MBZUAI researchers will present 20 papers at the 40th International Conference on Machine Learning (ICML) in Honolulu. Visiting Associate Professor Tongliang Liu leads with seven publications, followed by Kun Zhang with six. One paper investigates semi-supervised learning vs. model-based methods for noisy data annotation in deep neural networks. Why it matters: The research addresses the critical issue of data quality and accessibility in machine learning, particularly for organizations with limited resources for data annotation.
MBZUAI held its Class of 2023 commencement ceremony, graduating 59 students with master's degrees in CV, ML, and NLP. The ceremony was attended by UAE officials including Sheikh Hamed bin Zayed Al Nahyan and Dr. Sultan bin Ahmed Al Jaber. Dr. Al Jaber emphasized AI's role in addressing global challenges and supporting the UAE's economic diversification and sustainability goals. Why it matters: The graduation highlights the UAE's ongoing investment in AI talent development and its focus on leveraging AI to address critical challenges in climate, healthcare, and education.
MBZUAI and RIKEN-AIP (Japan) co-hosted a joint workshop at MBZUAI's Masdar City campus. The workshop facilitated the sharing of research and perspectives across machine learning, computer vision, and natural language processing. Researchers from both institutions explored interdisciplinary cooperation to enhance AI's capacity to address real-world problems. Why it matters: This collaboration strengthens MBZUAI's position as a hub for cross-disciplinary AI research and fosters international partnerships in the field.
Two teams from MBZUAI won awards at the IEEE SLT international hackathon held in Qatar. One team won the "Best Potential Impact Project" award for Autodub, a human-in-the-loop AI dubbing platform. The second MBZUAI team won the "Craziest Idea Award" for a commentator voice synthesizer for video games. Why it matters: The wins highlight MBZUAI's strength in applied AI research and its students' ability to develop innovative solutions with practical applications.
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 Professor Fahad Khan is working on a unified theory of machine visual intelligence. His goal is to enable AI systems to better understand and function in complex, chaotic visual environments. The aim is to improve real-world applications like smart cities, personalized healthcare, and autonomous vehicles. Why it matters: This research could significantly advance AI's ability to perceive and interact with the real world, especially in challenging environments common in the developing world.
MBZUAI students Hanoona Bangalath and Muhammad Maaz, with perfect GPAs, had papers accepted at ECCV 2022 ("Class-agnostic Object Detection with Multi-modal Transformer") and NeurIPS 2022 ("Bridging the Gap between Object and Image-level Representation for Open-Vocabulary Detection"). Both will stay at MBZUAI for their PhDs, crediting the university's resources and faculty. Their supervisor, Salman Khan, praised their curiosity and hard work, highlighting their role in building the institution's reputation. Why it matters: The success of these students underscores MBZUAI's potential to foster high-quality AI research and attract top talent to the UAE.
MBZUAI researchers are working to improve computer vision models by incorporating common sense knowledge. They aim to address issues like the generation of unrealistic human features, such as hands with incorrect numbers of fingers. By integrating common-sense knowledge, like the fact that humans typically have five fingers per hand, they seek to make deep learning models more reliable. Why it matters: This research could improve the accuracy and trustworthiness of AI-generated content, making it more suitable for real-world applications.
Bruno Ribeiro from Purdue University presented a talk on Asymmetry Learning and Out-of-Distribution (OOD) Robustness. The talk introduced Asymmetry Learning, a new paradigm that focuses on finding evidence of asymmetries in data to improve classifier performance in both in-distribution and out-of-distribution scenarios. Asymmetry Learning performs a causal structure search to find classifiers that perform well across different environments. Why it matters: This research addresses a key challenge in AI by proposing a novel approach to improve the reliability and generalization of classifiers in unseen environments, potentially leading to more robust AI systems.
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.
Ian Reid, a Professor of Computer Science at the University of Adelaide, gave a talk at MBZUAI on leveraging deep learning to go beyond geometric SLAM. The talk covered using prior domain knowledge to improve map and shape estimation and enabling navigation in unvisited environments. The research aims to turn cameras into devices for flexible, large-scale situational awareness or "Spatial AI" sensors. Why it matters: Integrating deep learning with SLAM could significantly advance robotic navigation and spatial understanding, with applications for autonomous systems in various industries.
MBZUAI and the Weizmann Institute of Science (WIS) are deepening research ties through ongoing engagement and knowledge sharing. A delegation from MBZUAI visited WIS to discuss collaboration across a range of research projects overseen by a joint review board. The partnership, formalized in 2021 through the MBZUAI-WIS Joint Program for Artificial Intelligence Research, focuses on advancing research in natural and machine intelligence. Why it matters: This collaboration strengthens the AI research ecosystem in the region and leverages expertise from both institutions to develop AI technologies for societal benefit.
