AI applications in healthcare across the GCC — including medical imaging, clinical decision support, genomics, and health informatics from Gulf universities and hospitals.
Malaysian Prime Minister Anwar Ibrahim visited MBZUAI and was received by UAE Minister Dr. Sultan Al Jaber to strengthen technology ties between the two countries. MBZUAI faculty presented research on healthcare AI, the AIOS platform for efficient AI computing, and LLMs like Vicuna and Jais. MBZUAI also announced partnerships with G42, Cerebras, and India’s Centre for Development of Advanced Computing. Why it matters: The visit underscores the UAE's commitment to AI research and international collaboration, particularly in areas like sustainable AI and Arabic language models.
MBZUAI hosted a two-day workshop on "Big Model AI in Drug Design" starting February 20, 2023. The workshop featured presentations from researchers in public and private institutions working on AI and health. MBZUAI Adjunct Professor Eran Segal opened the workshop with a talk on the Human Phenotype Project. Why it matters: The event highlights the growing interest and activity in applying AI, particularly large models, to advance drug discovery and personalized medicine within the UAE's research ecosystem.
MBZUAI's Kun Zhang is applying causal machine learning to improve drug development and precision medicine, focusing on answering 'why' questions. Traditional drug development is costly (est. $2B) due to extensive studies needed to determine drug toxicity and efficacy. Zhang is combining causal ML with organs-on-chips technology to improve pre-clinical drug testing, aiming to reduce the failure rate of drugs in human trials. Why it matters: By improving the accuracy of pre-clinical drug testing, this research could significantly reduce the cost and time required to bring new medicines to market in the region and worldwide.
An MBZUAI team developed a self-ensembling vision transformer to enhance the security of AI in medical imaging. The model aims to protect patient anonymity and ensure the validity of medical image analysis. It addresses vulnerabilities where AI systems can be manipulated, leading to misinterpretations with potentially harmful consequences in healthcare. Why it matters: This research is crucial for building trust and enabling the safe deployment of AI in sensitive medical applications, protecting against fraud and ensuring patient safety.
Researchers at MBZUAI developed a method to measure vital signs using webcams by analyzing color intensity changes in facial blood flow. They built a digital twin system that uses machine learning to combine heart rate, respiratory rate, and blood oxygen level measures. The system displays real-time vital sign information, enabling remote patient triage. Why it matters: This research contributes to the advancement of telemedicine, potentially improving healthcare access in underserved regions and aligning with UN Sustainable Development Goal #3.
MBZUAI hosted 34 undergraduate STEM students from around the world for its inaugural one-month Undergraduate Research Internship Program (UGRIP) in Abu Dhabi. The interns, hailing from countries including the UAE, USA, and India, engaged in ongoing MBZUAI research projects spanning sustainability, education, and healthcare. Interns worked on projects ranging from fake news detection using NLP to tumor diagnosis using computer vision. Why it matters: This program strengthens MBZUAI's position as a global AI research hub and cultivates AI talent within the region.
MBZUAI's Class of 2023 valedictorian, Klea Ziu, credits her meditation practice for balancing her studies in machine learning. Ziu, the first Albanian graduate from MBZUAI, was among 59 graduates receiving master's degrees in computer vision, machine learning, and NLP. She will represent MBZUAI at COP28 as part of the Climate Ambassador Program, focusing her AI research on reducing carbon dioxide production in the oil and gas industry. Why it matters: This highlights MBZUAI's focus on attracting international talent and applying AI research to sustainability challenges relevant to the UAE and the broader region.
COP28 President-Designate Dr. Sultan Ahmed Al Jaber visited MBZUAI and emphasized AI's role in the UAE's economic diversification and sustainable growth. He highlighted AI's potential to contribute $13 trillion to global GDP by 2030. Al Jaber also met with researchers to discuss projects related to sustainable environment, healthcare, education, and Arabic LLMs. Why it matters: This underscores the UAE's commitment to AI as a key driver for its future economy and its focus on leveraging AI for climate solutions and national priorities.
