Sponsored by Web3D Consortium, University of North Dakota, HBKU and Korea Standards Association
Shape the Future of 3D Web Tools, AI and Animation and Win cash prizes up to $1,200
Submission deadline: September 30, 2026. To submit, please go to the submission page
Dr. Zhihe Lu - Conference Chair
Assistant Professor, Division of Information & Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar
PhD in Computer Vision, University of Surrey; MSc in Computer Technology, Institute of Automation (Chinese Academy of Sciences); BA in Automation, Zhengzhou University.
Specializes in machine learning and computer vision, with a focus on transfer learning, few-shot learning, domain adaptation, and vision–language models.
Has published 20+ technical papers in top venues such as CVPR, ICCV, ECCV, NeurIPS, ICML, ACM MM, and leading journals including IEEE Transactions on Image Processing and Pattern Recognition.
Previously worked as a Research Fellow in the Department of Electrical and Computer Engineering at the National University of Singapore, collaborating closely with Prof. Xinchao Wang.
Completed his PhD under the supervision of Prof. Tao Xiang and Prof. Yi-Zhe Song, and his master’s studies under Prof. Ran He and Prof. Zhaoxiang Zhang.
Current research includes efficient tuning and deployment of foundation models and multimodal AI systems, with applications such as high-precision medical diagnosis.
Research interests span computer vision, transfer learning, few-shot learning, efficient adaptation of large models, and robust vision-language systems.
Dr. Jens Schneider - Conference Chair
Associate Professor in Data Science, Division of Information & Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar
Holds a PhD in Computer Science from the Technical University of Munich (2009) and a diploma/MSc in Computer Science from RWTH Aachen University (2004).
Specializes in visual computing, including interactive and GPU-based visualization, GPU-friendly data compression, hierarchical and parallel algorithms, and computer vision.
Former Staff Scientist at the Visual Computing Center, King Abdullah University of Science and Technology (KAUST), where he previously served as Postdoctoral Research Fellow and Research Scientist.
His teams won the IEEE Visualization Contest in two consecutive years (2005 and 2006).
Co-author of several award-winning papers in visual computing and related areas.
Member of professional societies including IEEE, ACM, and the scientific research honor society Sigma Xi.
Active researcher with dozens of publications spanning topics such as efficient geometry compression, spatial data structures for GPUs, and AI-based medical image analysis.
Dr. Marco Agus - Program Chair
Associate Professor, Division of Information & Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar
Holds an MSc in Electronic Engineering and a PhD in Mechanical Design from the University of Cagliari, Italy.
Specializes in visual computing, including haptics and visual rendering for medical applications, real-time exploration of massive 3D models, and machine-learning methods for scientific and biomedical data.
Previously served as a Research Engineer at the Visual Computing Center, King Abdullah University of Science and Technology (KAUST), Saudi Arabia.
Worked for many years as a Research Scientist and Expert Researcher in the Visual Computing groups at CRS4 (Center for Advanced Studies, Research and Development in Sardinia), Italy.
Has taught tutorials and courses at major venues such as ACM SIGGRAPH, IEEE CVPR, and Eurographics.
Regularly serves as program committee member, reviewer, chair, and associate editor for leading conferences and journals in visual computing and computer graphics.
Dr. Giovanni Pintore - Program Chair
Senior/Principal Researcher, Visual Computing Group, CRS4, Cagliari, Italy
Senior researcher and engineer in the Visual and Data-intensive Computing / Visual Computing group at CRS4.
Holds a Laurea/MSc degree in Electronic Engineering and a PhD in Information and Communication Technologies.
Leads and contributes to research projects on AI-based indoor scene understanding, 3D reconstruction, and digital twins from panoramic and spherical images.
Has authored more than 50 scientific publications in computer graphics, computer vision, and visual computing, including work on depth estimation, indoor layout recovery, and large-scale 3D model processing.
Research interests include deep learning for 360° imaging, automatic 3D reconstruction of indoor environments, multiresolution 3D representations, and interactive visualization systems for smart cities, security, and space applications.