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.
A recent study questions the necessity of deep ensembles, which improve accuracy and match larger models. The study demonstrates that ensemble diversity does not meaningfully improve uncertainty quantification on out-of-distribution data. It also reveals that the out-of-distribution performance of ensembles is strongly determined by their in-distribution performance. Why it matters: The findings suggest that larger, single neural networks can replicate the benefits of deep ensembles, potentially simplifying model deployment and reducing computational costs in the region.
MBZUAI has opened graduate admissions for the 2023/2024 academic year, offering master’s and doctoral programs in computer vision, machine learning, and natural language processing. The university ranks in the top 25 globally in AI, computer vision, machine learning, and NLP, according to Computer Science Rankings. In Fall 2022, MBZUAI welcomed 125 new students, including 22 doctoral and 105 master’s students, bringing the total student population to over 250. Why it matters: This signals continued growth for MBZUAI as a leading AI research institution in the region, attracting international talent and contributing to the development of AI expertise in the UAE.
MBZUAI has launched a Metaverse Lab led by Hao Li, focusing on integrating computer vision, graphics, and machine learning for metaverse applications. The lab aims to develop AI algorithms for photorealistic virtual humans and dynamic environment digitization. Pinscreen, Li's AI startup, previously created avatars for Expo 2020 Dubai. Why it matters: This initiative positions MBZUAI and the UAE as key players in the development of core technologies underpinning the metaverse and digital communication.
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.
This article discusses retrieval augmentation in text generation, where information retrieved from an external source is used to condition predictions. It references recent work on retrieval-augmented image captioning, showing that model size can be greatly reduced when training data is available through retrieval. The author intends to continue this work focusing on the intersection of retrieval augmentation and in-context learning, and controllable image captioning for language learning materials. Why it matters: This research direction has the potential to improve transfer learning in vision-language models, which could be especially relevant for downstream applications in Arabic NLP and multimodal tasks.
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 faculty and researchers had 27 papers accepted at the 2022 NeurIPS conference. 12 MBZUAI faculty members have at least one paper accepted, with Professor Kun Zhang leading with 10 papers. Other faculty with accepted publications include Eric Xing, Le Song, and Fahad Khan. Why it matters: This achievement highlights MBZUAI's growing prominence in the global machine learning research community.
Researchers at MBZUAI have developed Auto-DUB, a system using deep learning, NLP, and CV to improve audio-visual dubbing, particularly for educational videos. The three-step process generates subtitles, creates an audio representation, and synchronizes the audio with lip movements. The system aims to overcome language barriers in e-learning by providing accurate translations and lip-synced audio. Why it matters: This research addresses a critical need in online education by making content more accessible to non-native English speakers, potentially expanding access to global educational resources in the Arab world.
Daniela Rus from MIT CSAIL discussed the role of AI in revolutionizing autonomous vehicles, emphasizing the need for risk evaluation, intent understanding, and adaptation to diverse driving styles. The talk highlighted integrating risk and behavior analysis in autonomous vehicle control systems. Social Value Orientation (SVO) can be incorporated into decision-making for self-driving vehicles. Why it matters: This research advances the development of safer and more adaptive autonomous vehicles, crucial for their successful deployment in diverse real-world driving scenarios within the GCC region and globally.
WAM (Emirates News Agency) and MBZUAI have signed a strategic agreement to collaborate on media and AI, knowledge sharing, training, and development. MBZUAI will be the Strategic Academic Sponsor of the Global Media Congress organized by ADNEC and WAM in November 2022. MBZUAI will also provide WAM employees with seats in its Executive Program and offer consultancy services for establishing an AI lab at WAM. Why it matters: This partnership aims to modernize the UAE's media sector by leveraging MBZUAI's AI expertise to develop innovative media applications and support the Global Media Congress.
MBZUAI Professor Salman Khan is researching continuous, lifelong learning systems for computer vision, aiming to mimic human learning processes like curiosity and discovery. His work focuses on learning from limited data and adversarial robustness of deep neural networks. Khan, along with MBZUAI professors Fahad Khan and Rao Anwer, and partners from other universities, presented research at CVPR 2022. Why it matters: This research has the potential to significantly improve the ability of AI systems to understand and adapt to the real world, enabling more intelligent autonomous systems.
MBZUAI welcomes Hao Li, CEO of Pinscreen, as a new faculty member specializing in virtual humans. Li envisions a future where virtual humans facilitate interactions and overcome limitations of physical presence, citing benefits like improved education and remote collaboration. His work focuses on the intersection of computer vision, computer graphics, and machine learning to enable immersive digital experiences. Why it matters: This signals MBZUAI's commitment to advancing research in virtual reality and the metaverse, potentially positioning the UAE as a leader in this emerging field.
