Professor Le Song has joined MBZUAI as Deputy Department Chair of the Machine Learning Department. He brings decades of experience from institutions like Georgia Tech, Google Research, and Carnegie Mellon University. Le Song's research focuses on machine learning methods and algorithms for complex and dynamic data, with over 160 papers published in top ML conferences. Why it matters: This appointment bolsters MBZUAI's machine learning department and signals the university's commitment to attracting world-class AI talent to the UAE.
MBZUAI Department Chair Le Song served as a program co-chair at the 39th International Conference on Machine Learning (ICML). MBZUAI faculty, researchers, and students had 7 papers accepted at ICML 2022. Song noted the increasing focus on biomedicine and other science areas within the AI research community. Why it matters: Song's leadership role at ICML and MBZUAI's strong presence highlights the university's growing influence in the global machine learning landscape.
MBZUAI's Professor Le Song is developing an AI-driven simulation to model the human body at societal, organ, tissue, cellular, and molecular levels. The goal is to reduce the time and cost associated with bringing new medicines to market by removing the need for wet lab biological research. Song aims to create a comprehensive model using machine learning. Why it matters: This research could revolutionize drug discovery in the region by accelerating the development process and reducing reliance on traditional research methods.
KAUST Discovery highlighted Prof. Karl Leo's insights on translating science into business from an Entrepreneurship Center speaker series. Prof. Leo, with 440 publications and 8 co-founded companies, emphasized the importance of curiosity-driven basic research. He envisions organic semiconductors dominating electronics in 20-30 years, noting the success of Novaled, his OLED company in Dresden. Why it matters: This underscores KAUST's focus on fostering entrepreneurship and translating research into practical applications within the Kingdom.
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.
Dr. Hao Dong from Peking University presented research on addressing the challenge of limited large-scale training data in embodied AI, particularly for manipulation, task planning, and navigation. The presentation covered simulation learning and large models. Dr. Dong is a chief scientist of China's National Key Research and Development Program and an area chair/associate editor for NeurIPS, CVPR, AAAI, and ICRA. Why it matters: Overcoming data scarcity is crucial for advancing embodied AI research and enabling more sophisticated robotic applications in the region.
Dr. Zeke Xie from HKUST(GZ) presented research on noise initialization and sampling strategies for diffusion models. The talk covered golden noise for text-to-image models, zigzag diffusion sampling, smooth initializations for video diffusion, and leveraging image diffusion for video synthesis. Xie leads the xLeaF Lab, focusing on optimization, inference, and generative AI, with previous experience at Baidu Research. Why it matters: The work addresses core challenges in improving the quality and diversity of generated content from diffusion models, a key area of advancement for AI applications in the region.
This article summarizes a talk by Erci Xu on doing computer systems research, focusing on idea generation and paper writing. Xu shares experiences on developing research ideas and provides a tutorial on academic writing principles. He has published 20 papers in venues like OSDI, FAST, ATC, and Eurosys and received awards including two FAST Best Paper Awards. Why it matters: The talk and summary offer valuable guidance for researchers in the Middle East, particularly those at institutions like MBZUAI, on how to conduct impactful computer systems research and effectively communicate their findings in top-tier academic publications.