Michael Holland from NYU's Center for Urban Science & Progress (CUSP) presented a keynote lecture at KAUST's Winter Enrichment Program (WEP) 2015 on the importance of urban science. CUSP, launched in 2012, aims to make New York City a world capital of science and technology through multi-sector research and education. Holland emphasized how analyzing urban data can improve city government, planning, policy, and citizen engagement. Why it matters: As urbanization increases, the development of urban science and the effective use of urban data become crucial for sustainable and efficient city management in the GCC region and globally.
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KAUST held a KAUST-U.S. National Science Foundation (NSF) Conference on Environmental Monitoring from November 6 to 8, 2017. The conference focused on sustainability with an emphasis on environmental monitoring and sensing, including data collection, signal processing, and real-time decision-making. Keynote speakers included Ali Sayed (EPFL), Allen Tannenbaum (SUNY Stony Brook), and Dinesh Manocha. Why it matters: Such conferences foster international collaboration and knowledge exchange in applying AI and related technologies to pressing environmental challenges in Saudi Arabia and globally.
The article mentions several KAUST faculty and staff, including Matteo Parsani (Assistant Professor of Applied Mathematics), Teofilo Abrajano (Director of Sponsored Research), and David Keyes (Director of the Extreme Computing Research Center). It also references a talk by NASA Senior Scientist Mark Carpenter at the SIAM CSE 2017 conference. The article includes a photograph of King Abdullah bin Abdulaziz Al Saud. Why it matters: This appears to be general information about KAUST faculty and activities, but lacks specific details on research or AI developments.
Giuseppe Loianno from NYU presented research on creating "Super Autonomous" robots (USARC) that are Unmanned, Small, Agile, Resilient, and Collaborative. The research focuses on learning models, control, and navigation policies for single and collaborative robots operating in challenging environments. The talk highlighted the potential of these robots in logistics, reconnaissance, and other time-sensitive tasks. Why it matters: This points to growing research interest in advanced robotics in the region, especially given the focus on smart cities and automation.
A new framework for constructing confidence sets for causal orderings within structural equation models (SEMs) is presented. It leverages a residual bootstrap procedure to test the goodness-of-fit of causal orderings, quantifying uncertainty in causal discovery. The method is computationally efficient and suitable for medium-sized problems while maintaining theoretical guarantees as the number of variables increases. Why it matters: This offers a new dimension of uncertainty quantification that enhances the robustness and reliability of causal inference in complex systems, but there is no indication of connection to the Middle East.