KAUST and NEOM have signed an agreement to establish the KAUST-NEOM Center of Excellence for NEOM Research at KAUST. The center will focus on solutions for challenges in sustainable energy, urban planning, agriculture, seismology, water desalination, AI, big data, and sensors. NEOM will be backed by over $500 billion in funding. Why it matters: The partnership signifies a major investment in R&D and technological innovation within Saudi Arabia, aligning with the Kingdom's vision for economic diversification and development of cutting-edge technologies.
MBZUAI researchers are refining AI techniques to improve cancer diagnosis for colorectal and breast cancer, both common in the Middle East. They are using "few-shot tissue image generation," in which AI generates data for training AI models to recognize lesions, addressing the challenge of limited training data. The developed framework improves the efficiency of radiologists in breast cancer diagnosis, leading to better detection of breast lesions and timely treatment interventions. Why it matters: These advancements in AI-aided diagnostics can lead to earlier and more accurate cancer detection, ultimately improving patient outcomes in the region and beyond.
MBZUAI and Minerva Humanoids have launched a two-year research partnership to develop humanoid robotics for safety-critical industrial operations, initially focusing on the energy sector. The collaboration aims to create versatile, reasoning-based systems capable of operating with varying degrees of autonomy. MBZUAI students will be integrated into project teams to develop AI models and robotics systems. Why it matters: The partnership advances AI-driven robotics in safety-critical domains, supports the UAE's ambition to become a global hub, and develops local talent.
MBZUAI has partnered with the World Economic Forum to launch a Centre for the Fourth Industrial Revolution (C4IR) in the UAE. This center will focus on AI, energy transition, and cyber resilience, aiming to advance AI excellence and competitiveness in the region. It will convene leaders across sectors to co-design and pilot initiatives supporting AI research, governance, adoption, and innovation. Why it matters: This partnership positions the UAE and MBZUAI as key players in shaping the global AI landscape and addressing pressing economic, social, and human challenges through AI.
MBZUAI researchers co-led a study published in Nature demonstrating that GluFormer, an AI foundation model trained on continuous glucose monitoring (CGM) data, more accurately predicts long-term diabetes and cardiovascular risk than current clinical standards. GluFormer, built on a transformer architecture and trained using NVIDIA AI infrastructure on over 10 million CGM measurements, forecasts individual health risks using short-term glucose dynamics. In a 12-year follow-up, the model captured 66% of new-onset diabetes cases and 69% of cardiovascular-death events in its highest-risk group, outperforming established CGM-derived metrics across 19 external cohorts. Why it matters: The development of GluFormer represents a significant advancement in personalized healthcare, enabling proactive and individualized health strategies through the analysis of dynamic glucose data.
MBZUAI has launched the Institute for Agriculture and Artificial Intelligence (IAAI) in collaboration with the UAE Presidential Court and the Gates Foundation. The IAAI will focus on strengthening global food security by providing digital advisory tools to over 43 million smallholder farmers. The institute will develop a new data corpus for agriculture to train AI models and offer localized insights on crops, pests, soils, weather, and markets. Why it matters: This initiative highlights the UAE's commitment to using AI for global good, specifically addressing food security challenges and empowering small-scale farmers through advanced technologies.
The Tahnoon bin Zayed Scholarship in AI Excellence has been established to support undergraduate students at MBZUAI, starting in the 2025-2026 academic year. The merit-based scholarship aims to support approximately 350 students over six years, focusing on mathematical fluency, leadership, and entrepreneurial attitude. Scholarship recipients will have opportunities to represent the UAE at youth events and pursue entrepreneurial ventures. Why it matters: This scholarship program is a significant investment in developing local AI talent and positioning the UAE as a leader in global AI innovation.
MBZUAI has launched master’s and Ph.D. programs in computational biology, expanding its research into life sciences. This includes projects like AIDO (AI-Driven Digital Organism) and analysis of the Emirati Genome Program. The programs are part of MBZUAI’s School of Digital Public Health and aim to integrate computational biology with precision medicine. Why it matters: This initiative supports the UAE's vision for a knowledge-based economy and its ambition to become a global center for scientific and technological progress in biotechnology and healthcare.
MBZUAI Adjunct Professor Iryna Gurevych has won the 2025 Royal Society Milner Award for her contributions to NLP and AI. The Milner Award recognizes outstanding European computer scientists and includes a bronze medal and a £5,000 honorarium. Gurevych's work focuses on processing big data with NLP tools, argument mining, and detecting misleading content. Why it matters: The award highlights MBZUAI's growing prominence in the international AI research landscape and Gurevych's work in making language models safer.
