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Researchers have developed a CNN-based deep learning model for predicting coastal flooding in cities under various sea-level rise scenarios. The model utilizes a vision-based, low-resource DL framework and is trained on datasets from Abu Dhabi and San Francisco. Results show a 20% reduction in mean absolute error compared to existing methods, demonstrating potential for scalable coastal flood management.
arXiv · · Research Traffic Management
The paper introduces a novel method for short-term, high-resolution traffic prediction, modeling it as a matrix completion problem solved via block-coordinate descent. An ensemble learning approach is used to capture periodic patterns and reduce training error. The method is validated using both simulated and real-world traffic data from Abu Dhabi, demonstrating superior performance compared to other algorithms.
MBZUAI · · Research Machine Learning
This talk discusses the asymptotic study of large asymmetric spiked tensor models. It explores connections between these models and equivalent random matrices constructed through contractions of the original tensor. Mohamed El Amine Seddik, currently a senior researcher at TII in Abu Dhabi, presented the work. Why it matters: The research provides theoretical foundations relevant to machine learning algorithms that leverage low-rank tensor structures, potentially impacting AI research and applications in the region.
MBZUAI welcomed its largest cohort of 209 graduate students for Fall 2024, selected from over 4800 applications. The new cohort includes the first students in computer science and robotics, representing 36 countries with 44 Emiratis. MBZUAI is also creating new departments dedicated to human-computer interaction, statistics and data science, and computational biology. Why it matters: This expansion strengthens Abu Dhabi's AI ecosystem and MBZUAI's position as a leading global AI institution, providing a diverse talent pool for the UAE's innovation goals.
Dr. Maxim Panov from TII Abu Dhabi will give a talk on uncertainty estimation in neural networks, covering model calibration, ensemble methods, and Bayesian approaches. The talk will focus on efficient single-network methods for quantifying prediction confidence, without requiring ensembles or major training changes. Panov's background includes experience at Skolkovo Institute of Science and Technology and DATADVANCE Company. Why it matters: Improving uncertainty estimation is crucial for deploying reliable AI systems in critical applications across the GCC region.
MBZUAI · · Policy Government
The Director-General of the Abu Dhabi Digital Authority, Mohamed Abdelhameed Al Askar, will give a talk on AI adoption in government. The talk will cover key points related to AI utilization within government organizations. Al Askar has experience managing digital initiatives such as the Abu Dhabi Government Services Program (TAMM). Why it matters: This signals the increasing importance of AI in public sector modernization efforts in the UAE and the broader region.