Dr. Pere-Pau Vazquez - Program Chair
Associate Professor, Computer Science Department, Universitat Politècnica de Catalunya (UPC), Spain
Associate professor in the ViRVIG (Visualisation, Virtual Reality and Graphics) research group at UPC’s Facultat d’Informàtica de Barcelona.
Holds a PhD in Software and a degree in Computer Science from Universitat Politècnica de Catalunya.
Researches visual computing, including information visualization, scientific and medical visualization, volume rendering, and molecular visualization.
Has authored numerous publications on topics such as viewpoint selection, ambient occlusion, illustrative rendering, and visualization techniques for large-scale and medical datasets.
Teaches courses in information visualization, fast realistic rendering, scientific visualization, and medical data visualization at undergraduate and master’s levels.
Dr. Adel Bibi - Program Chair
Senior Researcher in Machine Learning and Computer Vision, Department of Engineering Science, University of Oxford, UK
Senior Researcher in the Torr Vision Group at Oxford, focusing on machine learning, computer vision, and AI safety.
Research Member of Common Room at Kellogg College and former Junior Research Fellow there.
Leads a research group on trustworthy and secure AI, with emphasis on robustness, certification, adversarial attacks/defenses, and continual learning for large models.
Previously postdoctoral researcher and now long-term collaborator with the Torr Vision Group.
Holds a PhD and MSc in Electrical Engineering (machine learning / computer vision track) from KAUST, and a BSc in Electrical Engineering from Kuwait University.
Recipient of several major awards, including an Amazon Research Award (2022), Google Gemma-related academic award, and a UK AI Safety / Security grant, alongside multiple best paper and outstanding reviewer awards at top ML and CV conferences.
Has published extensively in leading venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, and TPAMI, with several oral and spotlight papers.
Dr. Dena Al-Thani - Treasurer
Associate Professor, Director of Interdisciplinary Programs, and Co-Founder of the A-Sense Center of Excellence, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar
PhD in Computer Science from Queen Mary University of London, specializing in Human–Computer Interaction and inclusive design.
Leads research at the intersection of accessibility, inclusive design, eHealth, and human–AI interaction, with a strong focus on supporting marginalized and neurodivergent communities.
Co-founded the Autism Sensing Center of Excellence (A-Sense), advancing AI and sensing technologies to support autistic individuals and their families.
Actively publishes in high-impact journals and international conferences on topics such as digital wellbeing, explainable AI, assistive technologies, and inclusive digital systems.
Frequently invited as an expert speaker and panelist on inclusion, accessibility, and ethical AI, contributing to national and international initiatives on digital inclusion and disability.
Dr. Alberto Jaspe-Villanueva - Tutorials Chair
Research Scientist, High-Performance Visualization Group, Visual Computing Center, King Abdullah University of Science and Technology (KAUST), Saudi Arabia
Computer science researcher and engineer specializing in computer graphics, visual computing, and real-time rendering of massive 3D models.
Research focuses on large-scale model exploration, real-time visualization, digital heritage, and immersive environments from panoramic and 3D data.
Has authored numerous publications on topics such as indoor reconstruction, sparse voxel data structures, panoramic view graphs, and interactive exploration of cultural heritage models.
Previously Expert Researcher in the Visual Computing Group at CRS4 (Italy) and Marie Curie Early Stage Researcher working on real-time massive model exploration.
Developed early research career at the VideaLAB group, University of A Coruña (Spain), where he worked on terrain rendering, virtual reality, and natural interaction, completing his BSc in Computer Science and MSc in High-Performance Computing before earning a PhD in Computer Science.
Dr. Mariam Bahameish - Tutorials Chair
Lecturer, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar
PhD in Computer Science from Queen Mary University of London; MSc in Computing from Imperial College London; BSc in Computer Engineering from Qatar University.