Professor Ling Shao, Executive Vice President and Provost of MBZUAI, has been elected an IEEE Fellow. This honor recognizes his contributions to computer vision and representation learning. The IEEE Fellowship is a prestigious distinction given to select IEEE members. Why it matters: This recognition highlights the growing prominence of MBZUAI and its faculty in the international AI research community.
MBZUAI board member Sir Michael Brady and Weizmann Institute's Shimon Ullman lectured in the fourth module of MBZUAI’s Executive Program on December 11. Brady led a session on 'Artificial Intelligence (AI) and Image Analysis,' while Ullman presented on ‘AI and Human Intelligence: Lessons From Computer Vision.’ The 12-week Executive Program aims to educate high-level decision makers in AI, supporting the UAE's AI leadership mission. Why it matters: Showcases MBZUAI's commitment to attracting top global talent and fostering AI education for leadership in the UAE.
MBZUAI faculty members led or co-led several top global AI conferences in 2022, including ACL, ICML, CLeaR, and UAI. Faculty members Timothy Baldwin, Le Song, Kun Zhang, and Preslav Nakov held leadership positions at these conferences. According to CSRankings, MBZUAI ranks in the top 30 globally in AI, computer vision, machine learning, and NLP. Why it matters: This highlights MBZUAI's growing influence and reputation in the global AI research community, solidifying its position as a leading institution in the field.
MBZUAI faculty member Dr. Hang Dai won first and second place in the Commands 4 Autonomous Vehicles (C4AV) Workshop Challenge at ECCV 2020. Dr. Dai participated in the competition as part of two teams, earning top spots for using AI in autonomous vehicles. The C4AV Workshop Challenge aims to develop models for joint understanding of vision and language in self-driving cars. Why it matters: This win demonstrates MBZUAI's commitment to advancing AI research and its applications in key areas like autonomous vehicles.
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.
MBZUAI Associate Professor Karthik Nandakumar is conducting computer vision research with students, focusing on security, privacy, and trustworthiness in AI. His SPriNT-AI lab is developing machine learning algorithms for industries like energy, health, and security, aligning research with the UAE’s strategic goals. One project involves using drones to detect defects in solar plants in collaboration with Masdar. Why it matters: This applied research contributes to the UAE's sustainable development goals and enhances the practical skills of AI students for local industry needs.
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.
UAE University (UAEU) and Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) are strengthening research ties through collaboration. A UAEU delegation visited MBZUAI to discuss joint programs and cooperation, aiming to develop academic talent. MBZUAI has 133 students from 40 countries enrolled in graduate programs like computer vision, machine learning, and NLP. Why it matters: This partnership between two leading UAE institutions can help advance the nation's AI capabilities and contribute to its 50-year vision.
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 welcomed its second cohort of students for the Fall 2021 semester, totaling 74 students across master's and Ph.D. programs. The incoming class includes 41 students in Computer Vision, 24 in Machine Learning, and 9 in the inaugural Natural Language Processing program. The cohort represents 29 nationalities, including 10 UAE nationals, and includes graduates from universities such as Purdue, Edinburgh, and Khalifa University. Why it matters: This demonstrates MBZUAI's continued growth as a global AI research institution attracting international talent to Abu Dhabi.
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 hosted a virtual Student Opportunities Fair, connecting its AI students with UAE employers. 26 companies including ADNOC, Etihad, Huawei, and Majid Al Futtaim attended the fair. Students explored internships ranging from NLP to big data applications. Why it matters: The event highlights the growing demand for AI talent in the UAE and MBZUAI's role in developing a skilled workforce for the nation's AI ambitions.
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 alumnus Abdelrahman Shaker discusses his evolving perspective on impactful AI research, shifting from publication counts to real-world usefulness. He highlights the success of his SwiftFormer and EdgeNext papers, which have been adopted by third parties and reached millions of users. Shaker chose MBZUAI for its faculty expertise, which led to 10 publications and over 2,500 citations during his Ph.D.
Google has reportedly rolled back a controversial AI feature within its Google Earth product. The decision follows public or internal controversy surrounding the feature's implementation or impact. The specific details of the feature and the nature of the controversy were not immediately available. Why it matters: This incident highlights the ongoing challenges in deploying AI features responsibly and the importance of addressing user feedback and ethical concerns in product development.
