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.
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 faculty members led or co-led several top global AI conferences in 2022, including ACL, ICML, CLeaR, and UAI. Faculty members Timothy Baldwin, Le Song, Kun Zhang, and Preslav Nakov held leadership positions at these conferences. According to CSRankings, MBZUAI ranks in the top 30 globally in AI, computer vision, machine learning, and NLP. Why it matters: This highlights MBZUAI's growing influence and reputation in the global AI research community, solidifying its position as a leading institution in the field.
MBZUAI faculty and researchers had 27 papers accepted at the 2022 NeurIPS conference. 12 MBZUAI faculty members have at least one paper accepted, with Professor Kun Zhang leading with 10 papers. Other faculty with accepted publications include Eric Xing, Le Song, and Fahad Khan. Why it matters: This achievement highlights MBZUAI's growing prominence in the global machine learning research community.
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.