Researches at the intersection of human–computer interaction, cognitive science, and artificial intelligence, with a focus on digital health and wellbeing.
Works on projects involving physiological sensing (e.g., heart rate variability biofeedback), immersive and virtual reality systems, and accessible, user-centred technologies.
Co-authors publications on topics such as biofeedback for working memory, social media and explainable AI, and gamified digital learning in Arabic mathematics education.
Dr. Marwa Qaraqe - Tutorials Chair
Associate Professor, Division of Information & Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar
PhD and MSc in Electrical Engineering from Texas A&M University (USA); BSc in Electrical Engineering (summa cum laude) from Texas A&M University at Qatar.
Co-founder of the Autism Sensing Center of Excellence (A-Sense), advancing AI-enabled sensing and assessment for autistic children.
Researches lightweight security for wireless networks, machine learning for wireless communications, AI-enabled technologies for personalized learning and intervention in autism, and predictive analytics.
Has authored more than 180 research outputs, with work spanning wireless communications, physical-layer security, federated learning, and AI for healthcare and education.
Lead or co-lead investigator on multi-million-dollar competitive research grants and recipient of awards such as the IEEE GLOBECOM Best Paper Award and the Richard E. Wing Award for Excellence in Research.
Dr. Noora Fetais - Industrial Use Cases Chair
Associate Professor, Department of Computer Science and Engineering, College of Engineering, Qatar University, Qatar
Expert in emerging technologies with a focus on cybersecurity, blockchain, and visualization.
Founding President (and previously Founding Secretary-General) of the Arab Association for Cyber Security.
Former Director of the KINDI Center for Computing Research and the first woman to chair the Faculty Senate at Qatar University.
Represents Qatar University at international bodies such as the ITU (UN) and Qatar Internet Exchange Point (Qatar IXP).
Holds a PhD in Informatics from the University of Sussex (UK) and an Executive Master’s in Leadership from Georgetown University (US).
Leads and collaborates on large, multi-institutional research projects in cybersecurity and emerging technologies, and is an active mentor and advocate for women in cyber security regionally and internationally.
Dr. Abdullatif Albaseer - Demo Chair
Laboratory Manager and Researcher, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar
Holds a PhD in Computer Science and Engineering from HBKU, with a dissertation on federated learning over wireless edge networks, and an MSc in Computer Networks from King Fahd University of Petroleum and Minerals.
Research focuses on deep reinforcement learning, federated learning at the wireless edge, smart grid cybersecurity, and proactive network defense.
Has published widely on energy-efficient and fair federated edge learning, privacy-preserving federated learning, and deep learning–based cybersecurity for smart grid and communication networks.
Active collaborator within the Information & Computing Technology division at HBKU, contributing to multi-disciplinary projects on AI, wireless communications, and secure edge intelligence.
Dr. Mohamad Hassan Fadi Hijab - Web3D Chair
Laboratory Manager, College of Science and Engineering, Hamad Bin Khalifa University (HBKU), Qatar
Holds a PhD in Computer Science and Engineering (HBKU, 2024), an MSc in Data Analytics (HBKU, 2021), a BS in Computer Science (AUCE, 2018), and a BS in Mathematics (LIU, 2020).
Research focuses on human–computer interaction, AI and machine learning, and computer vision for autism, including eye-tracking, pose estimation, and object detection in play-based and learning contexts.
Leads and contributes to projects on joint engagement, preference assessment, and inclusive assessment for autistic learners, often combining sensing technologies, VR, and learning analytics.
Has published in venues such as CoDesign, Frontiers in Education, International Journal of Human–Computer Interaction, JMIR, BCS HCI, and LNCS (HCII/INTERACT).
Recipient of the Mada Innovation Award (2022) for the MAAN accessibility-focused application.
Experienced educator and tutor in mathematics and computer science, and teaching assistant for courses on ICT accessibility and statistics for science and engineering.
Actively serves as a reviewer and collaborator on interdisciplinary projects spanning autism, inclusive technology, AI, and education.