Apple is set to introduce new AI-powered photo editing features, including 'Extend', 'Enhance', and 'Reframe', as part of its Apple Intelligence suite within iOS 27. These tools are designed to offer users advanced capabilities for manipulating and improving their images directly on their devices. The announcement highlights Apple's continued integration of generative AI into its core consumer products. Why it matters: This development reflects the broader industry trend of embedding sophisticated AI functionalities into everyday consumer technology, influencing user experience and adoption across markets, including the Middle East.
This research presents a post-hoc framework to explain, verify, and align semantic hierarchies within vision-language model (VLM) encoders like CLIP. The method involves agglomerative clustering of class centroids, naming internal nodes via dictionary matching, and quantifying plausibility against human ontologies. Findings across 13 VLMs and 4 datasets reveal that image encoders are more discriminative, while text encoders induce hierarchies better matching human taxonomies, showing a trade-off between zero-shot accuracy and ontological plausibility. Why it matters: This work provides critical insights into the internal organization of VLM embeddings, which is essential for improving their explainability, reliability, and alignment with human knowledge, leading to more trustworthy AI systems.
Zoom is expanding its artificial intelligence strategy by introducing new features such as photorealistic avatars and AI-powered productivity applications. The company is also rolling out a custom agent builder, allowing users to create tailored AI agents for various tasks. These advancements aim to enhance user experience and streamline workflows within the Zoom platform. Why it matters: While a significant global tech development, this news is less directly relevant to the specific focus on Middle East AI news and papers due to its general industry nature and lack of specific regional application.
Researchers have reportedly developed an artificial intelligence system capable of deblurring photographs. This AI aims to enhance image clarity by using advanced algorithms to reconstruct sharper images from blurry inputs. The technology could significantly improve visual quality across various applications where image capture is prone to blur. Why it matters: This development contributes to the broader field of computer vision and image processing, offering potential applications in areas from surveillance to professional photography.
Artificial intelligence is increasingly being utilized to generate and update detailed street maps directly from satellite imagery. This technology automates the identification and extraction of roads, buildings, and other geographical features, significantly reducing the manual effort traditionally required for cartography. It offers a solution for rapidly updating maps in dynamic urban environments and for mapping remote or previously uncharted areas. Why it matters: This advancement improves the accuracy and timeliness of geospatial data, essential for navigation, urban planning, disaster management, and infrastructure development globally.
An artificial intelligence system has been developed that can reconstruct human faces from images affected by motion blur. This technology leverages advanced algorithms to reverse the blurring effect, enhancing facial clarity and detail. The system aims to improve image quality in various applications where motion artifacts are common. Why it matters: This advancement holds significant potential for applications in forensics, security surveillance, and improving consumer photography by recovering lost detail in images.
Shozo Yokoyama, a biology professor at Emory University specializing in color vision evolution, was interviewed by KAUST. Yokoyama's lab identified amino acids regulating red-green and UV vision in vertebrates. He emphasizes the importance of young scientists developing fresh perspectives on evolution and learning directly from animals. Why it matters: While not directly an AI story, the piece highlights KAUST's broader research focus and its investment in attracting and showcasing international scientific expertise, relevant to building a strong research ecosystem.
Margaret Livingstone, a neurobiology professor at Harvard Medical School, lectured at KAUST's Winter Enrichment Program 2018 on how art can reveal insights into the human brain. She discussed how artists have long understood the independent roles of color and luminance in visual perception. Livingstone highlighted examples from Picasso, Monet, and Warhol to illustrate how artists manipulate visual cues. Why it matters: This interdisciplinary approach can potentially lead to new understandings of how the brain processes visual information and inform advances in both neuroscience and art.
KAUST PhD students David Castro and David Conchouso won the 2014 Art in Science photography competition sponsored by NIST and Lab on a Chip. The winning photograph depicted work from KAUST's Electromechanical Microsystems & Polymer Integration Research Lab (EMPIRe), specifically real-time agglutination within a microdroplet. The photo will be featured on a future cover of the journal Lab on a Chip. Why it matters: This award highlights the visually compelling nature of microfluidics research and showcases the interdisciplinary work at KAUST.
Dezhen Song from Texas A&M University presented a talk on Co-Modality Active sensing and Perception (C-MAP) for robotics, covering sensor fusion for autonomous vehicles, augmented reality, and remote environmental monitoring. The talk highlighted lessons learned in sensor fusion using autonomous motorcycles and NASA Robonaut as examples. Recent works in robotic remote environment monitoring, especially focused on subsurface surface void and pipeline mapping were discussed. Why it matters: This research explores sensor fusion techniques to enhance robot perception, which could improve the robustness and capabilities of autonomous systems developed and deployed in the Middle East, particularly in challenging environments.