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.
MBZUAI ·
MBZUAI researchers created a new benchmark dataset called TextGames to evaluate the reasoning abilities of LLMs. The dataset uses simple, text-based games requiring skills like pattern recognition and logical thinking. LLMs struggled with the hardest questions, suggesting limitations in their reasoning capabilities despite advancements in language understanding. Why it matters: This research highlights the need for specialized reasoning models and benchmarks that go beyond memorization to truly test AI's problem-solving abilities.
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.
KAUST ·
KAUST researchers in the Sensors Lab are developing neuromorphic circuits for vision sensors, drawing inspiration from the human eye. They created flexible photoreceptors using hybrid perovskite materials, with capacitance tunable by light stimulation, mimicking the human retina. The team collaborates with experts in image characterization and brain pattern recognition to connect the 'eye' to the 'brain' for object identification. Why it matters: This biomimetic approach promises advancements in AI, machine learning, and smart city development within the region.
MBZUAI ·
Sir Michael Brady, professor at Oxford and MBZUAI, argues that AI in healthcare must move beyond pattern recognition to causal understanding. He states that clinicians require AI models to articulate their reasoning behind diagnoses and therapy recommendations, not just provide statistical scores. He believes AI's immediate impact will be in personalized medicine, tailoring treatments to the individual rather than relying on epidemiological averages. Why it matters: This perspective highlights the critical need for explainable AI in sensitive domains like healthcare, paving the way for more trustworthy and clinically relevant AI applications in the region.
arXiv ·
The Symposium on Data Mining and Applications (SDMA 2014) was organized by MEGDAM to foster collaboration among data mining and machine learning researchers in Saudi Arabia, GCC countries, and the Middle East. The symposium covered areas such as statistics, computational intelligence, pattern recognition, databases, Big Data Mining and visualization. Acceptance was based on originality, significance and quality of contribution.
MBZUAI ·
A public talk announcement features Professor Anil K. Jain from Michigan State University discussing biometric recognition. The talk will cover automated recognition of individuals based on biological and behavioral traits. It will also address challenges, research opportunities, and ongoing projects in Jain's lab related to biometrics. Why it matters: As biometric technologies become increasingly integrated into daily life across the Middle East, understanding their limitations and ethical implications is crucial for responsible development and deployment.