Emirates Health Services (EHS) and Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) have signed an MoU to strengthen cooperation and knowledge sharing. The agreement focuses on developing human capital, promoting skills, and advancing scientific research and innovation. It includes research opportunities, sponsoring EHS employees for master’s and doctorate degrees at MBZUAI, and providing specialized AI training programs in healthcare. Why it matters: This partnership aims to enhance healthcare efficiency and digital skills in the UAE through AI, contributing to the overall well-being of the population.
MBZUAI's BioMedIA lab, led by Mohammad Yaqub, is developing AI solutions for healthcare challenges in cardiology, pulmonology, and oncology using computer vision. Yaqub's previous research analyzed fetal ultrasound images to correlate bone development with maternal vitamin D levels. The lab is now applying image analysis to improve the treatment of head and neck cancer using PET and CT scans. Why it matters: This research demonstrates the potential of AI and computer vision to improve diagnostic accuracy and accessibility of healthcare in the region and beyond.
MBZUAI faculty Kun Zhang is researching methods to improve the reliability of generative AI, particularly in healthcare applications. Current generative AI models often act as "black boxes," making it difficult to understand why a specific result was produced. Zhang's research focuses on incorporating causal relationships into AI systems to ensure more accurate and meaningful information. Why it matters: Improving the trustworthiness of generative AI is crucial for sensitive sectors like healthcare and ensuring responsible AI deployment across the region.
Sheikha Shamma bint Sultan bin Khalifa Al Nahyan stated that AI is crucial for the UAE to achieve its Net Zero goals by 2050. Other Emirati officials who graduated from the MBZUAI Executive Programme also shared their views on AI applications in healthcare, government services, and energy. They highlighted AI's potential in disease diagnosis, digital transformation, and resource allocation. Why it matters: This underscores the UAE's commitment to leveraging AI across various sectors to address climate change and improve public services.
Eran Segal from Weizmann Institute of Science presented The Human Phenotype Project, a large-scale prospective cohort with over 10,000 participants. The project aims to identify novel molecular markers and develop prediction models for disease onset using deep profiling. The profiling includes medical history, lifestyle, blood tests, and molecular profiling of the transcriptome, genetics, microbiome, metabolome and immune system. Why it matters: Such projects demonstrate the growing focus on personalized medicine in the region, utilizing advanced AI and machine learning techniques for disease prevention and treatment.
Pierre Baldi from UC Irvine presented applications of AI to biomedicine, covering molecular-level analysis of circadian rhythms, real-time polyp detection in colonoscopy videos, and prediction of post-operative adverse outcomes. He discussed integrating AI in future AI-driven hospitals. The presentation was likely part of a panel discussion hosted by MBZUAI in collaboration with the Manara Center for Coexistence and Dialogue. Why it matters: This highlights the growing interest in AI applications within the healthcare sector in the UAE, particularly through institutions like MBZUAI.
MBZUAI showcased AI applications for health, education, and climate at Abu Dhabi Sustainability Week (ADSW) 2023. Talks highlighted AI's capacity to address challenges in climate change and other sectors, aligning with the UAE’s vision for technology-enabled solutions. MBZUAI researchers will demonstrate real-world AI applications and discuss research related to climate, health, and education. Why it matters: MBZUAI's focus on AI for sustainability demonstrates the UAE's commitment to leveraging advanced technology for addressing global challenges and advancing its leadership in clean energy and emissions reduction.
Researchers at Johns Hopkins are developing AI-driven video analysis tools to provide surgeons with unbiased skill assessments and personalized feedback. The system segments surgical procedures, detects instruments, and assesses skill in cataract surgery. Dr. Shameema Sikder is leading the development of technologies to improve ophthalmic surgical care standards internationally. Why it matters: AI-based surgical skill assessment could standardize training and improve patient outcomes in the region and globally.
MBZUAI valedictorian Shahd AlShamsi is using AI and ML to develop personalized cognitive healthcare, shifting treatment from reaction to prevention. Her master's research involves a digital twin framework that integrates representations of a person’s cognitive experience using deep learning models and EEG data. She hopes to develop a mobile application to extend her work to personalized mental health. Why it matters: This research highlights the potential of AI to improve personalized healthcare in the UAE and beyond, and demonstrates the contributions of Emirati researchers.