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 researchers are developing LAIKA, an autonomous quadruped robot for hazardous industrial environments, integrating vision-language AI models with 360-degree imaging. LAIKA can operate in operator-assist mode via natural language or autonomously to inspect, detect anomalies like leaks, and generate structured reports. The robot is designed for versatile tasks in industrial inspection, emergency response, and facility monitoring, with future versions integrating multi-robot collaboration. Why it matters: This technology demonstrates AI's potential to enhance industrial safety, reduce risks to human workers, and improve response times in critical situations within the region's vital energy and manufacturing sectors.
MBZUAI researchers are developing an AI-driven energy management system that optimizes ice battery technology for cooling in hot climates. The system stores energy as frozen water during times of energy surplus and uses it to cool buildings when demand peaks. The AI model integrates multimodal data from weather forecasts, environmental sensors, and power grid signals to determine when to store or release thermal energy. Why it matters: This approach promises to reduce fossil fuel dependence and lower energy costs while improving cooling performance in regions like the UAE.
MBZUAI researchers presented DEFUSE-MS at MICCAI 2025, a novel AI system for analyzing changes in MRI scans of multiple sclerosis (MS) patients. DEFUSE-MS uses a deformation field-guided spatiotemporal graph-based framework to identify new lesions by reasoning about how the brain has changed. The model constructs graphs of small regions within baseline and follow-up MRIs, linking them across time with edges enriched with learned embeddings of the deformation field. Why it matters: DEFUSE-MS reframes the task from simple "spot the difference" to understanding structural changes, potentially improving the speed and accuracy of MS diagnosis and treatment monitoring.
MBZUAI and the Department of Health – Abu Dhabi (DoH) have signed an agreement to collaborate on AI research across genomics, precision medicine, robotics, and AI-powered diagnostics. Signed on October 13, 2025, the MoU aims to drive breakthroughs in disease prevention, early detection, and therapeutics. The partnership seeks to translate AI research into tangible improvements in patient care within Abu Dhabi and beyond. Why it matters: This partnership signifies a major push to establish Abu Dhabi as a leader in biomedical research and AI-driven healthcare innovation.
The Abu Dhabi Department of Energy (DoE) and Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) have signed an MoU to collaborate on AI and ML applications in the energy sector. The partnership aims to drive innovation, efficiency, and sustainability in Abu Dhabi's energy landscape. MBZUAI will combine its research expertise with DoE's regulatory leadership to develop smart energy solutions. Why it matters: This partnership signifies a major step towards integrating AI into the UAE's energy sector, supporting the nation's Net Zero 2050 target and fostering AI-driven sustainability.
MBZUAI and MIT Schwarzman College of Computing have launched a collaborative research program to advance AI across scientific discovery, human thriving, and planetary health. The program will involve faculty, students, and research staff from both institutions, with projects jointly led by principal investigators from each. The collaboration aims to strengthen AI foundations and accelerate its application to pressing societal challenges, aligning with both MIT's goals and the UAE's mission to become a global AI innovation hub. Why it matters: This partnership between a leading UAE AI university and a top US institution will foster impactful AI research and development, contributing to both regional and global advancements in the field.
MBZUAI researchers developed Data Wise, an AI platform that provides instant data analytics for businesses. The platform uses AI agents and LLMs to analyze raw customer data and generate actionable recommendations. Data Wise aims to address the shortage of data scientists, particularly in the UAE and GCC. Why it matters: This platform democratizes access to advanced analytics, empowering businesses in the region to make data-driven decisions without relying on scarce technical expertise.
MBZUAI and Quris-AI have partnered to launch a Bio-AI center in Abu Dhabi during Abu Dhabi Sustainability Week. The center will focus on developing personalized medications tailored to the MENA region's diverse populations, leveraging Quris-AI's 'patient-on-a-chip' technology and MBZUAI's AI expertise. Quris-AI is establishing a UAE subsidiary, Quris-UAE, in Abu Dhabi as part of this collaboration. Why it matters: This initiative positions Abu Dhabi as a hub for Bio-AI research and personalized medicine, potentially accelerating drug development and reducing clinical trial failures in the region.
MBZUAI awarded OpenAI CEO Sam Altman an honorary doctorate in recognition of his leadership in AI. The ceremony was attended by UAE dignitaries and university leadership, who emphasized Altman's impact on making AI accessible globally. Altman expressed his honor and commended MBZUAI's commitment to AI research and education. Why it matters: This award recognizes the growing importance of AI and the UAE's ambition to be a leader in the field, highlighting the alignment between global AI innovators and the nation's vision.
