UAE President Sheikh Mohamed bin Zayed Al Nahyan visited MBZUAI and was briefed on academic programs, research areas, and partnerships. Researchers presented AI projects spanning energy, climate, medicine, genetics, media, and robotics, and two start-ups from the university’s incubator showcased their work. MBZUAI President Professor Eric Xing noted the university's ranking as 10th globally in AI fields. Why it matters: The visit underscores the UAE's commitment to developing national AI talent and building a knowledge-based economy with AI at its core.
MBZUAI hosted the third edition of its Mailis program, focusing on AI's role in redefining the workplace and strengthening the UAE’s innovation ecosystem. The session brought together entrepreneurs, policymakers, and innovators from Abu Dhabi’s government, business, and startup sectors to discuss AI integration. Leaders from organizations like Khalifa Fund and Hub71 shared updates on AI initiatives, while MBZUAI showcased AI tools that can act as a co-founder. Why it matters: This event highlights the UAE's commitment to fostering AI adoption and collaboration across sectors, positioning the country as a leader in responsible AI innovation.
MBZUAI concluded its 2025 Undergraduate Research Internship Program (UGRIP), hosting 57 students from 24 countries. The four-week program, held in Abu Dhabi, allowed undergraduates to collaborate with faculty on AI research projects in machine learning, computer vision, and NLP. The 2025 edition had a 4% acceptance rate, with nearly 2,000 applications received. Why it matters: The program highlights MBZUAI's role in attracting global AI talent to the UAE and fostering research collaborations.
MBZUAI has joined the Aspen Institute’s Technology Leaders Initiative as a founding partner, alongside the Institute for Ethics in AI at the University of Oxford. This two-year program within the Aspen Global Leadership Network will convene 20 senior leaders from the global technology ecosystem. The initiative aims to explore ethical innovation, responsible leadership, and the societal impact of technology. Why it matters: The partnership highlights MBZUAI's commitment to fostering responsible AI development and ethical leadership in the technology sector.
MBZUAI alumnus Kane Lindsay is using AI to digitize and analyze plant specimens at Kew Gardens, including handwritten notes and preserved plants dating back centuries. He developed an AI model to recognize handwriting (OCR) and extract phenotype data from plant images, and another to redact sensitive location data. This work began as an internship and evolved into a fully funded Ph.D. Why it matters: AI is accelerating the digitization and preservation of plant collections, making them more accessible to researchers and aiding in conservation efforts.
MBZUAI hosted a Single Cell Summer Workshop, gathering over 25 participants and speakers to explore single-cell omics data. The two-day event featured three workshops, nine talks, and networking opportunities, aiming to develop bioinformatics skills and strengthen the regional ecosystem. Workshops were led by Eduardo Beltrame (MBZUAI), Mariano Gabitto (Allen Institute), and Luke Zappia (Data Intuitive), covering topics like scvi-tools, multimodal machine learning, and benchmarking. Why it matters: This workshop signifies MBZUAI's commitment to advancing bioinformatics research in the UAE and fostering collaboration within the regional scientific community.
MBZUAI's Computational Biology department hosted the first Data Carpentry workshop in the UAE, a global initiative focused on foundational data science skills for researchers. The workshop included 35 participants from academia and industry, covering topics like data tidiness, cloud computing, command lines, and data wrangling. 70% of the participants were female, and several were Emirati nationals. Why it matters: This initiative addresses the growing need for computational skills in genomics research, bridging the gap between wet lab experiments and data analysis for scientists in the UAE.
MBZUAI has launched the 6th edition of its Executive Program (MEP) aimed at empowering over 40 senior leaders from UAE's public and private sectors with AI knowledge. The 16-week program will cover AI fundamentals, industry transformations, strategy, policymaking, and ethics. Participants will explore a refreshed curriculum with immersive learning experiences, site visits, and an Ideas Launchpad to address real-world challenges. Why it matters: The program demonstrates the UAE's commitment to AI upskilling and aims to accelerate AI-driven transformations across sectors by equipping leaders with strategic, technical, and ethical foundations of AI.
