KAUST, KACST, and RDI co-organized the Future of Semiconductors Forum 2023, held at KAUST on May 15-18, featuring 36 speakers from leading research institutes, universities, and companies. Nobel Prize Laureate Dr. Shuji Nakamura and Minister of Investment Eng. Kahlid Al Falih headlined the event, emphasizing the importance of semiconductors in various sectors, including AI and renewable energy. NEOM's Dr. Donal Bradley highlighted the need for energy-efficient semiconductor innovations to support NEOM's vision and reduce carbon footprint. Why it matters: The forum underscores Saudi Arabia's commitment to becoming a global leader in semiconductor technology, fostering local expertise and attracting international investment in this critical sector.
This paper describes the QCRI-Columbia-NYUAD group's Egyptian Arabic-to-English statistical machine translation system submitted to the NIST OpenMT'2015 competition. The system used tools like 3arrib and MADAMIRA for processing and standardizing informal dialectal Arabic. The system was trained using phrase-based SMT with features such as operation sequence model, class-based language model and neural network joint model. Why it matters: The work demonstrates advances in machine translation for dialectal Arabic, a challenging but important area for regional communication and NLP research.
KAUST hosted a Global IT Summit. The summit featured speakers like Khaled Biyari, group CEO at the Saudi Telecom Company. Interviews from the summit are available on KAUST's official YouTube channel. Why it matters: The summit likely served as a forum for discussing IT trends and developments relevant to Saudi Arabia's Vision 2030.
Song Chaoyang from the Southern University of Science and Technology (SUSTech) presented research on Vision-Based Tactile Sensing (VBTS) for robot learning, combining soft robotic design with learning algorithms to achieve state-of-the-art performance in tactile perception. Their VBTS solution demonstrates robustness up to 1 million test cycles and enables multi-modal outputs from a single, vision-based input, facilitating applications such as amphibious tactile grasping and industrial welding. The talk also highlighted the DeepClaw system for capturing human demonstration actions, aiming for a universal interaction interface. Why it matters: This research advances embodied intelligence by improving robot dexterity and adaptability through enhanced tactile sensing, which is crucial for complex manipulation tasks in various sectors such as manufacturing and healthcare within the region.
KAUST's Visualization Core Lab (KVL) has released inshimtu, a pseudo in situ visualization system for scientists working with large datasets and supercomputer simulations. Inshimtu simplifies the implementation of in situ visualization by using existing simulation output files without requiring changes to the simulation code. It helps scientists determine if implementing a full in situ visualization into their code is worthwhile. Why it matters: This open-source tool can improve the efficiency of supercomputing research in the region by allowing researchers to assess the value of in situ visualization before fully committing to it.
Patrick van der Smagt, Director of AI Research at Volkswagen Group, discussed the use of generative machine learning models for predicting and controlling complex stochastic systems in robotics. The talk highlighted examples in robotics and beyond and addressed the challenges of achieving quality and trust in AI systems. He also mentioned his involvement in a European industry initiative on trust in AI and his membership in the AI Council of the State of Bavaria. Why it matters: Understanding control in robotics, along with trust in AI, are key issues for further development of autonomous systems, especially in industrial applications within the GCC region.
KAUST researchers developed CovMT, a COVID-19 mutation tracking system for authorities and scientists to detect variants. CovMT tracks mutation fingerprints using daily data from the GISAID database of over 1.5 million viral genomes. The system identifies mutation hot spots, enabling public health authorities to stay ahead of new variants. Why it matters: This system provides a tool for rapid variant detection and informed public health decision-making in the region and globally.
Areej Aljarb is a Ph.D. student in material science and engineering at KAUST, researching 2D materials within the KAUST 2D Materials Research Lab under Professors Lain-Jong Li and Xixiang Zhang. Her research focuses on the controlled growth and fundamental phenomena of two-dimensional atomic layer thin materials, specifically controlling the orientation of 2D transition metal dichalcogenides (TMDs). Aljarb aims to achieve single-orientation epitaxial monolayer 2D TMDs to fully utilize the potential of these materials. Why it matters: This highlights KAUST's commitment to fostering local talent and contributing to advanced materials research with potential applications in various technology sectors.