A Science Robotics article co-authored by MBZUAI explores the use of AI and robotics to accelerate scientific discovery in chemistry, biology, and materials science. The paper envisions closed-loop labs with AI-designed experiments, robotic execution, and machine learning analysis, potentially cutting discovery timelines. It proposes a framework emphasizing human-machine partnership, modular systems, and AI-driven planning while addressing challenges like data standardization. Why it matters: This research highlights the potential of AI and robotics to transform scientific research in the GCC region and beyond, enabling faster discoveries and democratizing access to advanced lab capabilities.
MBZUAI and the University of Chicago are collaborating on a program to train governments in low- and middle-income countries (LMICs) to use AI weather forecasting models. Funded by a grant from the UAE Presidential Court, the program's first cohort includes staff from Bangladesh, Chile, Ethiopia, Kenya, and Nigeria, receiving training in the UAE at MBZUAI and NCM. The program aims to expand to 30 countries, potentially benefiting millions of farmers by improving yields and livelihoods. Why it matters: This initiative democratizes access to advanced weather forecasting, enabling LMICs to leverage AI for climate resilience and agricultural productivity.
Researchers from Carnegie Mellon University and MBZUAI have developed a new method called ConceptAligner for precise image editing using AI. The system decomposes text embeddings into independent building blocks called atomic concepts, allowing users to make targeted tweaks without generating entirely new images. Their approach ensures that each latent factor maps to a specific user-controllable dial, enabling accurate concept-level modifications. Why it matters: This research addresses a major limitation in AI image generation, enhancing its usefulness in industries where precise control is crucial, such as advertising and medicine, and improving the reliability of AI-driven creative tools.
The Human Phenotype Project (HPP), led by researchers from Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), published findings in Nature Medicine detailing an understanding of the health-disease continuum. The HPP involves deep and longitudinal profiling of approximately 28,000 participants, collecting diverse data including medical history, lifestyle, blood tests, and molecular profiling. The project aims to create AI-based predictive models for disease onset and progression, and digital twins to simulate interventions. Why it matters: This research can transform precision medicine and preventative care in the UAE by creating personalized digital twins that can simulate interventions and predict health trajectories.
MBZUAI graduates Abdulla and Abdulrahman Almarzooqi are developing AI systems to improve UAE road safety. Abdulla's research focuses on external highway monitoring using MLLMs to analyze driving scenes and generate accident reports, while Abdulrahman's work uses in-cabin sensors to detect driver fatigue and distractions. Together, their systems aim to create a comprehensive view of factors influencing traffic accidents, with potential applications in ADAS and automated accident reporting. Why it matters: This research showcases the potential of AI agents and multimodal LLMs to proactively enhance road safety in the UAE and reduce traffic-related incidents.
MBZUAI researchers have developed "Tactile Skills," a new embodied AI framework enabling robots to rapidly learn complex tactile tasks. The framework combines expert process knowledge with reusable tactile control and adaptation components, reducing reliance on extensive datasets. Tested on 28 industrial tasks, the robots achieved nearly 100% success, demonstrating adaptability to changing conditions. Why it matters: This breakthrough offers a practical and scalable approach to robotic automation, potentially transforming robots into adaptable assistants across diverse industries in the GCC.
MBZUAI and Corniche Hospital researchers have developed FetalCLIP, a foundation model for analyzing fetal ultrasound images to detect congenital conditions. FetalCLIP outperformed other foundation models on ultrasound analysis tasks. The AI model aims to improve the early diagnosis of ailments like congenital heart defects. Why it matters: This innovation has the potential to dramatically improve health outcomes for millions of children annually by providing physicians with better insights into fetal health.
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's VP of Research, Professor Sami Haddadin, and his team at TUM have developed the 'Tree of Robots,' a new framework for categorizing robots based on capabilities and morphology rather than appearance or purpose. This framework uses a Process Database and Metrics Definitions to assess a robot's fitness for specific tasks, resulting in a fitness score and classification within the tree. The research appears in the March 2025 issue of Nature Machine Intelligence. Why it matters: This systematic approach could fundamentally change how we understand, compare, and develop robotic systems, enabling a deeper understanding of intelligent machines and their potential.
MBZUAI researchers developed a new deep learning method for rapid and accurate estimation of clinical measurements from echocardiograms. The method focuses on improving the measurement of the left ventricle ejection fraction, a key indicator of heart health. Their deep learning approach improves upon previous methods by better organizing data representation, enhancing performance and transferability. Why it matters: The AI-driven solution can potentially reduce analysis time for cardiologists, improve patient care, and be particularly beneficial in regions with limited healthcare resources.
