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.
MBZUAI faculty and students will present 53 papers at NeurIPS 2023. Key faculty include Eric Xing, Kun Zhang, and Tongliang Liu, each contributing to nine papers. One paper was selected for oral presentation and two for spotlight presentations. Why it matters: MBZUAI's strong presence at NeurIPS highlights its growing influence in the global AI research community and its focus on high-impact AI research.
MBZUAI had 22 papers accepted at ICLR 2023, with faculty Kun Zhang co-authoring seven of them. Yuanzhi Li, an affiliated assistant professor at MBZUAI, received an honorable mention for his paper on knowledge distillation. Additionally, a paper co-authored by MBZUAI President Eric Xing was recognized as a top 5% paper at the conference. Why it matters: MBZUAI's strong presence at a top-tier machine learning conference like ICLR demonstrates the university's growing influence and research capabilities in the global AI landscape.
MBZUAI researchers will present 20 papers at the 40th International Conference on Machine Learning (ICML) in Honolulu. Visiting Associate Professor Tongliang Liu leads with seven publications, followed by Kun Zhang with six. One paper investigates semi-supervised learning vs. model-based methods for noisy data annotation in deep neural networks. Why it matters: The research addresses the critical issue of data quality and accessibility in machine learning, particularly for organizations with limited resources for data annotation.
MBZUAI faculty, researchers, and students will present 34 papers at the 35th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023). Fahad Khan is a co-author on 11 accepted papers, while Salman Khan and Shijian Lu have 10 and 9 papers, respectively. One paper focuses on person image synthesis via a denoising diffusion model, and another introduces PromptCAL for generalized novel category discovery. Why it matters: This large volume of acceptances at a top-tier conference highlights MBZUAI's growing prominence and research contributions in computer vision, with potential impact across various industries from online retail to autonomous driving.