A professor from EPFL (Lausanne) gave a talk at MBZUAI on computing in the post-Moore era, highlighting the slowing of Moore's Law due to physical limits in transistor miniaturization. He discussed research challenges and opportunities for future computing technologies. He presented examples of post-Moore technologies he helped develop in the datacenter space. Why it matters: As Moore's Law slows, research into alternative computing paradigms becomes critical for the continued advancement of AI and digital services in the UAE and globally.
DERC is partnering with EPFL in Switzerland on a four-year project using EMTR and ML to study electromagnetic disturbance localization in PCBs. Professor Farhad Rachidi (EPFL) and Dr. Nicolas Mora (DERC) will mentor a PhD student. The collaboration builds on prior relationships between DERC researchers and Prof. Rachidi's lab. Why it matters: The partnership strengthens DERC's methodological expertise and international recognition in electromagnetic studies, potentially leading to further collaborations.
TII Chief Researcher Mérouane Debbah and MBZUAI President Eric Xing visited École Polytechnique in France to discuss AI research and training. They reviewed AI projects and opportunities to increase the visibility of UAE-led research. The meeting aimed to strengthen collaboration between MBZUAI, TII, and École Polytechnique. Why it matters: Such partnerships can foster knowledge exchange and accelerate AI innovation in the UAE by leveraging international expertise.
KAUST researchers have integrated a hexagonal boron nitride sheet into CMOS microchips, creating a hybrid 2D-CMOS microchip. This integration leverages the electrical and thermal properties of 2D materials, resulting in circuits that are smaller, more energy-efficient, and have longer lifespans. The KAUST Imaging and Characterization Core Lab contributed to the observations in this study, which involved researchers from six countries. Why it matters: This achievement represents a significant advancement in microchip miniaturization and performance, potentially impacting various electronic applications.
Pascal Fua from EPFL presented an approach to implementing convolutional neural nets that output complex 3D surface meshes. The method overcomes limitations in converting implicit representations to explicit surface representations. Applications include single view reconstruction, physically-driven shape optimization, and bio-medical image segmentation. Why it matters: This research advances geometric deep learning by enabling end-to-end trainable models for 3D surface mesh generation, with potential impact on various applications in computer vision and biomedical imaging in the region.
A KAUST team led by Hossein Fariborzi won second place in the MEMS Design Contest for their "MEMS Resonator for Oscillator, Tunable Filter and Re-Programmable Logic Applications." The device is runtime-reprogrammable, allowing the function of each device in the circuit to be changed during operation. The KAUST team demonstrated that two MEMS resonators could replace over 20 transistors in applications like digital adders, reducing digital circuit complexity. Why it matters: This innovation could significantly reduce power consumption, chip area, and manufacturing costs in microprocessors, advancing the development of energy-efficient microcomputers in the region.
KAUST researchers found Y-series nonfullerene acceptors enhance the outdoor stability of organic solar cells, enabling energy-efficient windows. They also used satellite data to show managed vegetation can mitigate rising temperatures across Saudi Arabia's agricultural regions. Additionally, they developed DeepKriging, a deep neural network, to solve complex spatiotemporal datasets and tested it on air pollution. Why it matters: This research addresses critical challenges in renewable energy, climate change, and AI data privacy relevant to Saudi Arabia and the broader region.
KAUST and McLaren Racing have expanded their 5-year partnership to include collaborative research projects across McLaren's motorsport teams. The partnership will focus on simulation methodologies, optimized computing, and high-efficiency lubricants. KAUST students and researchers will work with McLaren at the McLaren Technology Centre to deliver joint projects. Why it matters: This collaboration provides KAUST students with real-world experience in an applied R&D environment, fostering innovation in areas like materials, lightweight structures, and circularity, with potential implications for the broader automotive and technology sectors in the region.