completion (Amodal3R), and physics-aware generative models (DSO). Notable awards include the Singapore NRF Fellowship (2025), DAAD Ainet Fellowship (2024), and MSCA Fellowship (2024). His work spans over 30 peer-reviewed publications in top venues like CVPR, ECCV, NeurIPS, and ICCV, with contributions to open-source projects like CVQ-VAE on GitHub. Current openings include PhD, postdoc, and research assistant positions focused on advancing physical-aware AI systems and generative modeling.
Jia-Bin Huang is an Associate Professor in the Department of Computer Science at University of Maryland, College Park , with a secondary appointment at the University of Maryland Institute for Advanced Computer Studies . His work bridges computer vision , computer graphics , and machine learning . His research focuses on 3D scene reconstruction , neural radiance fields , generative models , and multimodal foundation models . He has made significant contributions to video super-resolution , text-driven 3D modeling , and inverse rendering techniques. 15 recent publications (2024-2025) at top venues: CVPR , NeurIPS , SIGGRAPH Asia , 3DV , and ECCV Pioneering work in Urban Scene Inverse Rendering , Generative Video Editing , and 3D Human Digitization He has received multiple awards including the 3M Non-Tenured Faculty Award , ETRA Best Paper , and NSF Grants . His lab trains 12 PhD students and has graduated 18 Masters/PhD students now at institutions like Stanford , Meta , and Google .
Weiyu Liu is an incoming Assistant Professor at the Kahlert School of Computing , University of Utah. Previously, he was a Postdoctoral Scholar at Stanford University in the CogAI group and Stanford Vision and Learning Lab (SVL), after completing his Ph.D. in Robotics at Georgia Institute of Technology under the supervision of Sonia Chernova. Ph.D. in Robotics (Georgia Tech) Bachelor's in Electrical Engineering (Georgia Tech) His research focuses on developing robots that can perceive, model, and interact with the real world through structured knowledge representations grounded in language and sensorimotor data. Key areas include language-guided manipulation , long-horizon task execution , and semantic reasoning frameworks for robotic systems. His recent work (2024) explores: Language-annotated demonstration integration (BLADE framework) 3D visual grounding with concept learners Embodied decision-making benchmarks Long-horizon inference challenges 4D instruction grounding from videos Scientific contributions include the RSS Pioneer (2023) recognition and First Place in Fetch It! Mobile Manipulation Challenge (2019) . He advocates for weekly individual mentoring , open research dissemination, and holistic student development in both academic and personal growth.
Taein Kwon is a postdoctoral research fellow at the Visual Geometry Group (VGG) within the Department of Engineering Science at the University of Oxford, working under Prof. Andrew Zisserman. Previously, he completed his PhD at ETH Zurich under Prof. Marc Pollefeys and earned master's and bachelor's degrees from UCLA and Yonsei University, respectively. His educational background includes: Bachelor's in Electrical Engineering from Yonsei University, Seoul, Korea Master's degree from UCLA PhD from ETH Zurich (defended July 2024) His research spans Egocentric Vision, Action Recognition, Hand-object Interaction, Video Understanding, AR/VR, and Multi-modal Learning, with emphasis on first-person perspective analysis for AI assistants and human-computer interaction. His work integrates 3D reconstruction, pose estimation, and multimodal signals to model complex human activities and physical interactions. Analysis of his 2021-2025 publications reveals a consistent focus on egocentric vision datasets (H2O, HoloAssist, EgoPressure) and novel frameworks for hand-object interaction, action recognition, and gesture understanding. His research demonstrates strong interdisciplinary connections between computer vision, robotics, and human-centered AI, with increasing emphasis on pressure sensing, co-speech gestures, and cross-modal alignment. His scientific recognition includes: CVPR Egovis 2022/2023 Distinguished Paper Award for HoloAssist (July 2024) SNSF Postdoc.Mobility fellowship (May 2024) He actively mentors students on egocentric vision projects, supervising master's theses, semester projects, and collaboration initiatives leading to publications at top conferences. His research is supported by the SNSF fellowship and industry collaborations with Meta Reality Labs and Microsoft Research. As part of Oxford's Visual Geometry Group, he contributes to cutting-edge computer vision research while maintaining strong ties with ETH Zurich's computer vision community through ongoing collaborations and dataset development efforts.
