KAUST doctoral student Jose Filho won the 2022 InnovateFPGA Design Contest for his "Customized Medicine for Corals" project. The project uses an automatic feeder technology to deliver coral probiotics and monitor their efficacy via cloud connectivity, computer vision, and an FPGA. The system gathers data from cameras, temperature sensors, and luminosity sensors, using AI to determine the coral's bleaching stage and deploy beneficial microorganisms. Why it matters: This win highlights KAUST's innovative research in applying AI and cloud technology to address critical environmental challenges like coral bleaching, demonstrating the potential for technology to aid marine conservation efforts.
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.
This article discusses the application of AI in semiconductor chip design and manufacturing, with a focus on examples such as IR-drop estimation and lithography processes. It mentions Youngsoo Shin, a KAIST professor and founder of Baum, who is an expert in this area. The article also briefly mentions panel discussion hosted by MBZUAI. Why it matters: AI-driven chip design and manufacturing could accelerate semiconductor innovation in the GCC region and beyond.
Researchers at National Taiwan University are developing low-complexity neural network technologies using quantization to reduce model size while maintaining accuracy. Their work includes binary-weighted CNNs and transformers, along with a neural architecture search scheme (TPC-NAS) applied to image recognition, object detection, and NLP tasks. They have also built a PE-based CNN/transformer hardware accelerator in Xilinx FPGA SoC with a PyTorch-based software framework. Why it matters: This research provides practical methods for deploying efficient deep learning models on resource-constrained hardware, potentially enabling broader adoption of AI in embedded systems and edge devices.
KAUST researchers published a paper in Nature Electronics outlining communications infrastructure enhancements for 6G to provide global internet access and bridge the digital divide. They propose innovations like aerial access networks, intelligent spectrum management, and energy efficiency improvements. In a separate IEEE paper, KAUST and Missouri S&T researchers demonstrate approaches for improving network throughput using UAVs and balloons in areas lacking terrestrial infrastructure. Why it matters: The research addresses the UN's Sustainable Development Goal of universal internet access and aims to bring connectivity to underserved populations, enabling access to essential services and opportunities.
Technology Innovation Institute's (TII) Directed Energy Research Center (DERC) is integrating machine learning (ML) techniques into signal processing to accelerate research. One project used convolutional neural networks to predict COVID-19 pneumonia from chest x-rays with 97.5% accuracy. DERC researchers also demonstrated that ML-based signal and image processing can retrieve up to 68% of text information from electromagnetic emanations. Why it matters: This adoption of ML for signal processing at TII highlights the potential for advanced AI techniques to enhance research and security applications in the UAE.
KAUST researchers demonstrated a new flash memory device design using gallium oxide, which can withstand harsh environments. In collaboration with the University of Michigan, KAUST researchers explained a key molecular event for the activation of an enzyme associated with cancer. The Summer 2023 issue of KAUST Discovery is now available. Why it matters: These research achievements highlight KAUST's contributions to advanced materials science and biomedical research, with potential applications in space technology and cancer treatment.
Communications Physics journal has a focus collection on space quantum communications. The collection covers supporting technologies, new quantum protocols, inter-satellite QKD, constellations of satellites, and quantum inspired technologies and protocols for space based communication. Contributions are welcome from October 20, 2020 to April 30, 2021, and accepted papers are published on a rolling basis. Why it matters: Space-based quantum communication is a critical area for developing secure, global quantum networks, and this collection could highlight relevant research for the GCC region as it invests in advanced technologies.