MBZUAI will participate as an official partner at Machines Can See 2025 (MCS 2025) during Dubai AI Week, showcasing AI innovation with expert speakers and live demos. MBZUAI will present BiMediX2, a multimodal virtual assistant that answers medical questions in Arabic and English and won Meta’s Llama Impact Innovation Award. They will also demonstrate Voodoo XP, a one-shot face re-enactment tool, and LAIKA, an AI-powered robot dog. Why it matters: This event highlights MBZUAI's contributions to AI and robotics, strengthening the UAE's position as a leader in science and technology, especially in healthcare and advanced robotics.
MBZUAI alumnus Hanan Gani, a 2024 master's graduate in machine learning, is now a research associate at MBZUAI working on a meteorological project with the UAE government. He also focuses on multimodal and embodied intelligence research, mentors AI students, and has published nine papers during his time at MBZUAI. His research includes work on vision transformers, text-to-image generation, and large multimodal models. Why it matters: Showcases MBZUAI's role in attracting and developing AI talent within the UAE, contributing to the nation's AI research capabilities.
MBZUAI and UC Berkeley held a joint workshop on machine learning, featuring discussions on online learning, fair allocation in dynamic mechanism design, and causal inference. Michael I. Jordan, Laureate Professor and Honorary Program Director at MBZUAI, highlighted the institute's rapid growth during his visit. Researchers explored methods for enhancing the properties of large, complex models, such as calibration, fairness, and robustness. Why it matters: Such collaborations advance AI research and foster knowledge exchange between leading global experts and regional institutions like MBZUAI.
MBZUAI is hosting the Augmented Humans International Conference 2025 in the Middle East for the first time, in cooperation with the ACM. The conference focuses on physical, cognitive, and perceptual augmentations of humans through digital technologies. 30 papers were selected from 77 submissions, with participation from researchers from institutions like MIT Media Lab and the University of Tokyo. Why it matters: This event underscores the UAE's commitment to AI research and human-computer interaction, fostering collaboration and driving progress in augmentation technologies for societal benefit.
MBZUAI's Undergraduate Research Internship Program (UGRIP) is a one-month summer program in Abu Dhabi for promising AI students. Launched in 2023, UGRIP aims to expose undergraduates to AI research and talent development. In 2025, around 60 interns will join the program to work on research projects and receive mentorship from faculty. Why it matters: The program strengthens Abu Dhabi's position as a hub for AI research and attracts global talent.
MBZUAI held its fourth annual Internships and Opportunities Fair, connecting over 160 students with 48 industry partners. The fair provided a platform for students to explore internships and career opportunities in AI-related fields. Participating companies included ADNOC, Abu Dhabi Police, e&, and IBM. Why it matters: The event highlights the growing demand for AI talent in the UAE and MBZUAI's role in supplying skilled graduates to the local AI ecosystem.
MBZUAI's executive programs (MEP and MEP-A) have trained nearly 240 senior leaders from the UAE's public and private sectors to implement AI solutions. Cohort six of the MEP begins in April, while the MEP-A will commence later in the year. The programs, taught by instructors from MBZUAI, UC Berkeley, Oxford, Harvard, and MIT, cover AI fundamentals, industry applications, strategy, policymaking, and ethics. Why it matters: These programs aim to empower leaders to contribute to the UAE's growing AI ecosystem and promote ethically-rooted innovation, aligning with the UAE's national AI strategy.
Gregory Chirikjian presented an overview talk on applying probability, harmonic analysis, and geometry to robotics, emphasizing the need for robots to function beyond traditional industrial programming. He discussed a new approach where robots define affordances of objects, using simulation to 'imagine' object use and enabling reasoning about novel objects. Probabilistic methods on Lie-groups, initially developed for mobile robot state estimation, are now adapted for one-shot learning of affordances, with plans to integrate large language models. Why it matters: This research direction aims to enhance robot intelligence and adaptability, crucial for service robots in dynamic environments and aligning with broader goals of advanced AI integration in robotics.