Waldemar Celes Filho is an Associate Professor in the Department of Computer Science at Pontifical Catholic University of Rio de Janeiro (PUC-Rio) and serves as Director of the Tecgraf Institute/PUC-Rio. With a career spanning over three decades, he has established himself as a leading researcher in computer graphics and scientific visualization. His educational background includes a Civil Engineering degree from UFRJ (1986), a Master's in Civil Engineering from PUC-Rio (1990), a Doctorate in Computer Science from PUC-Rio (1995), and postdoctoral studies in Computer Graphics at Cornell University (1995-1997). Dr. Celes Filho's research focuses primarily on Computer Graphics with special emphasis on Scientific Visualization, Numerical Simulation, Distributed Visualization, and Real-Time Rendering. He is particularly known for his work on visualization techniques for black oil reservoir models and as a co-creator of the Lua programming language. His research has resulted in over 50 publications spanning nearly three decades, with consistent output continuing through 2025. His recent publications demonstrate a strong trend toward applying advanced visualization techniques to complex industrial problems, particularly in petroleum engineering and construction informatics. His work bridges theoretical computer graphics with practical applications in engineering domains, showing particular strength in volume rendering, CAD model visualization, and distributed rendering systems. As Director of the Tecgraf Institute, he leads research initiatives that connect academic work with industry applications, fostering collaborations that translate visualization research into practical tools. Dr. Celes Filho has mentored numerous students who have become co-authors on his publications, including Paulo Ivson, Fábio Markus Miranda, and Lucas Caracas de Figueiredo, among others. His work continues to be influential in both academic and industrial settings.
Dr. Zichun Zhong is an Associate Professor and Graduate Program Director in the Department of Computer Science at Wayne State University's James and Patricia Anderson College of Engineering. He earned his Ph.D. from the University of Texas at Dallas and completed postdoctoral training at UT Southwestern Medical Center. His research focuses on geometric modeling, computer graphics, medical image processing, and visualization technologies. Research encompasses: Geometric modeling of surfaces and volumes 3D computer vision and reconstruction Medical image segmentation and visualization Virtual/augmented reality applications GPU-accelerated algorithms Awards and honors include NSF CAREER and CRII awards, Faculty Research Excellence Award, and Excellence in Teaching recognition. He serves as Technical Paper Chair for Shape Modeling International conferences and associate editor for multiple journals. Current doctoral advisees: Shiman Zhou, Hongbo Li, Haikuan Zhu, and Sikai Zhong. Notable alumni include researchers at Samsung NEON, Skoltech, and General Motors.
Professor Adrian Hilton is a distinguished faculty member at the University of Surrey, serving as Director of the Centre for Vision, Speech and Signal Processing (CVSSP) and Director of the Surrey Institute for People-Centred AI. He is affiliated with the School of Computer Science and Electronic Engineering and leads the Visual Media Research Lab (V-Lab). His research focuses on pioneering next-generation 4D computer vision technologies that enable machines to understand and model dynamic real-world scenes. Key areas include 3D/4D shape capture, computer vision, machine learning, graphics, and animation for applications in sports analysis, film/TV production, virtual reality, and medical imaging. His work bridges the gap between real and computer-generated imagery, with notable contributions in volumetric capture, motion capture, and free-viewpoint video. Hilton's recent publications demonstrate a strong trend toward multimodal integration, particularly combining audio and visual processing for spatial audio applications, while advancing 4D reconstruction techniques for human performance capture. His work increasingly incorporates transformer architectures and neural rendering techniques for improved illumination estimation, shadow modeling, and multi-view consistency. Scientific Awards and Recognition Two EU IST Innovation Prizes Manufacturing Industry Achievement Award Royal Society Industry Fellowship (2008-2011) Royal Society Wolfson Research Merit Award in 4D Vision (2013-2018) Fellow of the Royal Academy of Engineering (FREng) Fellow of the International Association for Pattern Recognition (FIAPR) Fellow of the Institution of Engineering and Technology (FIET) Hilton actively mentors PhD and post-doctoral researchers through his leadership of CVSSP, which has a grant portfolio exceeding £31M and comprises 170 researchers. He has successfully commercialized several technologies, including systems used by the BBC for sports commentary visualization. His research collaborations span major industry partners including BBC, BT, Sony, Framestore, and The Foundry. He co-founded the G3 Games forum and the CVMP Conference on Visual Media Production, demonstrating strong engagement with the creative industries. Current research projects include the S3A Programme Grant in Future Spatial Audio and InnovateUK's ALIVE project for 360 video reconstruction.
