The Saudi Space Agency (SSA) and KAUST held a workshop on September 19, 2023, to evaluate the Kingdom's space program and plan future initiatives. The SSA aims to propel Saudi Arabia's space program into the top 10 globally, focusing on six research areas. The partnership seeks to leverage KAUST's expertise to achieve Saudi Arabia's RDI vision in space exploration and set a roadmap to be available by January 2024. Why it matters: This collaboration signifies Saudi Arabia's commitment to advancing its space program and fostering local expertise in space-related research and development, aligning with the Kingdom's broader technology and innovation goals.
KAUST Ph.D. student Zhuo Qu and fellow students from the Statistics Program launched the first American Statistical Association (ASA) student chapter outside of the U.S. in October 2019. The chapter aims to encourage and provide opportunities for KAUST students interested in statistics to connect with statisticians worldwide. In 2020, the chapter plans to organize seminars and connect students interested in statistics and data mining. Why it matters: This initiative highlights KAUST's commitment to fostering a global network of statisticians and promoting data analysis skills among its students, enhancing its role as a hub for international collaboration in STEM fields.
KAUST alumnus Jagdish Chandra Vyas (Ph.D. '17) received a Student Presentation Award at the Seismological Society of America (SSA) Annual Meeting for his poster "Mach Wave Coherence in the Presence of Source and Medium Heterogeneity." Vyas's Ph.D. research at KAUST, under the direction of Professor Martin Mai, focused on analyzing the effects of rupture complexity and heterogeneities in Earth structure on near-source ground motions. He is currently a postdoctoral scholar at the University of Canterbury, New Zealand. Why it matters: This award recognizes the high-caliber research being conducted at KAUST and its impact on the field of seismology.
KAUST Ph.D. student Sabrina Vettori won the 2017 Student Paper Competition sponsored by the Section on Statistics and the Environment of the American Statistical Association. Her winning paper was titled "Bayesian clustering and dimension reduction in multivariate air pollution extremes", co-authored by Huser and Genton. The competition focused on environmental statistics, with winners presenting at the Joint Statistical Meetings. Why it matters: This award recognizes KAUST's contribution to environmental statistics and highlights the university's ability to attract and nurture talent in this critical area.
The Secure Systems Research Center (SSRC) has obtained membership in the seL4 Foundation. This membership allows SSRC to participate in and contribute to the open-source development of seL4, a formally verified microkernel OS. SSRC aims to research, contribute to, and advance next-generation high-end edge device environments using seL4's capabilities. Why it matters: This move enhances the UAE's capabilities in developing secure and resilient edge computing solutions, fostering innovation in critical sectors like secure communications and drone technology.
KAUST Assistant Professor Ying Sun won the 2017 Section on Statistics and the Environment Early Investigator Award. The award recognizes early-career researchers making significant contributions to environmental statistics. The award was given by the American Statistical Association. Why it matters: This highlights KAUST's strength in interdisciplinary research and its faculty's recognition on the international stage.
Hassan Sajjad from Dalhousie University presented research on exploring the latent space of AI models to assess their safety and trustworthiness. He discussed use cases where analyzing latent space helps understand the robustness-generalization tradeoff in adversarial training and evaluate language comprehension. Sajjad's work aims to build better AI models and increase trust in their capabilities by looking at model internals. Why it matters: Intrinsic evaluation of model internals will become important to improving AI safety and robustness.