A talk discusses the challenges of single-cell data analysis, such as feature sparsity and the effects of rare cells. AI/ML strategies are uniquely positioned to model this data. ImYoo, a startup founded in 2021, is applying single-cell model architectures for unsupervised discovery of patient groupings and predicting sample-level phenotypical data in autoimmune disease. Why it matters: This highlights the growing application of AI/ML in analyzing single-cell data for population-scale human health studies, an area ripe for innovation and improvement in the Middle East's growing biotech sector.
MBZUAI hosted a panel discussion in collaboration with the Manara Center for Coexistence and Dialogue. The discussion focused on the intersection of AI and medical image computing. Jiebo Luo, a professor at the University of Rochester, discussed his work on applying AI to healthcare, including moving beyond classification to semantic description and expanding use from hospitals to home telemedicine. Why it matters: This highlights the increasing focus on AI applications in healthcare within the Middle East, particularly at institutions like MBZUAI, which are fostering discussions on the ethical and practical implications of AI in medicine.
Niket Tandon from the Allen Institute for AI presented a talk at MBZUAI on enabling large language models to focus on human needs and continuously learn from interactions. He proposed a memory architecture inspired by the theory of recursive reminding to guide models in avoiding past errors. The talk addressed who to ask, what to ask, when to ask and how to apply the obtained guidance. Why it matters: The research explores how to align LLMs with human feedback, a key challenge for practical and ethical AI deployment.
Dr. Mikhail Burtsev of the London Institute presented research on GENA-LM, a suite of transformer-based DNA language models. The talk addressed the challenge of scaling transformers for genomic sequences, proposing recurrent memory augmentation to handle long input sequences efficiently. This approach improves language modeling performance and holds promise for memory-intensive applications in bioinformatics. Why it matters: This research can significantly advance AI's capabilities in genomics by enabling the processing of much larger DNA sequences, with potential breakthroughs in understanding and treating diseases.
Thamar Solorio from the University of Houston presented preliminary work on multimodal representation learning for detecting objectionable content in videos at MBZUAI. The research investigates two multimodal pretraining mechanisms, finding contrastive learning more effective than unimodal representation prediction. The study also assesses the value of common multimodal corpora for this task. Why it matters: This research contributes to the development of AI techniques for content moderation, an important issue for online platforms in the Middle East and globally.
A partner at Oblon, Stefan Uwe Koschmieder, explained key points for patenting software and AI inventions. Koschmieder works with GCC universities on IP programs and advises foreign clients on IP portfolio management. He also lectured at Freie Universität Berlin on Intellectual Property. Why it matters: As software and AI innovation grows in the GCC, understanding patent law is increasingly important for protecting intellectual property and fostering local innovation.
A talk at MBZUAI discussed federated learning, a distributed machine learning approach training models over devices while keeping data localized. The presentation covered a straggler-resilient federated learning scheme using adaptive node participation to tackle system heterogeneity. It also presented a robust optimization formulation for addressing data heterogeneity and a new algorithm for personalizing learned models. Why it matters: Federated learning is crucial for AI applications involving decentralized data sources, and research on improving its robustness and personalization is essential for real-world deployment in the region.
Dr. Xiaoming Liu from Michigan State University discussed computer vision techniques for 3D world understanding at a talk hosted by MBZUAI. The talk covered 3D reconstruction, detection, depth estimation, and velocity estimation, with applications in biometrics and autonomous driving. Dr. Liu also touched on anti-spoofing and fair face recognition research at MSU's Computer Vision Lab. Why it matters: Showcasing international experts and research directions helps to catalyze computer vision and 3D understanding research efforts within the UAE's AI ecosystem.
Jingjin Yu from Rutgers University presented research on multi-robot coordination and robotic manipulation at MBZUAI. The talk covered Rubik Table algorithms for collision-free path planning for multiple robots in dense settings. It also discussed algorithms for long-horizon manipulation tasks like rearrangement and object retrieval. Why it matters: Advancements in multi-robot coordination and manipulation are crucial for deploying robots in various sectors within the UAE and beyond, such as logistics and elder care.