Emily Whiting is an Associate Professor of Computer Science at Boston University and Director of the Shape Design & Computation Lab. She also serves as Director of PhD Admissions and Co-Director of the BU Computer Graphics Lab. Her research focuses on computational fabrication, architectural geometry, and computer-aided design, bridging digital geometry processing, engineering mechanics, and rapid prototyping. She holds a PhD from MIT (2012), an SM in Design & Computation from MIT (2006), and a BASc in Engineering Science from the University of Toronto (2004). Previously, she was faculty at Dartmouth and a Marie Curie Postdoctoral Fellow at ETH Zurich. Her research interests include 3D printing optimization, structural design for fabrication, and tools for functionally-valid object creation. Notable projects include work on elastic garments, climbing experience replication, and print-wind instrument design. Her work has been featured on TEDx and PBS NOVA, and she has received awards such as the NSF CAREER Award and Sloan Research Fellowship. Education: PhD (MIT), SM (MIT), BASc (University of Toronto) Labs: Shape Design & Computation Lab, BU Computer Graphics Lab Key Projects: Knitting 4D garments, Environment-Scale Fabrication, Thermal-comfort casts Recent professional activities include program committee roles at SIGGRAPH 2025 and UIST 2024, and serving as Program Co-Chair for Pacific Graphics 2024. She advises a team of PhD and MS students, with alumni now in academia and tech industries.
Isabella Di Lenardo is a Lecturer and Scientist at the Digital Humanities Institute (DHI) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as the coordinator of the EPFL Time Machine Unit and the European Local Time Machines. She holds affiliations across multiple departments, including DHI-GE, SAR-ENS, SHS-ENS, and EDDH-ENS, reflecting her interdisciplinary role in teaching and research. Her educational background includes a PhD in Theories and Art History, with postdoctoral and faculty experience at institutions such as INHA (Paris), EPFL, and IUAV (Venice). Her research spans Digital Humanities, Art History, Urban History, and GIS , with a focus on digital urban reconstruction, historical cadastres, and AI applications in cultural heritage. She employs advanced computational methods including machine learning, 4D modeling, and semantic segmentation to analyze historical maps, cadastral records, and art archives. Her work bridges humanities scholarship with computer science, particularly in reconstructing urban evolution and analyzing visual patterns. The recent publications reveal a consistent trend in AI-powered historical data analysis , especially in processing non-standardized historical documents, reconstructing urban spaces, and developing open-source tools for digital heritage. Her work frequently involves large-scale datasets from Venice, Lausanne, Paris, and Jerusalem, demonstrating a transnational and interdisciplinary approach. She has contributed to significant collaborative projects such as the Venice Time Machine , Parcels of Venice , and Time Machine Organization , often acting as a principal investigator or project leader. Her role involves coordinating diverse teams of researchers, engineers, and cultural institutions. Scientific contributions include: Development of the Morphograph tool for visual pattern recognition in art archives Automatic vectorization and analysis of Napoleonic cadastres Creation of 4D models for historical cities AI-driven text and pattern extraction from historical maps Building discovery engines for digital art history She actively teaches ex cathedra courses in Digital Urban History and Art History at EPFL and internationally. Her work in grants and projects emphasizes open data, reproducibility, and interdisciplinary collaboration. She has led research funded by organizations supporting digital heritage innovation. She is a key member of the Digital Humanities Laboratory at EPFL and the Time Machine Organization , where she fosters collaboration between computer scientists, historians, and cultural institutions. Her work in the Replica Project and ARCHiVe center highlights her leadership in digitizing and making accessible large art historical archives.
