KAUST ·
KAUST researchers have developed an enhanced hot-electron nanoscopy technique. The new method improves the resolution and sensitivity of mapping materials at the nanoscale. Why it matters: This advancement can accelerate materials science research and development in areas relevant to the GCC, such as sustainable energy and advanced manufacturing.
KAUST ·
KAUST's Visual Computing Center (VCC) is researching computer vision, image processing, and machine learning, with applications in self-driving cars, surveillance, and security. Professor Bernard Ghanem is working on teaching machines to understand visual data semantically, similar to how humans perceive the world. Self-driving cars use visual sensors to interpret traffic signals and detect obstacles, while computer vision also assists governments and corporations with security applications like facial recognition and detecting unattended luggage. Why it matters: Advancements in computer vision at KAUST can contribute to innovations in autonomous vehicles and enhance security measures in the region.
KAUST ·
KAUST researchers are developing iSCAN, a rapid, field-deployable COVID-19 test using RT-LAMP coupled with CRISPR-Cas12. The iSCAN system is designed for rapid, specific detection of SARS-CoV-2 and can be deployed by untrained personnel. The researchers are benchmarking iSCAN against commercial kits and seeking emergency use authorization from the Saudi FDA. Why it matters: A rapid, accurate, and field-deployable COVID-19 test could significantly improve pandemic management and control in Saudi Arabia and beyond.
KAUST ·
Researchers at KAUST have developed a nanocomposite material that converts X-rays into light with nearly 100% efficiency. The material combines a metal-organic framework (MOF) containing zirconium with an organic TADF chromophore. This design achieves high resolution and sensitivity in X-ray imaging, potentially reducing medical imaging doses by a factor of 22. Why it matters: This innovation could lead to more efficient and safer medical imaging and security screening technologies in the region and beyond.
KAUST ·
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.
MBZUAI ·
MBZUAI researchers are introducing MedNNS, a system to be presented at MICCAI 2025, that recommends the best AI architecture and initialization for medical imaging tasks. MedNNS addresses the challenge of inefficient trial-and-error in building medical imaging AI by reframing model selection as a retrieval problem. The system employs a Once-For-All ResNet-like model and a learned meta-space of 720k model-dataset pairs, using dataset embeddings to predict optimal model performance. Why it matters: By automating model selection, MedNNS promises to significantly reduce the time and resources required to develop effective AI solutions for healthcare, particularly in medical imaging.
KAUST ·
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MBZUAI ·
MBZUAI researchers led by Dr. Mohammad Yaqub are developing AI algorithms for real-time medical diagnoses, including tools for multiple sclerosis and congenital heart disease. The team developed ScanNav, an AI fetal anomaly assessment system licensed by GE Healthcare for Voluson SWIFT ultrasound machines. ScanNav assists doctors during anomaly scans after 20 weeks of gestation to check for conditions like heart issues and spina bifida. Why it matters: This research has the potential to significantly improve the speed and accuracy of medical diagnoses in the UAE and beyond, addressing critical gaps in healthcare.