Joonhyuk Kang from KAIST gave a presentation at MBZUAI on AI's impact on wireless communication. The talk covered how communication systems can improve AI and how AI can develop wireless systems. Kang's research interests include signal processing for information transmission, security, and machine cognition. Why it matters: This talk highlights the growing intersection of AI and communication technologies in the region, with potential applications for smart cities and autonomous systems.
This article discusses the application of AI in semiconductor chip design and manufacturing, with a focus on examples such as IR-drop estimation and lithography processes. It mentions Youngsoo Shin, a KAIST professor and founder of Baum, who is an expert in this area. The article also briefly mentions panel discussion hosted by MBZUAI. Why it matters: AI-driven chip design and manufacturing could accelerate semiconductor innovation in the GCC region and beyond.
Dr. Zeke Xie from HKUST(GZ) presented research on noise initialization and sampling strategies for diffusion models. The talk covered golden noise for text-to-image models, zigzag diffusion sampling, smooth initializations for video diffusion, and leveraging image diffusion for video synthesis. Xie leads the xLeaF Lab, focusing on optimization, inference, and generative AI, with previous experience at Baidu Research. Why it matters: The work addresses core challenges in improving the quality and diversity of generated content from diffusion models, a key area of advancement for AI applications in the region.
A professor from Nanyang Technological University (NTU), Singapore gave a talk at MBZUAI about "Just-Noticeable Difference (JND)" models in visual intelligence. The talk covered visual JND models, research and applications, and future opportunities for JND modeling. JND can help tackle big data challenges with limited resources by focusing on user-centric and green systems. Why it matters: Exploring JND could lead to advancements in AI applications related to visual signal processing, image synthesis, and generative AI in the region.
MBZUAI student Ahmed AlShamsi and his team won the Gulf Hackathon for Cybersecurity in Oman for their Secure+ platform. Secure+ uses AI to detect phishing links, identify the source, and provide users with statistics about malicious emails. The platform allows users to browse links safely on the Secure+ server. Why it matters: The award highlights the growing entrepreneurial ecosystem around cybersecurity and AI in the GCC, fostered by initiatives like CyberE71 and guidance from leaders like Dr. Mohamed Al Kuwaiti.
Marc Pollefeys from ETH Zurich and Microsoft Spatial AI Lab will discuss building 3D environment representations for assisting humans and robots. The talk covers visual 3D mapping, localization, spatial data access, and navigation using geometry and learning-based methods. It also explores building rich 3D semantic representations for scene interaction via open vocabulary queries leveraging foundation models. Why it matters: Advancements in spatial AI and 3D scene understanding are critical for enabling more capable robots and AI assistants in various applications within the region.
Professor Cesare Stefanini will discuss the relationship between AI and natural systems, highlighting robotics inspired by nature. His talk will cover neuro-inspired robot control, bio-hybrid ecosystems, and advancements in biomedical and industrial robotics. Stefanini will share achievements in underwater robot locomotion, AI-powered biomedical systems, and industrial platforms enhancing human manipulation. Why it matters: The talk at Khalifa University reflects the UAE's interest in bio-robotics research and integrating AI into various sectors, potentially fostering collaborations and advancements in the field.
Holger Pirk from Imperial College London is developing a novel approach to data management system composition called BOSS. The system uses a homoiconic representation of data and code and partial evaluation of queries by components, drawing inspiration from compiler-construction research. BOSS achieves a fully composable design that effectively combines different data models, hardware platforms, and processing engines, enabling features like GPU acceleration and generative data cleaning with minimal overhead. Why it matters: This research on composable database systems can broaden the applicability of data management techniques in the GCC region, enabling more flexible and efficient data processing for various applications.
