KAUST researchers are exploring the link between nutrition and brain-energy metabolism to address cognitive decline, dementia, and Alzheimer’s disease. Dr. Pierre Magistretti and Dr. Johannes le Coutre are collaborating on ways to merge brain-energy metabolism research into the field of nutrition. They published an article entitled “Goals in Nutrition Science 2015-2020” in the journal Frontiers in Nutrition. Why it matters: This research could lead to nutritional interventions to hinder or prevent cognitive decline, offering a new approach beyond traditional drug treatments.
Microsoft Azure AI CTO Dr. Xuedong Huang will speak at the MBZUAI Executive Program on AI-powered communications. Huang will share his experience in advancing Microsoft's AI stack, from deep learning infrastructure to new user experiences. He has over 170 U.S. patents and has contributed to speech technology, including Windows SAPI and Azure Speech. Why it matters: This talk can help foster knowledge transfer and collaboration between a global AI leader and the UAE's flagship AI university.
A professor from Nanyang Technological University (NTU), Singapore gave a talk at MBZUAI about "Just-Noticeable Difference (JND)" models in visual intelligence. The talk covered visual JND models, research and applications, and future opportunities for JND modeling. JND can help tackle big data challenges with limited resources by focusing on user-centric and green systems. Why it matters: Exploring JND could lead to advancements in AI applications related to visual signal processing, image synthesis, and generative AI in the region.
A new benchmark, LongShOTBench, is introduced for evaluating multimodal reasoning and tool use in long videos, featuring open-ended questions and diagnostic rubrics. The benchmark addresses the limitations of existing datasets by combining temporal length and multimodal richness, using human-validated samples. LongShOTAgent, an agentic system, is also presented for analyzing long videos, with both the benchmark and agent demonstrating the challenges faced by state-of-the-art MLLMs.