MBZUAI's Professor Le Song is developing an AI-driven simulation to model the human body at societal, organ, tissue, cellular, and molecular levels. The goal is to reduce the time and cost associated with bringing new medicines to market by removing the need for wet lab biological research. Song aims to create a comprehensive model using machine learning. Why it matters: This research could revolutionize drug discovery in the region by accelerating the development process and reducing reliance on traditional research methods.
MBZUAI master's student Sayed Hashim is applying machine learning to improve cancer diagnosis and treatment, motivated by personal loss. He and fellow student Muhammad Ali developed algorithms for cancer type classification from multi-omics data, achieving over 96% accuracy. Their work, supervised by MBZUAI faculty, resulted in a published paper on multi-omics data representation learning. Why it matters: This research demonstrates the potential of AI and machine learning to advance cancer research and personalized medicine in the region.
MBZUAI faculty, researchers, and students presented eight academic papers at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022) in Singapore. Seven of the accepted papers feature a master’s or doctoral student as first author. The papers are the outcome of two MBZUAI faculty led labs – BioMedical Image Analysis (BioMedIA) lab and SPriNT-AI. Why it matters: This highlights MBZUAI's growing prominence in medical image analysis and AI, showcasing the university's commitment to producing high-quality research and fostering young talent in the field.
MBZUAI showcased its AI research and innovation at GITEX Global 2022 in Dubai, featuring an interactive exhibit. The university highlighted faculty research, student innovations, and presentations, including a keynote by President Eric Xing. A key focus was on AI technologies for the metaverse, led by Hao Li, and innovations like a communication aid for speech-impaired individuals. Why it matters: MBZUAI's presence at GITEX underscores its commitment to advancing AI literacy and demonstrating practical AI applications across diverse sectors in the UAE.
MBZUAI Assistant Professor Samuel Horváth is researching federated learning to address the tension between data privacy and the predictive power of machine learning models. Federated learning trains models on decentralized data, keeping sensitive information on devices. Horváth's research focuses on designing algorithms that can efficiently train on distributed data while respecting user privacy. Why it matters: This work is crucial for advancing AI in sensitive domains like healthcare, where privacy regulations limit centralized data collection.
Professor Hava Siegelmann, a computer science expert, is researching lifelong learning AI, drawing inspiration from the brain's abstraction and generalization capabilities. The research aims to enable intelligent systems in satellites, robots, and medical devices to adapt and improve their expertise in real-time, even with limited communication and power. The goal is to develop AI systems applicable for far edge computing that can learn in runtime and handle unanticipated situations. Why it matters: This research could lead to more resilient and adaptable AI systems for critical applications in remote and resource-constrained environments, with potential benefits for various sectors in the Middle East.
Sami Haddadin from the Technical University of Munich (TUM) discusses a shift in robotics towards machines that autonomously develop their own blueprints and controls. He highlights advancements driven by human-centered design, soft control, and model-based machine learning, enabling human-robot collaboration in manufacturing and healthcare. Haddadin also presents progress towards autonomous machine design and modular control architectures for complex manipulation tasks. Why it matters: This research has implications for advancing robotics and AI in the GCC region, especially in manufacturing and healthcare, by enabling safer and more efficient human-robot collaboration.
Dr. Mohammad Yaqub from MBZUAI will present AI solutions used to combat the COVID-19 pandemic, addressing healthcare consequences, social, economic, and policy-making decisions. The talk will cover the applications of AI and also discuss challenges like privacy, data needs, generalizability, data noise, and human acceptance. Yaqub's background includes a DPhil from the University of Oxford in Biomedical Engineering and research at the Institute of Biomedical Engineering, focusing on machine learning solutions for medical problems. Why it matters: This talk highlights the important role of AI in addressing pandemics and the ethical considerations that come with its application in healthcare and policymaking.
Dr. Xinwei Sun from Microsoft Research Asia presented research on trustworthy AI, focusing on statistical learning with theoretical guarantees. The work covers methods for sparse recovery with false-discovery rate analysis and causal inference tools for robustness and explainability. Consistency and identifiability were addressed theoretically, with applications shown in medical imaging analysis. Why it matters: The research contributes to addressing key limitations of current AI models regarding explainability, reproducibility, robustness, and fairness, which are crucial for real-world applications in sensitive fields like healthcare.