Tetsunari Inamura's talk explores using VR to collect HRI data and tailor assistive robotic functionalities to individual users. He discusses symbol emergence via multimodal interaction, interactive behavior generation through symbol manipulation, and VR for data collection. The talk emphasizes long-term human capability enhancement and avoiding over-reliance on technology. Why it matters: This research promotes independence and growth in human-robot interactions, potentially revolutionizing assistive technologies in the region.
Dr. Hao Dong from Peking University presented research on addressing the challenge of limited large-scale training data in embodied AI, particularly for manipulation, task planning, and navigation. The presentation covered simulation learning and large models. Dr. Dong is a chief scientist of China's National Key Research and Development Program and an area chair/associate editor for NeurIPS, CVPR, AAAI, and ICRA. Why it matters: Overcoming data scarcity is crucial for advancing embodied AI research and enabling more sophisticated robotic applications in the region.
Krishna Murthy, a postdoc at MIT, researches computational world models to enable robots to understand and operate effectively in the physical world. His work focuses on differentiable computing approaches for spatial perception and interfaces large image, language, and audio models with 3D scenes. Murthy envisions structured world models working with scaling-based approaches to create versatile robot perception and planning algorithms. Why it matters: This research could significantly advance robotics by enabling more sophisticated perception, reasoning, and action capabilities in embodied agents.
Eduardo da Veiga Beltrame, bioinformatics lead at ImYoo (a Caltech spinout), presented on scalable methods for single-cell omics data analysis, including kallisto|bustools and scvi-tools. He highlighted their use in ImYoo's decentralized longitudinal study on Inflammatory Bowel Disease (IBD), where patients self-collect capillary blood samples. Beltrame also discussed his research on STEM education programs in Brazil as a visiting scholar at UC Berkeley. Why it matters: This highlights the growing trend of decentralized clinical studies leveraging advanced single-cell technologies for precision medicine, showcasing the potential of remote data collection and analysis in understanding complex diseases.
Doug Greenig, Group CEO and CIO of Florin Court Capital based in London and Abu Dhabi, discussed macro trends in 2024 and beyond. Florin Court's Programme has delivered strong returns since 2017, capturing macro themes through alternative markets. Prior to founding Florin Court, Doug held leadership roles at Man/AHL, Fortress Investment Group, and Goldman Sachs. Why it matters: The presence of a leading systematic asset manager like Florin Court in Abu Dhabi signals the growing importance of the UAE as a hub for sophisticated financial firms leveraging AI and quantitative strategies.
Dr. Jindong Wang from Microsoft Research Asia gave a talk at MBZUAI about the limitations of large foundation models, including adapting to real-world unpredictability and security concerns. He also discussed the need for interdisciplinary collaboration to evaluate the benefits and risks of these models. Dr. Wang shared his research and insights on how to harness the power of large foundation models while addressing their constraints and fostering responsible AI integration. Why it matters: This highlights MBZUAI's role in hosting discussions about responsible AI development and the challenges of deploying foundation models.
Ekaterina Radionova from Smarter AI (formerly Samsung AI Center) presented an approach to generating lifelike real-time avatars. The work focuses on generating high-quality video with authentic facial features to support online generation. Radionova's master's degree is from Skoltech on Data Science program and Bachelor degree at Moscow Institute of Physics and Technology on Applied Math. Why it matters: Achieving realistic real-time avatars is critical for applications in online communication, entertainment, and virtual reality within the region.
Giuseppe Loianno from NYU presented research on creating "Super Autonomous" robots (USARC) that are Unmanned, Small, Agile, Resilient, and Collaborative. The research focuses on learning models, control, and navigation policies for single and collaborative robots operating in challenging environments. The talk highlighted the potential of these robots in logistics, reconnaissance, and other time-sensitive tasks. Why it matters: This points to growing research interest in advanced robotics in the region, especially given the focus on smart cities and automation.
Nicu Sebe from the University of Trento presented recent work on video generation, focusing on animating objects in a source image using external information like labels, driving videos, or text. He introduced a Learnable Game Engine (LGE) trained from monocular annotated videos, which maintains states of scenes, objects, and agents to render controllable viewpoints. Why it matters: This talk highlights advancements in cross-modal AI, potentially enabling new applications in gaming, simulation, and content creation within the region.
