KAUST, in collaboration with the Communications, Space and Technology Commission (CST) and Meta, has launched a Terragraph Wi-Fi project to bring high-speed internet to the Modern Architectural Contracting Company (MACC) camp near KAUST. The project utilizes Meta's Terragraph technology, a gigabit wireless system operating in the 57-71GHz band, to provide a low-cost, high-speed alternative to fiber. Weather stations will monitor climate variables affecting the hybrid RF/FSO links, validating KAUST's research in extreme bandwidth communication. Why it matters: This deployment demonstrates a practical solution for delivering affordable, high-speed internet access to underserved communities in the region, leveraging advanced wireless technologies and KAUST's research capabilities.
KAUST Ph.D. student Valerio Mazzone won the best paper award at the 9th International Conference on Metamaterials, Photonic Crystals and Plasmonics (META). Mazzone's paper demonstrated the design of a new type of fully optical neural network using dielectric nano-lasers with invisible emission. The research showed the system can produce ultrafast optical pulses with controllable period and time duration in an optical chip. Why it matters: This award recognizes KAUST's contribution to innovative research in nanophotonics and optical computing, potentially leading to more efficient and compact laser technology.
KAUST hosted the KAUST Research Conference: Advances in Well Construction with Focus on Near-Wellbore Physics and Chemistry from November 7 to 9. The conference was co-chaired by Eric van Oort, a professor at UT Austin, and Tadeusz Patzek, director of the University’s Upstream Petroleum Engineering Research Center. Attendees included professors from the University of Queensland and UT Austin, and directors from GenesisRTS and Labyrinth Consulting Services, Inc. Why it matters: The conference facilitates international collaboration on advancements in petroleum engineering and well construction technologies, which are strategically important for Saudi Arabia.
This is an advertisement for KAUST Discovery Associate Professor of Computer Science Ivan Viola. The ad promotes KAUST as a university. Why it matters: This reflects KAUST's ongoing efforts to attract international faculty and promote its research programs.
KAUST highlights postdoctoral fellows Yi Jin Liew, Isabelle Schulz, Maren Ziegler and Neus Garcias Bonet outside the University Library. The article mentions King Abdullah bin Abdulaziz Al Saud (1924 – 2015). It encourages applications to KAUST's Discovery Postdoctoral program. Why it matters: This brief announcement signals KAUST's ongoing investment in attracting international research talent to Saudi Arabia.
A KAUST student blog post discusses optical wireless communications (OWC) as a solution to radio frequency exhaustion. OWC uses optical frequencies to carry electrical signals, offering advantages like high data rates and immunity to electromagnetic interference. Free-space optical (FSO) communication, a type of OWC, is applicable for inter-building connections and has seen use cases such as broadcasting during the 2010 FIFA World Cup. Why it matters: OWC research and deployment in the region can support high-bandwidth applications and provide cost-effective connectivity solutions, especially in challenging environments or disaster scenarios.
MBZUAI President Eric Xing delivered a talk at Carnegie Mellon University on May 13, 2022, titled “From Learning, to Meta-Learning, to Lego-Learning — theory, systems, and engineering.” Xing discussed the development of a standard model for learning, inspired by the standard model in physics, which aims to unify various machine learning paradigms. Before joining MBZUAI, Xing was a professor at CMU and founder of Petuum Inc., an AI development platform company. Why it matters: This talk highlights MBZUAI's leadership in advancing theoretical frameworks for machine learning and its commitment to unifying different AI approaches.
A new mini-batch strategy using aggregated relational data is proposed to fit the mixed membership stochastic blockmodel (MMSB) to large networks. The method uses nodal information and stochastic gradients of bipartite graphs for scalable inference. The approach was applied to a citation network with over two million nodes and 25 million edges, capturing explainable structure. Why it matters: This research enables more efficient community detection in massive networks, which is crucial for analyzing complex relationships in various domains, but this article has no clear connection to the Middle East.