The article discusses immersive analytics, which uses VR and AR to visualize data in 3D and embed it into the user's environment, and reviews systems and techniques from the Data Visualisation and Immersive Analytics lab at Monash University. It explores the concept of "embodied sensemaking" and its potential to improve how people work with complex data. Professor Tim Dwyer directs the Data Visualisation and Immersive Analytics Lab at Monash University. Why it matters: Immersive analytics could significantly enhance data comprehension and decision-making across various sectors in the Middle East, where large-scale projects and smart city initiatives generate vast datasets.
This article discusses the evolution of mobile extended reality (MEX) and its potential to revolutionize urban interaction. It highlights the convergence of augmented and virtual reality technologies for mobile usage. A novel approach to 3D models, characterized as urban situated models or “3D-plus-time” (4D.City), is introduced. Why it matters: The development of MEX and 4D.City could significantly enhance user experience and analog-digital convergence in urban environments, offering new possibilities for human-computer interaction.
KAUST alumnus Ronell Sicat (M.S. '10, Ph.D. '15) is developing immersive data visualization tools using augmented and virtual reality (AR/VR). After a postdoc at Harvard, Sicat returned to KAUST as a research scientist in the Visual Computing Center. Sicat developed a tool called DXR to help researchers prototype immersive visualizations. Why it matters: This highlights KAUST's role in fostering talent and innovation in AR/VR, a growing area with applications across various sectors in Saudi Arabia.
A computer science vision involves computing devices becoming proactive assistants, enhancing various aspects of life through user digitization. Current devices provide coarse digital representations of users, but there's significant potential for improvement. Karan, a Ph.D. candidate at CMU, develops technologies for consumer devices to capture richer user representations without sacrificing practicality. Why it matters: Advancements in user digitization can lead to improved extended reality experiences, health tracking, and more productive work environments, enhancing the utility of consumer devices.
MBZUAI researchers developed Data Wise, an AI platform that provides instant data analytics for businesses. The platform uses AI agents and LLMs to analyze raw customer data and generate actionable recommendations. Data Wise aims to address the shortage of data scientists, particularly in the UAE and GCC. Why it matters: This platform democratizes access to advanced analytics, empowering businesses in the region to make data-driven decisions without relying on scarce technical expertise.
MBZUAI's Dr. Hao Li is working on using AI and 3D telepresence to transform communication, work, and education by replacing physical transportation with virtual teleportation. His research focuses on the intersection of computer graphics, computer vision, and AI, specifically virtual avatar creation and facial performance capture. Li aims to improve communication using AI to achieve what cannot be done in real life. Why it matters: This research has the potential to reduce carbon footprints by enabling remote work and virtual collaboration, while also positioning MBZUAI and the UAE as leaders in AI-driven metaverse technologies.
MBZUAI's Metaverse Lab is developing AI algorithms for photorealistic virtual humans and dynamic environments. Hao Li, Director of the lab, envisions using the metaverse for immersive learning experiences related to history and culture. He is also working on tools to prevent deepfakes and other cyberthreats. Why it matters: This research at MBZUAI aims to advance AI and immersive technologies for education and address potential risks in the metaverse.
Researchers at MBZUAI developed a method to measure vital signs using webcams by analyzing color intensity changes in facial blood flow. They built a digital twin system that uses machine learning to combine heart rate, respiratory rate, and blood oxygen level measures. The system displays real-time vital sign information, enabling remote patient triage. Why it matters: This research contributes to the advancement of telemedicine, potentially improving healthcare access in underserved regions and aligning with UN Sustainable Development Goal #3.