The Technology Innovation Institute (TII) in Abu Dhabi has entered a research agreement with Amazon Web Services (AWS) to explore quantum computing applications using Amazon Braket. TII researchers will leverage AWS's quantum and high-performance computing resources for research in machine learning, computational chemistry, and optimization. AWS will provide support, workshops, and facilitate connections between TII and regional enterprise customers to build R&D partnerships. Why it matters: This collaboration advances TII's mission to develop quantum computing capabilities in the UAE and fosters innovation in AI, drug discovery, finance, and other sectors.
MBZUAI researchers have developed MorphDiff, a diffusion model that predicts cell morphology from gene expression data. MorphDiff uses the transcriptome to generate realistic post-perturbation images, either from scratch or by transforming a control image. The model combines a Morphology Variational Autoencoder (MVAE) with a Latent Diffusion Model, enabling both gene-to-image generation and image-to-image transformation. Why it matters: This could significantly accelerate drug discovery and biological research by allowing scientists to preview cellular changes before conducting experiments.
MBZUAI and GenBio AI have won the UAE AI Award 2025 in the AI Scientific Research category for their "Unified Protein Language Modeling Framework". The winning project enables AI to learn protein function, generate sequences, and predict 3D structures. The AI-driven simulation approach aims to accelerate drug development, reduce costs, and improve success rates. Why it matters: This award highlights the UAE's commitment to fostering AI innovation in biomedicine and drug discovery, positioning the region as a leader in AI-driven healthcare advancements.
MBZUAI researchers developed FetalCLIP, an AI model trained on 210,000 ultrasound images for fast and reliable interpretation of fetal scans. MBZUAI's President Eric Xing contributed to the General Expression Transformer (GET), an AI foundation model acting as a biological simulator to predict gene behavior. MBZUAI and Carleton University created MedPromptX for quicker disease diagnosis and treatment plans using multimodal AI. Why it matters: These AI advancements from MBZUAI have the potential to revolutionize healthcare in the region and globally, from prenatal care to drug discovery and personalized medicine.
MBZUAI and BioMap have signed an MoU to establish the first biocomputing innovation research lab in the Middle East, located on MBZUAI's campus. The collaboration will focus on applying AI protein generation to life science models, addressing needs in drug design, energy, and environmental protection. The lab will research de novo design of oil degradation enzymes and identify drug targets for aging-associated and rare diseases. Why it matters: This partnership signals a growing focus on applying AI to critical life science challenges in the region, potentially leading to breakthroughs in drug discovery and sustainable energy solutions.
KAUST alumnus Yu Li was named in Forbes' 30 Under 30 Asia List for his work developing algorithms to solve problems in biology and healthcare. Li, now an assistant professor at CUHK, was recognized for his computational tools to identify antibiotic-resistant genes. His research focuses on computational biology, human health, biomolecular structure prediction, and AI-driven drug discovery. Why it matters: This recognition highlights the impact of KAUST's programs in fostering AI talent in the region, particularly in the growing field of bioinformatics and healthcare.
Dr. Farida Al Hosani, a UAE public health leader and MBZUAI Executive Program graduate, has been at the forefront of the nation’s public health strategy, specializing in infectious diseases. She emphasizes the growing importance of AI in healthcare, particularly in areas like early detection, drug discovery, and public health strategies. Al Hosani has worked on several AI initiatives, including building algorithms and predictive modeling systems to bridge gaps in human health, especially in prevention. Why it matters: This highlights the increasing role of AI in transforming healthcare in the UAE, with public health leaders leveraging AI tools to improve disease prevention and treatment.
Xiao Wang from Purdue University presented research on Adversarial Contrastive Learning (AdCo) and Cooperative-adversarial Contrastive Learning (CaCo) for improved self-supervised learning. He also discussed CryoREAD, a framework for building DNA/RNA structures from cryo-EM maps, and future work in deep learning for drug discovery. Wang's algorithms have impacted molecular biology, leading to new structure discoveries published in journals like Cell and Nature Microbiology. Why it matters: The research advances AI techniques for crucial tasks in molecular biology and drug discovery, with potential applications for institutions in the GCC region focused on healthcare and biotechnology.