Dr. Yali Du from King's College London will give a presentation on learning to cooperate in multi-agent systems. Her research focuses on enabling cooperative and responsible behavior in machines using reinforcement learning and foundation models. She will discuss enhancing collaboration within social contexts, fostering human-AI coordination, and achieving scalable alignment. Why it matters: This highlights the growing importance of research into multi-agent systems and human-AI interaction, crucial for developing AI that integrates effectively and ethically into society.
Qingbiao Li from the Oxford Robotics Institute is researching decentralized multi-robot coordination using Graph Neural Networks (GNNs). The approach builds an information-sharing mechanism within a decentralized multi-robot system through GNNs and imitation learning. It also uses visual machine learning-assisted navigation with panoramic cameras to guide robots in unseen environments. Why it matters: This research could improve the effectiveness of automated mobile robot systems in urban rail transit and warehousing logistics in the GCC region, where smart city initiatives are growing.
Akhil Arora from EPFL presented a framework for AI-assisted knowledge navigation, focusing on understanding and enhancing human navigation on Wikipedia. The framework includes methods for modeling navigation patterns, identifying knowledge gaps, and assessing their causal impact. He also discussed applications beyond Wikipedia, such as multimodal knowledge navigation assistants and multilingual knowledge gap mitigation. Why it matters: This research has the potential to improve information systems by making online knowledge more accessible and navigable, especially for platforms like Wikipedia that serve as critical resources for global knowledge sharing.
Ehsan Hoque from the University of Rochester gave a talk at MBZUAI discussing how to integrate AI into healthcare to improve access and equity. He emphasized that technology should align with values and infrastructure, advocating for AI solutions developed through collaboration between computer scientists and healthcare professionals. Hoque presented examples like using AI to quantify movement disorders and improve empathy skills. Why it matters: This highlights the importance of human-centered AI development in the GCC region, particularly in sensitive sectors like healthcare, and MBZUAI's role in fostering such discussions.
Sai Praneeth Karimireddy from UC Berkeley presented a talk on building planetary-scale collaborative intelligence, highlighting the challenges of using distributed data in machine learning due to data silos and ethical-legal restrictions. He proposed collaborative systems like federated learning as a solution to bring together distributed data while respecting privacy. The talk addressed the need for efficiency, reliability, and management of divergent goals in these systems, suggesting the use of tools from optimization, statistics, and economics. Why it matters: Collaborative AI systems can unlock valuable distributed data in the region, especially in sensitive sectors like healthcare, while ensuring privacy and addressing ethical concerns.
Eyal Ofek of Microsoft Research is researching how to augment users' senses and use scene understanding to create more inclusive workspaces, especially for remote work. His work involves designing applications flexible to changing environments and personalized to each user. Ofek's background includes computer vision, augmented reality, and leading research groups at Microsoft. Why it matters: This research aims to improve remote collaboration and adapt technology to individual user needs, which could enhance productivity and inclusivity in the evolving work landscape of the GCC region.
The InterText project, funded by the European Research Council, aims to advance NLP by developing a framework for modeling fine-grained relationships between texts. This approach enables tracing the origin and evolution of texts and ideas. Iryna Gurevych from the Technical University of Darmstadt presented the intertextual approach to NLP, covering data modeling, representation learning, and practical applications. Why it matters: This research could enable a new generation of AI applications for text work and critical reading, with potential applications in collaborative knowledge construction and document revision assistance.
Daisuke Kihara from Purdue University presented a seminar at MBZUAI on using deep learning for biomolecular structure modeling. His lab is developing 3D structure modeling methods, especially for cryo-electron microscopy (cryo-EM) data. They are also working on RNA structure prediction and peptide docking using deep neural networks inspired by AlphaFold2. Why it matters: Applying advanced deep learning techniques to biomolecular structure prediction can accelerate drug discovery and our understanding of molecular functions.