MBZUAI is developing AI algorithms to intelligently process data from wearables and home sensors for remote patient monitoring. The algorithms aim to analyze multiple strands of health data to provide a more comprehensive view of a patient's health, distinguishing between genuine emergencies and benign situations. MBZUAI's provost, Professor Fakhri Karray, believes this approach could handle 20-25% of diagnoses virtually, reducing the burden on healthcare systems. Why it matters: This research could significantly improve healthcare efficiency and accessibility in the UAE and beyond by enabling more effective remote patient monitoring and reducing unnecessary hospital visits.
A delegation from MBZUAI visited Egypt to discuss potential collaborations with Egyptian universities in AI. Discussions involved joint research projects in healthcare and Arabic language processing, establishing joint AI labs, faculty exchange programs, and dual degree programs. MBZUAI expressed its enthusiasm for collaborating with Egyptian universities, offering its faculty and research capabilities. Why it matters: This partnership can help advance AI research and education in both countries, especially in areas like Arabic NLP and AI applications in healthcare, fostering regional AI talent and innovation.
MBZUAI hosted an AI Talks session featuring Dr. Mohammad Yaqub discussing AI's role in fighting COVID-19 and predicting future pandemics. AI can detect outbreaks by mining news and social media for unusual patterns, as demonstrated by companies flagging pneumonia cases in Wuhan before the official announcement. AI-empowered drug repurposing identified Baricitinib as a potential COVID-19 treatment and can predict virus mutations. Why it matters: This highlights the potential of AI to enhance pandemic preparedness and response in the region, particularly through institutions like MBZUAI.
Dr. Pengtao Xie joins MBZUAI as an assistant professor focusing on healthcare and machine learning, inspired by human learning. He is developing automated machine learning methods for healthcare, such as neural architectures for pneumonia detection from chest X-rays. His method achieves state-of-the-art performance with 95% accuracy and is under review by Nature Scientific Report. Why it matters: This appointment strengthens MBZUAI's research capabilities in healthcare AI and signals the university's commitment to attracting top global talent to Abu Dhabi.
Dr. Mohammad Yaqub, an Assistant Professor at MBZUAI, leads the BioMedIA lab and focuses on applying AI to real-world healthcare challenges, particularly in smart imaging. He was inspired by a textbook by Tom Mitchell and his work at Oxford University where he helped develop ScanNav, an AI solution aiding sonographers in anomaly scans during pregnancy. ScanNav assists in assessing fetal growth and detecting abnormalities, potentially improving early intervention. Why it matters: This highlights the growing importance of AI in enhancing medical diagnostics and improving healthcare outcomes in the UAE and globally.
Dr. Min Xu joins MBZUAI as Affiliated Assistant Professor in Computer Vision to advance AI-based biomedical image analysis. His research focuses on cellular cryo-electron tomography (Cryo-ET) 3D image analysis, spatial transcriptomics, digital pathology, and automated science. Xu will collaborate with MBZUAI faculty and advise master’s students, leveraging his expertise in computational biology and bioinformatics. Why it matters: This appointment strengthens MBZUAI's capabilities in applying AI to critical areas of biomedical research, potentially leading to breakthroughs in disease understanding and treatment.
A senior delegation from Weizmann Institute of Science visited MBZUAI in Abu Dhabi to discuss the MBZUAI-WIS Joint Program for Artificial Intelligence Research. The AI Program, announced in February, aims to promote collaborative initiatives in fundamental AI research and explore AI applications in healthcare and genomics. The program will focus on Machine Learning, Computer Vision, NLP, Computational Biology, and Neural Sciences, with plans for researcher appointments and resources. Why it matters: This partnership strengthens the AI ecosystem in the UAE and the region, particularly in fundamental research and key application areas.
