Skip to content
GCC AI Research

Search

Results for "Fahad Khan"

31 MBZUAI papers accepted at CVPR

MBZUAI ·

MBZUAI faculty and students presented 31 papers at the 2022 Conference on Computer Vision and Pattern Recognition (CVPR), including 6 oral presentations. Professors Fahad Khan and Shijian Lu had 9 and 8 papers accepted respectively. Researchers collaborated with 57 institutions across 16 countries. Why it matters: MBZUAI's strong showing at a top-tier CV conference demonstrates the rapid growth and international collaboration of AI research in the UAE.

Can artificial intelligence help cool our dangerously overheating cities?

MBZUAI ·

IBM and MBZUAI have partnered to create an AI Center of Excellence, with the goal of driving sustainability in the region. The center will use AI to monitor, model, and visualize climate change, providing decision-makers with data to address issues like the urban heat island effect. Dr. Fahad Khan, Dr. Salman Khan, and Dr. Levente Klein from MBZUAI are leading the research. Why it matters: This collaboration highlights the UAE's commitment to using AI to tackle critical climate challenges and supports the upcoming COP28 in Dubai.

34 MBZUAI papers accepted at CVPR

MBZUAI ·

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.

A unified theory of all things visual

MBZUAI ·

MBZUAI Professor Fahad Khan is working on a unified theory of machine visual intelligence. His goal is to enable AI systems to better understand and function in complex, chaotic visual environments. The aim is to improve real-world applications like smart cities, personalized healthcare, and autonomous vehicles. Why it matters: This research could significantly advance AI's ability to perceive and interact with the real world, especially in challenging environments common in the developing world.

27 papers accepted at NeurIPS

MBZUAI ·

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.

Using child’s play for machine learning

MBZUAI ·

MBZUAI Professor Salman Khan is researching continuous, lifelong learning systems for computer vision, aiming to mimic human learning processes like curiosity and discovery. His work focuses on learning from limited data and adversarial robustness of deep neural networks. Khan, along with MBZUAI professors Fahad Khan and Rao Anwer, and partners from other universities, presented research at CVPR 2022. Why it matters: This research has the potential to significantly improve the ability of AI systems to understand and adapt to the real world, enabling more intelligent autonomous systems.