General AI research publications from MBZUAI, KAUST, TII, QCRI, and other GCC institutions, including conference papers, journal articles, and preprints.
A team of MBZUAI graduate students won first place at the UAE University's University Challenge for their SawabAI project, which addresses AI-generated misinformation about climate change. The winning team included Salem Bin Saqer AlMarri, Hanoona Bangalath, and Muhammad Maaz, all Computer Vision Ph.D. students. SawabAI is envisioned as a platform to evaluate the authenticity and source of information, including text, image, and video, to combat fake news. Why it matters: This win highlights the growing importance of AI in addressing misinformation and promoting sustainability in government communication within the region.
MBZUAI President Professor Eric Xing argues against exaggerated claims of AI existential threats, contrasting them with real dangers like climate change and nuclear warfare. He critiques the "doomer outcry" fueled by sensationalism rather than rational analysis, emphasizing the importance of evidence-based discussion. Xing suggests that overregulation risks stifling the startup and open-source community, which are vital for transparent and responsible AI development. Why it matters: The piece advocates for a balanced perspective on AI's risks and benefits, promoting informed discussion over alarmist narratives in the region's rapidly developing AI landscape.
To meet Net Zero Emissions goals, governments and corporations need to drive a wholesale energy transition. Current energy grids are outdated and need to be updated to handle renewable energy's specific demands. Research at MBZUAI is helping to create smarter grids by using AI to monitor and measure energy flow in real-time. Why it matters: AI-empowered smart grids can help accelerate the energy transition by enabling more efficient and reliable use of renewable energy sources.
MBZUAI researchers presented a new approach to video question answering at ICCV 2023. The method leverages insights from analyzing still images to understand video content, potentially reducing the computational resources needed for training video question answering models. Guangyi Chen, Kun Zhang, and colleagues aim to apply pre-trained image models to understand video concepts. Why it matters: This research could lead to more efficient and accessible video analysis tools, benefiting fields like healthcare and security where video data is abundant.
MBZUAI has been actively involved in developing AI and generative models, contributing to models like Llama 2, Jais, Vicuna, and LaMini. Professor Preslav Nakov notes Llama 2's improvements in size and carbon footprint over Llama 1. MBZUAI aims to tackle challenges like information accuracy, economic costs, and the scarcity of Arabic online content. Why it matters: MBZUAI's work helps address the limitations of current LLMs, particularly for Arabic, and promotes sustainable AI development in the region.
MBZUAI Professor Fakherddine Karray is developing deep learning algorithms for human activity recognition to monitor the health and safety of elderly people. The AI tools analyze movement, posture, and facial expressions to detect early warning signs of health emergencies. Remote patient monitoring systems integrate smart devices and secure communication to allow elderly patients to stay at home and communicate with healthcare providers. Why it matters: AI-powered smart homes can provide affordable healthcare solutions for the rapidly growing elderly population in the region and worldwide.
MBZUAI and Etihad Airways have signed an MoU to explore AI applications in the aviation sector. The partnership includes joint training programs, research, seminars, and workshops. MBZUAI students will gain aviation industry experience and explore AI's potential in addressing challenges. Why it matters: The collaboration aims to enhance AI competitiveness in the UAE's aviation sector and foster sustainable growth and innovation.
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 AI Quorum launched its second workshop, "Building Ecosystems for AI at Scale," focusing on AI scalability and business applications. The first CASL workshop aims to define steps for organizations to become self-sufficient with AI and explore new use cases. Speakers include MBZUAI faculty and researchers from CMU, Stanford, KAUST, UC Berkeley, and Google. Why it matters: The workshop highlights the UAE's growing role in fostering AI innovation and bridging the gap between academic research and industry applications in the region.
MBZUAI launched the AI Quorum, a winter series from October 2022 to March 2023, to stimulate AI research. The first session, led by Professor Michael Jordan, focused on collaborative learning with around 20 research experts. Discussions covered the use of edge devices like cell phones and hospitals providing data to build large models, as well as risks like free-riding and adversarial attacks. Why it matters: The AI Quorum initiative positions MBZUAI as a hub for global AI collaboration, addressing key challenges and opportunities in collaborative learning for real-world applications.
MBZUAI had 30 papers accepted at the International Conference on Computer Vision (ICCV) in Paris, out of 8,260 submissions. Visiting Professor Ivan Laptev served as one of the ICCV Program Chairs. Two papers from MBZUAI researchers focused on analyzing moving images, with one introducing Video-FocalNets for action analysis and the other exploring the transfer of knowledge from still image analysis to video. Why it matters: MBZUAI's strong presence at ICCV demonstrates its growing prominence in the global computer vision research landscape.
MBZUAI researchers presented a new approach to video analysis at ICCV in Paris, led by Syed Talal Wasim. The approach builds on still image processing techniques like focal modulation to analyze spatial and temporal information in video separately. It aims to improve temporal aggregation while avoiding the computational complexity of transformers. Why it matters: This research advances video understanding in computer vision by offering a more efficient method for temporal modeling, crucial for applications like activity recognition and video surveillance.