MBZUAI has launched a full robotics program focusing on robot learning, humanoid robotics, human-computer interaction, and sensory awareness. The program includes research and teaching labs for experimentation and aims to address challenges in agriculture, logistics, and healthcare. The robotics department, founded in 2023, welcomed 18 students in August and is expected to grow to more than 15 faculty members over the next two years. Why it matters: This program signifies a major investment in AI for physical systems in the UAE, potentially leading to innovations across sectors and strengthening MBZUAI's position as a leading AI research institution.
The Abu Dhabi Department of Health (DoH) has partnered with MBZUAI and Core42 to launch the Global AI Healthcare Academy. The academy will provide AI training to healthcare workers in Abu Dhabi, aiming to improve diagnostics, operational efficiency, and patient care. The initiative includes mass training sessions for up to 100 attendees and customized courses in areas like AI for radiology and cardiology. Why it matters: This partnership signals a strategic push to integrate AI into Abu Dhabi's healthcare system, potentially establishing the emirate as a leader in technology-driven healthcare.
Researchers from MBZUAI presented a new algorithm at ICLR 2024 that identifies causal relationships involving both observed and latent variables. The algorithm addresses limitations of existing methods that struggle with latent variables or assume observed variables don't directly influence latent variables. The proposed algorithm can accommodate both scenarios, offering a more generalizable approach to causal discovery. Why it matters: This research advances the development of AI systems that can analyze complex data and identify causal relationships, with potential applications in fields like medicine where understanding causality is crucial for developing treatments and preventative measures.
MBZUAI and Silal, an Abu Dhabi-based agri-food company, signed an MoU at COP28 to bring AI innovation to agriculture and food production. The agreement establishes a joint AI Center of Excellence to develop the UAE's food production sector, improve food security, and enhance sustainability. Both parties will conduct joint research, exchange expertise, and support startups focused on improving efficiency and innovation in the UAE’s food sector. Why it matters: The partnership aligns with the UAE's National Strategy for Food Security 2051 and aims to leverage AI for sustainable food production, addressing critical challenges like climate change and resource management.
MBZUAI Professor Agathe Guilloux developed the SigLasso model to forecast hospitalizations using real-time data from Google and Météo France during the COVID-19 pandemic. The model integrates mobility data and weather patterns to predict hospitalization rates 10-14 days in advance. SigLasso outperformed industry standards like GRU and Neural CDE in reducing reconstruction error. Why it matters: This research demonstrates the potential of AI to improve healthcare resource allocation and crisis management by accurately predicting patient flow using readily available data.
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.
MBZUAI is now ranked 24th globally in AI, computer vision, machine learning, and natural language processing, according to CSRankings. This ranking is attributed to the addition of faculty like Preslav Nakov, Hanan Al Darmaki, and Samuel Horvath. MBZUAI now ranks ahead of universities like the University of Michigan and Imperial College London in specific AI fields. Why it matters: This ranking establishes MBZUAI as the top CS institution in the Arab World and highlights the UAE's growing prominence in AI research.
MBZUAI has been ranked 127th globally among institutions conducting computer science research and ranks 30th globally in AI, computer vision, machine learning, and NLP. This places MBZUAI ahead of universities such as the University of Michigan, Georgia Tech, Imperial College London and others. MBZUAI is now the top-ranked CS institution in the Arab World and the Middle East and Africa according to CSRankings. Why it matters: This ranking highlights the rapid growth and increasing prominence of AI research in the UAE and the broader Middle East.
MBZUAI has established new robotics and computer science departments, launching master’s and Ph.D. programs in each discipline. The new departments will complement MBZUAI’s existing CV, ML, and NLP departments. The robotics department will focus on robot learning and algorithms, while computer science will focus on foundational technologies with an emphasis on entrepreneurship and sustainability. Why it matters: This expansion strengthens the UAE's AI ecosystem and positions MBZUAI as a hub for AI research and innovation, addressing the growing global demand for AI talent.
Researchers from MBZUAI, KAUST, and Mila are collaborating to develop methods for identifying and mitigating the impact of malicious actors in federated learning systems used for health data analysis. These systems aggregate anonymized data from numerous devices to generate insights for healthcare improvements. The team's research, accepted at ICLR 2023, focuses on using variance reduction techniques to counteract the disruptive effects of skewed or corrupted data submitted by dishonest users. Why it matters: Protecting the integrity of AI-driven health systems is crucial for ensuring the reliability and safety of insights derived from sensitive patient data in the GCC region and globally.