MBZUAI AI Talks hosted a webinar on AI in government, featuring Dr. Mohamed Abdelhameed Al Askar of the Abu Dhabi Digital Authority. Dr. Al Askar highlighted use cases such as machine learning for cardiovascular risk calculation, student performance prediction, and traffic safety tools. The UAE aims for a 60% GDP increase by 2031 through AI, with an estimated AED 353 billion economic benefit. Why it matters: This showcases the UAE's proactive approach to integrating AI across various sectors, particularly in public services and infrastructure.
MBZUAI hosted delegates from the US-UAE Business Council Trade Mission to discuss research and education partnerships. Discussions focused on AI research and collaboration in healthcare, with representatives from Abbott, Johnson & Johnson, and leading children's hospitals participating. Potential personnel exchanges and R&D facility development were also explored during the meeting. Why it matters: This engagement strengthens ties between US and UAE institutions, potentially accelerating AI innovation in healthcare and other sectors.
MBZUAI students Mugariya Farooq and Sarah Al Barri created a machine learning framework that classifies plant diseases from images and predicts yield using data inputs. Their project won second place at the Agritech Hackathon organized by the Abu Dhabi Agriculture and Food Security Authority (ADAFSA). The algorithm boasts accuracy above 99% when tested against agricultural scientists. Why it matters: This work showcases AI's potential to revolutionize agriculture in the UAE and the broader MENA region by improving food security, reducing waste, and optimizing resource allocation.
MBZUAI student Karima Kadaoui is developing machine learning algorithms to help speech-impaired individuals communicate more easily. Her project aims to create an app that translates speech impediments into understandable language, facilitating communication with others and integration with voice-enabled technologies like Siri and Google Assistant. The AI-powered app could assist individuals with conditions such as strokes and cerebral palsy, who often struggle with muscle control affecting speech clarity. Why it matters: The research addresses a critical need for inclusive AI solutions, potentially improving the quality of life for speech-impaired individuals in the region and beyond.
H.E. Dr. Sultan Ahmed Al Jaber, Minister of Industry and Advanced Technology and Chairman of the MBZUAI Board of Trustees, visited MBZUAI and discussed the university's role in shaping the UAE's next 50 years. He was briefed on research projects including AI for remote medical care, holographic surgery techniques, and machine learning for enhanced mobility. He emphasized the importance of AI literacy in the UAE government's strategic projects and the university's role in fostering digital, technical, and scientific excellence. Why it matters: The visit underscores the UAE's commitment to AI as a key driver of future solutions and economic progress, with MBZUAI playing a central role in this vision.
Weizmann Institute Professor Eran Segal presented his work on the Human Phenotype Project at MBZUAI. The project is a large-scale biobank with data from over 10,000 participants, integrating medical history, lifestyle, and molecular profiling. Segal aims to use this data to develop personalized disease prevention and treatment plans. Why it matters: This research highlights the potential of interdisciplinary collaboration and big data analysis to advance personalized medicine in the region.
MBZUAI students and researchers presented findings at the Graduate Student Research Conference (GSRC) in Dubai, led by Assistant Professor Mohammad Yaqub. Topics included deep learning, computer learning, disease prediction, and AI in healthcare, with students from the BioMedIA lab presenting their work. Presentations covered areas like fetal ultrasound quality assessment, head and neck cancer diagnosis, and disease risk prediction using generative pre-trained transformers. Why it matters: This showcases MBZUAI's focus on applying AI to solve real-world healthcare problems and highlights the contributions of its students in advancing medical AI research.
MBZUAI Visiting Professor Haiyan Huang is working on bridging biology and AI by incorporating domain knowledge into modeling frameworks. She combines statistical principles, AI tools, and domain expertise to develop scientifically informed and statistically grounded methods. Her work addresses the challenge of extracting meaningful signals from complex biological data.
Researchers introduce Equivariant-Free Transformer-Autoencoded Latent Flow Matching (EF-TALFM), a two-stage generative framework designed to create variable-size 3D molecules using a single fixed-dimensional latent representation. This method employs an autoregressive Transformer decoder to determine molecule size and generate atom types, coordinates, and chemical states without requiring equivariant layers. EF-TALFM achieved 89.4% unique, novel, and sanitized molecules on the PCQM4Mv2 benchmark, outperforming existing models, and demonstrated higher computational throughput. Why it matters: This innovative architecture provides a practical and efficient approach for open-ended and property-directed 3D molecular design, which is crucial for advancements in drug discovery and materials science.