MBZUAI's Qirong Ho and colleagues are developing an Artificial Intelligence Operating System (AIOS) for decarbonization, aiming to reduce energy waste in AI development. The AIOS focuses on improving communication efficiency between machines during AI model training, as inefficient communication leads to prolonged tasks and increased energy consumption. This system addresses the high computing power demands of large language models like ChatGPT and LLaMA-2. Why it matters: By optimizing energy usage in AI development, the AIOS could significantly reduce the carbon footprint of AI technologies in the region and globally.
A team of MBZUAI students won the Pioneers 4.0 Hackathon by developing an AI-based predictive maintenance solution using sensor data. The solution uses data preprocessing techniques and the Prophet model to identify anomalies in manufacturing, leading to energy savings and preventing sensor outages. The hackathon, organized by MoIAT and EDGE, involved 15 students from UAE universities. Why it matters: This highlights the practical application of AI skills being cultivated at UAE universities and their potential to address industrial challenges in line with the UAE's 4IR strategy.
MBZUAI President Eric Xing discussed the transformative potential of AI with Abu Dhabi's Department of Community Development, likening its impact to that of the printing press. He emphasized AI's role in democratizing knowledge and enabling discoveries in genetics, pharmaceuticals, and healthcare. Xing also highlighted the UAE's strategic thinking and openness to innovation, positioning the nation as an international leader in AI, exemplified by MBZUAI's Jais LLM. Why it matters: This signals the UAE's continued focus on AI as a strategic priority, with emphasis on its potential to drive societal and economic development.
MBZUAI has implemented three HyFlex (hybrid flexible) classrooms using Zoom to connect remote and in-person students. The classrooms include smart whiteboards, sensor cameras, and multiple screens, benchmarked against setups at Harvard and King's College. A research article on the development of MBZUAI's HyFlex approach is under peer review. Why it matters: This initiative enhances hybrid learning in the region and provides a model for other universities looking to integrate advanced technology into their educational spaces.
MBZUAI is prioritizing natural language processing (NLP) research, aiming to be a top university in the field within 12-18 months according to Professor Timothy Baldwin. MBZUAI's NLP department is focusing on deep learning, algorithmic fairness, computational social science and social media analytics. A key area is Arabic NLP, addressing the challenges of dialectal variations and code-switching in social media. Why it matters: This focus on Arabic NLP and real-world problem-solving will contribute to the UAE's ambitious agenda of growing a local AI industry and integrating AI into various sectors.
MBZUAI Professor Preslav Nakov is researching methods to combat fake news and online disinformation through NLP techniques. His work focuses on detecting harmful memes and identifying the stance of individuals regarding disinformation. Four of Nakov’s recent papers on these topics were presented at NAACL 2022. Why it matters: This research aims to mitigate the impact of weaponized news and online manipulation, contributing to a more trustworthy information environment in the region and globally.
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 Professor Chih-Jen Lin gave a keynote at the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval in Taipei. Lin's address, titled ‘On the “Rough Use” of Machine Learning Techniques’, focused on instances where machine learning techniques are employed inappropriately, using examples from graph representation learning and deep neural networks. He advocated for the development of high-quality, user-friendly software to improve the practical application of machine learning and mitigate misuse. Why it matters: Showcases MBZUAI's faculty expertise and contributions to the discussion on responsible AI research and deployment on a global stage.
MBZUAI graduate Ahmed Elhagry received the Best Ph.D. Forum Paper Award at IEEE MetaCom 2023 for his work on generating virtual worlds using digital twin technology and AI through a text-to-metaverse pipeline. The research addresses the challenge of manually constructing 3D models for metaverse applications, which is time-consuming and costly. Elhagry's approach uses multimodal AI and DT technology to produce realistic virtual environments, benefiting industries like education, healthcare, and entertainment. Why it matters: This award recognizes innovative research at MBZUAI with the potential to advance metaverse development and AI-driven virtual environment creation in the region.
MBZUAI welcomed 142 students from 34 countries, its largest and most diverse cohort since 2019, with a competitive admission rate of 4.6% out of over 4,000 applications. The new students are pursuing master's and Ph.D. degrees in computer vision, machine learning, and natural language processing, bringing the total student body to nearly 300. MBZUAI also established new robotics and computer science departments to meet global demand. Why it matters: This expansion strengthens the UAE's position as a global AI research hub, attracting top talent and fostering innovation in key AI disciplines.
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 Professor Fakhri Karray and co-authors from the University of Waterloo have published "Elements of Dimensionality Reduction and Manifold Learning," a textbook on methods for extracting useful components from large datasets. The book addresses the challenge of the "curse of dimensionality," where growth in datasets complicates their use in machine learning. Karray developed the material from a popular course he taught at Waterloo. Why it matters: The textbook provides a unified resource for students and researchers in machine learning and AI, addressing a foundational challenge in processing high-dimensional data, relevant to diverse applications in the region.