MBZUAI and OurCrowd Arabia signed an MoU to accelerate the growth of the AI technology ecosystem at MBZUAI's campus in Abu Dhabi. The initiatives will focus on incubating startups and creating opportunities for AI talent, particularly MBZUAI graduates and researchers. OurCrowd Arabia is also establishing a VC investment center in Abu Dhabi to manage deals for its platform. Why it matters: This partnership aims to foster entrepreneurship and position Abu Dhabi as a global AI center by providing funding and support for AI startups.
MBZUAI is now ranked 19th globally in AI, computer vision, machine learning, and natural language processing according to CSRankings. The university is also top-ranked for computer science in the MENA region. MBZUAI's faculty has grown significantly, with more than 20 new members added in 2022 and Q1 2023, totaling 52. Why it matters: This ranking highlights the rapid rise of MBZUAI as a leading AI research institution in the Middle East, contributing to the UAE's ambitions to become a global AI hub.
MBZUAI has announced partnerships with IBT and BioMap to advance AI applications in healthcare. The collaboration with IBT will focus on developing personalized digital therapeutics for brain health. The partnership with BioMap will establish a biocomputing innovation research lab in the Middle East focused on AI-generated proteins. Why it matters: These partnerships highlight MBZUAI's commitment to leveraging AI for personalized healthcare solutions and establishing the UAE as a hub for biocomputing innovation.
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.
HPE is building a new supercomputer for MBZUAI to accelerate AI research and advance the UAE’s National Strategy for AI. The supercomputer will enhance MBZUAI's ability to run complex AI models and increase predictability in research analyses in fields like energy, transportation, and the environment. The Campus Super Computing Center (CSCC) will house the new supercomputer. Why it matters: This investment strengthens the UAE's AI capabilities and its position as a global leader in AI research and development.
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) has appointed Professor Dr. Eric Xing as its new president, succeeding Interim President Professor Sir Michael Brady. Dr. Xing joins from Carnegie Mellon University, where he was Associate Department Head of Research at the Machine Learning Department. He is a globally recognized AI academic and will lead MBZUAI in developing AI and AI solutions as the first graduate student cohort commences studies. Why it matters: This appointment signals MBZUAI's commitment to attracting top global talent and advancing its mission as a leading AI research institution in the UAE.
MBZUAI researchers are working on digital twin technology that can replicate human beings in detail, with real-time data flow between the physical and virtual. This project aims to extend digital twins from objects to organic entities like humans, plants and animals. The technology mines data from cameras, sensors, wearables, and other sources to predict health issues before they arise. Why it matters: This research has the potential to transform healthcare by enabling the prediction and prevention of health issues.
MBZUAI researchers led by Dr. Mohammad Yaqub are developing AI algorithms for real-time medical diagnoses, including tools for multiple sclerosis and congenital heart disease. The team developed ScanNav, an AI fetal anomaly assessment system licensed by GE Healthcare for Voluson SWIFT ultrasound machines. ScanNav assists doctors during anomaly scans after 20 weeks of gestation to check for conditions like heart issues and spina bifida. Why it matters: This research has the potential to significantly improve the speed and accuracy of medical diagnoses in the UAE and beyond, addressing critical gaps in healthcare.
Michael I. Jordan, a UC Berkeley Distinguished Professor and influential figure in machine learning and AI, has been appointed laureate professor at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI). He will also serve as honorary director of MBZUAI's new Laureate Faculty Program. The program aims to attract leading researchers to MBZUAI by providing resources and minimizing administrative burdens. Why it matters: This appointment strengthens MBZUAI's reputation and enhances the UAE's AI ecosystem by bringing in a world-renowned AI expert to foster research and innovation.
MBZUAI's Dr. Mohammad Yaqub is developing AI algorithms to power point-of-care ultrasound (PoCUS) on mobile devices, expanding on his prior work on an AI-based fetal anomaly system used in GE Healthcare's ultrasound. These algorithms aim to make smaller, affordable PoCUS devices accessible in remote areas for faster diagnoses. The handheld devices, costing around $5000 USD, can connect to mobile devices and provide intelligence to interpret images, addressing the shortage of specialists in remote locations. Why it matters: This initiative democratizes access to critical diagnostic tools, potentially saving lives by enabling early detection of life-threatening conditions in underserved communities.
MBZUAI and Abu Dhabi Health Services Company (SEHA) are collaborating to develop AI algorithms to predict heart attacks months in advance with 87% accuracy using ultrasound images. The project aims to preemptively predict heart attacks in the short and long term, addressing the high rates of cardiac arrest, especially in the Middle East. A Memorandum of Understanding (MoU) was signed between SEHA and MBZUAI to integrate AI into healthcare. Why it matters: This partnership could significantly improve healthcare outcomes in the region by leveraging AI to proactively address heart disease, a leading cause of death.