KAUST ·
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.
KAUST · Matteo Parsani · Teofilo Abrajano · David Keyes · Mark Carpenter
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KAUST ·
Entrepreneur Alexandru Ionut Budisteanu spoke at KAUST's 2018 Winter Enrichment Program (WEP) about pursuing one's passion to achieve their dreams. Budisteanu shared his journey of creating video games and building an autonomous self-driving car prototype. He emphasized the importance of finding a job or activity that one loves and working with passion. Why it matters: Showcases KAUST's efforts to host inspiring speakers and promote entrepreneurship among students.
KAUST ·
KAUST researchers developed a machine learning algorithm to control a deformable mirror within the Subaru Telescope's exoplanet imaging camera, compensating for atmospheric turbulence. The algorithm, which computes a partial singular value decomposition (SVD), outperforms a standard SVD by a factor of four. The KAUST team received a best paper award at the PASC Conference for this work, which has already been deployed at the Subaru Telescope. Why it matters: This advancement enables sharper images of exoplanets, facilitating their identification and study, and showcases the impact of optimizing core linear algebra algorithms.
KAUST ·
KAUST's Discovery program supports entrepreneurship. The program appears to have existed since at least 2014, with collaborations including UC Berkeley. Why it matters: Such programs foster innovation and align with Saudi Arabia's Vision 2030 goals for economic diversification.
MBZUAI ·
MBZUAI PhD graduate William de Vazelhes is researching hard-thresholding algorithms to enable AI to work from smaller datasets. His work focuses on optimization algorithms that simplify data, making it easier to analyze and work with, useful for energy-saving and deploying AI models on low-memory devices. He demonstrated that his approach can obtain results similar to those of convex algorithms in many usual settings. Why it matters: This research could broaden AI accessibility by reducing computational costs, and has potential applications in sectors like finance, particularly for portfolio management under budgetary constraints.