Luis Merino Cabañas is a Professor at the Universidad Pablo de Olavide , affiliated with the Deporte e Informática department and leading the SRL Service Robotics Laboratory . His research focuses on robotics, systems engineering, and automation, with a specialization in human-robot interaction and path planning. Education : PhD in Systems Engineering from the Universidad de Sevilla (2007), where his thesis explored cooperative perception techniques for multiple unmanned aerial vehicles in forest fire detection. Research Trends : Recent work (2023–2025) emphasizes 3D path planning, sensor fusion (LiDAR, radar, inertial systems), neural distance fields for safe navigation, and socially aware robotics. His studies integrate AI, genetic programming, and multi-modal perception for applications in construction, healthcare, and GNSS-denied environments. Labs & Teams : He leads the SRL Service Robotics Laboratory , contributing to projects like the Skyeye team and BIM2ROS integration for construction robotics.
Dr. Armin Mustafa is an Associate Professor in Computer Vision and AI at the University of Surrey, where he holds a prestigious Royal Academy of Engineering Research Fellow position. He is affiliated with the Centre for Vision, Speech and Signal Processing (CVSSP), the School of Computer Science and Electronic Engineering, and the Surrey Institute for People-Centred Artificial Intelligence (PAI). His research focuses on developing AI systems for visual understanding of complex dynamic scenes, with applications in entertainment, autonomous systems, and augmented/virtual reality. Dr. Mustafa completed his PhD in general dynamic scene reconstruction from multi-view videos in 2016 from the University of Surrey under the supervision of Prof. Adrian Hilton. Prior to his doctoral studies, he worked for three years (2010-2013) at Samsung Research Institute in Bangalore, India, in the field of Computer Vision. His research expertise spans Computer Vision, Scene Understanding, 3D/4D Vision, Virtual Reality, Light Fields, Machine Learning, Video Captioning, Augmented Reality, Artificial Intelligence, and Audio-visual Video Understanding. Dr. Mustafa has pioneered advances in 4D vision, NLP, and Scene Understanding over the past decade, with a particular focus on enabling machines to model and interpret real-world environments for socially beneficial applications. His work bridges theoretical advances in computer vision with practical applications in media production, virtual reality, and autonomous systems. Analysis of Dr. Mustafa's recent publications reveals a strong focus on multimodal learning, particularly the integration of audio and visual information for scene understanding. His work spans diverse areas including shadow detection and removal, audio event classification, video captioning, person image generation, and dynamic scene reconstruction. A notable trend is his exploration of transformer architectures for both vision and audio tasks, as well as the application of self-supervised learning techniques to reduce dependency on labeled data. Dr. Mustafa has received numerous prestigious awards: 2018 - Research Fellowship, The Royal Academy of Engineering, UK 2017 - Young Researcher award, CVPR 2016 - Doctoral Consortium grant, CVPR 2015 - BMVA travel grant for ICCV 2014 - Set-Squared Research to Innovator grant 2013 - Overseas Research Scholarship, FEPS, The University of Surrey 2010 - Cadence Silver Medal, Indian Institute of Technology, Kanpur As a dedicated mentor, Dr. Mustafa supervises several PhD students working on cutting-edge topics including multi-person reconstruction, audio-visual scene understanding, and automatic storyboard generation. His research is supported by significant grants including a £15 million UKRI Prosperity Partnership with the BBC (AI4ME), a 5-year Royal Academy of Engineering fellowship (4D Vision for Perceptive Machines), and multiple projects with industry partners such as Figment Productions and Foundry. Dr. Mustafa is an active member of the Centre for Vision, Speech and Signal Processing (CVSSP), one of the world's leading research centers in vision, speech, and signal processing. He also contributes to the Surrey Institute for People-Centred Artificial Intelligence (PAI), where he serves as a Surrey AI Fellow. His work often involves collaboration with industry partners and other academic institutions across Europe.