The article emphasizes that laboratory leaders must prioritize workforce enablement to successfully implement artificial intelligence within their operations. It highlights the critical need for comprehensive training, continuous skill development, and fostering an AI-ready culture among laboratory personnel. The piece argues that technological adoption alone, without adequate human preparation and support, will ultimately hinder the full potential of AI applications in laboratory settings. Why it matters: This perspective underscores the essential role of human capital in AI integration, a challenge relevant to organizations globally, including those in the Middle East striving for effective AI adoption and digital transformation.
Researchers at King Abdullah University of Science and Technology (KAUST) found that restoring a key cellular molecule, NAD+, can partially reverse the effects of acidic stress in human cells. Published in Communications Biology, their study utilized a precisely controlled bioreactor system to investigate how mild extracellular acidity disrupts cellular energy generation and mitochondrial function. The research identified NAD+ depletion as a key underlying mechanism and demonstrated that NMN supplementation partially restored cellular function and reduced mitochondrial dysfunction. Why it matters: These findings could inform future strategies to protect cells and support human health, particularly in diseases like cancer and inflammation where acidic conditions are common.
Researchers from King Abdullah University of Science and Technology (KAUST) conducted a study revealing that Red Sea corals absorb and accumulate various compounds, including pharmaceuticals, personal care products, and herbicides, thereby recording a long-term chemical footprint of human activity. The study detected substances like antibiotics, anti-inflammatories, and the herbicide atrazine across 15 reefs in three Red Sea regions, noting that some chemicals were found in higher concentrations offshore due to ocean currents. This research demonstrates how corals can provide a more comprehensive, time-integrated picture of environmental exposure than water samples alone. Why it matters: This work offers a valuable tool for environmental monitoring and informing policy in Saudi Arabia as it expands coastal tourism and other sectors, particularly for the unique Red Sea coral reef ecosystems.
KAUST organized a breast cancer awareness event in Thuwal on October 12, attended by over 150 women and girls from the local community, along with healthcare and education partners. The event featured educational lectures, personal stories from breast cancer survivors, and interactive sessions on early screening. KAUST's director of Social and Community Development highlighted the university's commitment to women's health and empowerment through such initiatives. Why it matters: This event demonstrates KAUST's commitment to social responsibility and community engagement by promoting health awareness and empowering women, aligning with Saudi Vision 2030.
KAUST held a "Run for a Cure" charity race on October 28 for breast cancer research, with over 425 participants from KAUST and partner organizations. A KAUST Ph.D. student discussed her research on non-invasive early cancer detection using plasma blood samples. The event included 10K, 5K, and 3K runs through KAUST, aligning with Vision 2030's goal of increasing public participation in sports. Why it matters: This event highlights KAUST's commitment to healthcare research, community engagement, and supporting national goals for health and sustainability.
KAUST's Impact magazine highlights advancements in health, sustainability, and renewable energy. The third edition showcases research, education, and innovation translated to society, government, and industry. It covers health advances on pages 33 and 37, sustainability on page 20, and renewable energy on pages 17 and 18. Why it matters: The magazine demonstrates KAUST's role in fostering Saudi Arabia's innovation and research ecosystem through various engagements.
KAUST Professor Carlos Duarte presented a lecture on the rebound of global ecosystems following decreased human activity during the COVID-19 pandemic. Duarte, a member of the Rapid Research Response Team (R3T), discussed evidence indicating the environment's capacity for recovery. He related these findings to the potential for positive change in addressing climate change. Why it matters: The lecture highlights KAUST's contribution to understanding the impact of human activity on ecosystems and potential solutions to climate change.
KAUST is increasing campus population due to repatriation flights and additional students coming to campus. There has been a noticeable uptick in new cases of COVID-19, with some presenting with symptoms. KAUST emphasizes the importance of wearing face coverings, observing physical distance, washing hands, avoiding groups of more than 10 people and restricting social networks. Why it matters: This update provides insight into the university's health and safety protocols, reflecting broader trends in managing public health within research institutions in the GCC.