A team led by the Technology Innovation Institute (TII) in Abu Dhabi has developed NATHR-G1, a ground penetrating radar for detecting landmines and unexploded ordnance. The project, involving researchers from Colombia, Germany, Sweden, and Switzerland, builds on earlier work using radar to detect buried objects. NATHR-G1 incorporates machine learning for advanced signal processing and object identification. Why it matters: This humanitarian application of AI and robotics based in the UAE could significantly reduce casualties from landmines and other explosive remnants of war.
MBZUAI held its inaugural Human-Computer Interaction (HCI) Symposium in Abu Dhabi, focusing on the human and societal impacts of AI. The event, led by Professor Elizabeth Churchill, featured workshops and keynotes from figures like Google's Matias Duarte. Participants collaborated to address critical design aspects of human-AI interaction and co-author a book. Why it matters: The symposium highlights the increasing importance of human-centered design in AI development, ensuring AI tools are useful, desirable, and beneficial for society in the GCC region and beyond.
Two mothers in the UAE have created an AI-powered teddy bear named "Emar" designed to help neurodivergent children communicate. Emar uses sensors and machine learning to analyze a child's emotional state through voice and touch. The AI then provides feedback and suggests coping mechanisms to both the child and their parents. Why it matters: This innovative application of AI offers a novel approach to supporting neurodivergent children and their families in the UAE.
The KAUST community held the opening night of its 2016 Enrichment in the Fall program. The event's theme was "Food for All." Photos from the event were taken by Meres Weche. Why it matters: This community event highlights KAUST's engagement with broader social themes, though the AI relevance is low.
This research introduces a novel method using the Lateral Accretive Hybrid Network (LEARNet) to capture and analyze micro-expressions for mental health applications. The method refines both broad and subtle facial cues to detect mental health conditions like anxiety or depression. The authors also propose a neural architecture search (NAS) strategy to design a compact CNN for micro-expression recognition, improving performance and resource use. Why it matters: By integrating micro-emotion recognition with mental health estimation, the approach enables more accurate and early detection of emotional and mental health issues, potentially leading to improved well-being.
Students from the KAUST School volunteered to assemble gift boxes for families in Thuwal as part of the "Sharing is Caring" campaign. The activity was organized to celebrate Eid. Why it matters: This highlights community engagement by a leading STEM university in Saudi Arabia.