MBZUAI board member Sir Michael Brady and Weizmann Institute's Shimon Ullman lectured in the fourth module of MBZUAI’s Executive Program on December 11. Brady led a session on 'Artificial Intelligence (AI) and Image Analysis,' while Ullman presented on ‘AI and Human Intelligence: Lessons From Computer Vision.’ The 12-week Executive Program aims to educate high-level decision makers in AI, supporting the UAE's AI leadership mission. Why it matters: Showcases MBZUAI's commitment to attracting top global talent and fostering AI education for leadership in the UAE.
The content discusses KAUST and its founder King Abdullah. It mentions applying to KAUST and KAUST Discovery. Why it matters: This is a routine update about KAUST.
Eran Segal from Weizmann Institute of Science presented The Human Phenotype Project, a large-scale prospective cohort with over 10,000 participants. The project aims to identify novel molecular markers and develop prediction models for disease onset using deep profiling. The profiling includes medical history, lifestyle, blood tests, and molecular profiling of the transcriptome, genetics, microbiome, metabolome and immune system. Why it matters: Such projects demonstrate the growing focus on personalized medicine in the region, utilizing advanced AI and machine learning techniques for disease prevention and treatment.
Professor Eran Segal presented The Human Phenotype Project, a longitudinal cohort study with over 10,000 participants. The project aims to identify molecular markers and develop prediction models for disease using deep profiling techniques including medical history, lifestyle, blood tests, and microbiome analysis. The study provides insights into drivers of obesity, diabetes, and heart disease, identifying novel markers at the microbiome, metabolite, and immune system level. Why it matters: Such large-scale phenotyping initiatives could inform personalized medicine approaches relevant to the Middle East's specific health challenges.
Shahar Harel, Head of AI at Quris, presented a BIO-AI approach to drug safety assessment using a 'patient-on-a-chip' platform. This platform simulates the human body and generates high-frequency microscopy and biochemical data on drug interactions, considering patient genomics and ethnicity. The data is used to train multimodal deep learning models to predict drug safety and provide patient-specific recommendations. Why it matters: This approach offers a potential alternative to animal models, promising faster and more personalized drug development while reducing safety concerns.
Professor Hava Siegelmann, a computer science expert, is researching lifelong learning AI, drawing inspiration from the brain's abstraction and generalization capabilities. The research aims to enable intelligent systems in satellites, robots, and medical devices to adapt and improve their expertise in real-time, even with limited communication and power. The goal is to develop AI systems applicable for far edge computing that can learn in runtime and handle unanticipated situations. Why it matters: This research could lead to more resilient and adaptable AI systems for critical applications in remote and resource-constrained environments, with potential benefits for various sectors in the Middle East.
KAUST Professors Mohamed Eddaoudi and Omar Knio have received the Abdul Hameed Shoman Award for Arab Researchers. Eddaoudi was recognized for his work on metal-organic frameworks (MOFs) for clean energy and carbon capture, while Knio was honored for his contributions to mathematical modeling and simulation of thermo-fluid systems. The award, established in 1982, recognizes outstanding scientific output and aims to encourage a culture of scientific research in the Arab world. Why it matters: This recognition highlights the impactful research being conducted at KAUST and underscores the importance of Arab researchers' contributions to solving regional and global challenges.