David E. Breen is a Professor in the Department of Computer Science within the College of Computing & Informatics (CCI) at Drexel University. He leads the Geometric Biomedical Computing Group and is affiliated with the Metadata Research Center and the Center for Biological Discovery from Big Data. His research spans interdisciplinary domains including biomedical image informatics, geometric modeling, textile modeling, and bio-inspired self-organization algorithms. Education: PhD, Computer and Systems Engineering, Rensselaer Polytechnic Institute MS, Computer and Systems Engineering, Rensselaer Polytechnic Institute BA, Physics, Colgate University His research interests focus on computational methods for biomedical applications, including shape and image analysis for cancer diagnosis, 3D reconstruction of biological tissues, and video analysis of animal behavior. He also investigates geometric modeling techniques for textiles and self-organizing systems. His work integrates computer science with biology, medicine, and engineering to solve complex problems in biomedical computing. The recent publications highlight a strong trend in computational modeling of textiles, biomedical image informatics, and AI-driven data analysis. Key themes include geometric modeling of knitted fabrics, deep learning for medical image classification, agent-based modeling of cancer metastasis, and metadata generation for biological image collections. His work bridges fundamental geometric algorithms with practical applications in healthcare and digital archives. Scientific Awards: No specific awards mentioned in the provided text. Breen has advised numerous students and collaborators across multiple domains, particularly in biomedical computing and textile modeling. His research has been supported through affiliations with major centers and collaborations with institutions such as Johns Hopkins University and the Max Planck Institute. He has been involved in projects related to NSF Center for Visual & Decision Informatics and has contributed to over 100 technical publications. He leads the Geometric Biomedical Computing Group , which conducts research at the intersection of biology, medicine, engineering, and computer science. The group develops algorithms and software for geometry-related computing problems in biomedical applications. Collaborations include the Drexel Integrated Laboratory for Cellular Tissue Engineering, Dr. Dan Marenda's Lab, and Dr. Aleister Saunder's Lab in Drexel's Biology Department.
Jianwen Su is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he has been since 1990. He holds a Ph.D. in Computer Science from the University of Southern California and B.S./M.S. degrees from Fudan University in China. His research focuses on databases, formal verification, web services, business process management (BPM), and workflow systems. He has contributed to data-centric workflow modeling, artifact-based BPM frameworks, and tools like the Web Service Analysis Tool (WSAT). Adjunct professorships at Peking, Fudan, and Donghua Universities in China. Key roles: General co-chair of ICSOC 2013, PC chair of PODS 2009, and general chair of SIGMOD 2001. Recipient of the 2000 Outstanding Faculty Award (UCSB College of Engineering) and IBM Faculty Awards (2007, 2008). Research spans database query languages, incremental query evaluation, spatial databases, and formal verification techniques for software systems. Current emphasis is on data modeling for workflows and BPM systems.
Leonid Goubergrits is a Professor of Cardiovascular Modeling and Simulation at the Einstein Center Digital Future and Charité – Universitätsmedizin Berlin . With a background in applied mathematics and physics from the Moscow Institute of Physics and Technology, he has dedicated his career to applying computational fluid dynamics (CFD) to cardiovascular medicine since immigrating to Germany in 1995. His work bridges fundamental research and clinical applications, aiming to integrate numerical models into everyday medical practice to enhance diagnostics and reduce invasiveness. Doctorate at Technische Universität Berlin (2000) Habilitation at Technische Universität Berlin (2016) His research spans blood flow modeling in coronary vessels, cerebral aneurysms, heart valves, and the aorta, alongside artificial organ development and blood damage modeling . He leads a research group at Charité and the German Heart Center Berlin, focusing on patient-specific simulations and their translation to clinical settings. Recent publications highlight his work on deep learning integration for hemodynamic analysis, 4D Flow MRI validation , and medical device optimization using computational models. His team’s research includes virtual therapy planning for aortic valve replacements, hemolysis modeling , and pulmonary artery pressure sensors . Leonid actively contributes to education, redesigning TU Berlin’s Fluid Mechanics in Medicine curriculum and fostering interdisciplinary collaboration between engineers, physicians, and computer scientists. His vision emphasizes the digital transformation of medicine through computational modeling and simulation.
Robert Collins is an Associate Professor in Computer Science and Engineering, with a focus on computer vision and human motion analysis. His research spans topics such as human pose estimation, crowd dynamics, stability quantification, and 3D scene understanding. He has contributed extensively to tracking algorithms, motion modeling, and applications in biomechanics and surveillance. Notable projects include NSF-funded work on crowd analysis, partial body model fitting, and sensor network overlays. His recent publications address stability from video, alignment of pose sequences, and vanishing point detection. Research interests emphasize vision-based human motion analysis , tracking in complex scenarios , and 3D reconstruction . Trends in his work include leveraging mean-shift belief propagation , spatiotemporal models , and deep learning for applications in biomechanics, urban scenes, and rehabilitation engineering.