MBZUAI 2023 graduate Muhammad Umar is researching propaganda detection in low-resource, code-switched languages like Roman Urdu. His master's thesis focuses on detecting propaganda techniques in social media text using deep learning models. Umar aims to submit a paper on his findings to the EMNLP 2023 conference. Why it matters: This research addresses the under-explored area of propaganda detection in low-resource languages, which is crucial for combating misinformation in bilingual communities.
MBZUAI graduate Gokul Karthik Kumar credits the university's interdisciplinary approach for helping him discover his passion for working at the intersection of computer vision and NLP. He chose MBZUAI over the University of Waterloo due to the flexibility to explore different AI domains. Kumar will join G42’s Inception Institute of Artificial Intelligence (IIAI) as an applied scientist to develop large language models tailored for UAE-focused applications. Why it matters: This highlights MBZUAI's role in nurturing AI talent for the UAE and G42's focus on developing local LLMs.
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.
MBZUAI Board of Trustees member Anil K. Jain received the 2023 Technology Transfer Achievement Award from Michigan State University for his work in biometric recognition. Jain developed core algorithms for biometric pattern representation and search, licensing these technologies to industry. He also advised India's Aadhaar, the world's largest biometric ID system. Why it matters: This award highlights the importance of translating academic research into practical applications that impact society, particularly in the realm of secure identification and access.
An article in Forbes highlights the Mohammed bin Zayed University of Artificial Intelligence (MBZUAI) as the first university devoted exclusively to AI advancement. MBZUAI President Eric Xing champions a 'connectionism' approach, designing computational models inspired by interconnected human cognition networks. AI's ability to process and analyze data at high speeds unlocks new knowledge realms, acting as a universal translator between humans and the digital world. Why it matters: MBZUAI is positioned as a key institution driving AI innovation and responsible AI practices in the Middle East.
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 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.
MBZUAI faculty Alham Fikri Aji, Timothy Baldwin, and Fajri Koto won an Outstanding Paper Award at EACL 2023 for their paper "NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages." The paper introduces the first parallel resource for 10 Indonesian low-resource languages to boost performance in sentiment analysis and machine translation. The dataset is available on HuggingFace. Why it matters: This work highlights MBZUAI's commitment to advancing NLP research in low-resource languages, which can help preserve linguistic diversity and improve access to digital resources for speakers of underrepresented languages.
MBZUAI researchers are using federated learning to optimize energy production and use in microgrids, balancing individual and grid-level needs with a focus on sustainability. They presented a multi-agent framework called MAHTM at the ICLR 2023 workshop, aiming to minimize the carbon footprint of electrical grids. The system uses three layers of decision-making agents to minimize cost, decrease carbon impact, and balance production. Why it matters: This research offers a novel approach to integrating renewable energy sources into existing grids, potentially accelerating the transition to more sustainable energy systems in the region and globally.
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 students participated in the Climate Ambassadors Programme (CAP) at Expo City Dubai, role-playing a COP28 session. Representing different countries, the students developed innovative climate change solutions, emphasizing AI's role. The event, part of a series leading up to COP28, saw MBZUAI ambassadors highlighting the need for proactive environmental action. Why it matters: This initiative showcases the potential of AI-focused education in addressing global climate challenges and promoting youth engagement in sustainability efforts within the UAE.
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.
MBZUAI President Eric Xing has been named a 2023 Fellow of the Institute of Mathematical Statistics (IMS). He was honored for contributions to statistics, machine learning research, AI entrepreneurship, and AI education. The IMS will formally recognize the 2023 fellows at the Joint Statistical Meetings in Toronto in August. Why it matters: This recognition highlights the growing prominence of MBZUAI and its leadership in the international AI and statistics community.
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 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 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.
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.
The article discusses the challenges in effectively applying text classification techniques, despite the availability of tools like LibMultiLabel. It highlights the importance of guiding users to appropriately use machine learning methods due to considerations in practical applications such as evaluation criteria and data strategies. The piece also mentions a panel discussion hosted by MBZUAI in collaboration with the Manara Center for Coexistence and Dialogue. Why it matters: This signals ongoing efforts within the UAE AI ecosystem to address practical challenges and promote responsible AI usage in NLP applications.
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.
Giulia De Masi, Principal Scientist at the Technology Innovation Institute (TII) in Abu Dhabi, specializes in Collective Intelligence and Swarm Robotics. Her work focuses on designing emergent behaviors in robot swarms through local interactions, drawing inspiration from social insects. De Masi's background includes positions at academic institutions in the UAE and a PhD from the University of Rome La Sapienza. Why it matters: This highlights the growing focus on swarm robotics and collective intelligence research within the UAE, with potential applications in various industries.