Natural language processing research from GCC institutions, covering Arabic NLP, multilingual models, text classification, named entity recognition, and machine translation.
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 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 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 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.
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.
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.
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 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.
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.
A Mixture of Experts (MoE) layer is a sparsely activated deep learning layer. It uses a router network to direct each token to one of the experts. Yuanzhi Li, an assistant professor at CMU and affiliated faculty at MBZUAI, researches deep learning theory and NLP. Why it matters: This highlights MBZUAI's engagement with cutting-edge deep learning research, specifically in efficient model design.
MBZUAI's president Eric Xing discussed AI career prospects after the university's first graduation. He also addressed the risks of ChatGPT and other AI developments. MBZUAI's Cesare Stefanini contributed to the development of underwater robots, while researchers Thamar Solorio, Monojit Choudhury, and Aseem Srivastava will study loneliness in digital spaces. Why it matters: The interview highlights MBZUAI's role in shaping AI talent and addressing societal impacts of AI in the UAE and beyond.
MBZUAI appointed Ekaterina Kochmar as an assistant professor of NLP to advance AI-assisted learning. Kochmar co-founded Korbit AI, an AI-powered dialogue-based tutoring system for STEM subjects. Korbit AI aims to democratize education by providing personalized, high-quality education globally at minimal cost. Why it matters: This appointment highlights MBZUAI's commitment to AI in education and personalized learning, positioning the UAE as a hub for innovation in educational technology.
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.
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.
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 Professor Preslav Nakov believes AI can outpace human fact-checkers in detecting fake news by analyzing language and sentence structure. AI systems can identify common sources of fake news and flag domains for blocking. Nakov's research focuses on disinformation, fact checking, and media bias detection. Why it matters: AI-driven solutions for combating fake news could help mitigate the spread of misinformation and its impact on society, especially in the Arabic-speaking world.
MBZUAI's Hanan Al Darmaki is working to improve automated speech recognition (ASR) for low-resource languages, where labeled data is scarce. She notes that Arabic presents unique challenges due to dialectal variations and a lack of written resources corresponding to spoken dialects. Al Darmaki's research focuses on unsupervised speech recognition to address this gap. Why it matters: Overcoming these challenges can improve virtual assistant effectiveness across diverse languages and enable more inclusive AI applications in the Arabic-speaking world.
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 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 welcomed 127 new students from over 25 countries for the Fall 2022 semester, bringing the total student population to 259. The incoming class includes 22 doctoral students and 105 master’s students across computer vision, machine learning, and natural language processing. 32% of the new students are female, and 30 are UAE nationals who will support the UAE’s National Strategy for AI 2031. Why it matters: This continued growth of MBZUAI's student body strengthens the UAE's AI talent pool and supports its national AI strategy.
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.
NYUAD and MBZUAI co-hosted the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP) in Abu Dhabi from December 7-11. EMNLP is a top-tier NLP and AI conference organized by the ACL special interest group on linguistic data (SIGDAT). MBZUAI's Natural Language Processing Department is actively developing NLP datasets and methods to solve social problems. Why it matters: Hosting EMNLP in the UAE highlights the growing importance of NLP research in the region and the increasing contributions of local institutions like MBZUAI to the field.
MBZUAI hosted a panel discussion in collaboration with the Manara Center for Coexistence and Dialogue. Chaoyang He, co-founder of FedML, presented on federated learning (FL), covering privacy/security, resource constraints, label scarcity, and scalable system design. FedML is a platform for zero-code, cross-platform, secure federated learning across industries like healthcare and finance. Why it matters: Federated learning is an important subfield for the GCC region, allowing privacy-preserving model training across distributed data sources.
MBZUAI Visiting Assistant Professor Gus Xia studies music to understand how AI can act more human-like in high-context activities. Xia analyzes and creates music with computers to explore the differences between human and machine perception. He aims to leverage music's abstract nature to study creative intelligence in AI. Why it matters: This research could lead to AI systems that interact more naturally with humans, particularly in creative fields.
MBZUAI Professor Kun Zhang's research focuses on causality in AI systems, aiming to understand underlying processes beyond data correlation. He emphasizes the importance of causality and graphical representations to model why systems produce observations and account for uncertainty. Zhang served as a program chair at the 38th Conference on Uncertainty in Artificial Intelligence (UAI) in Eindhoven. Why it matters: This highlights the growing importance of causality and uncertainty in AI research, crucial for responsible AI deployment and decision-making in the region.
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.
MBZUAI Department Chair Le Song served as a program co-chair at the 39th International Conference on Machine Learning (ICML). MBZUAI faculty, researchers, and students had 7 papers accepted at ICML 2022. Song noted the increasing focus on biomedicine and other science areas within the AI research community. Why it matters: Song's leadership role at ICML and MBZUAI's strong presence highlights the university's growing influence in the global machine learning landscape.
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.
This article discusses adversarial training (AT) as a method to improve the robustness of machine learning models against adversarial attacks. AT aims to correctly classify data and ensure no data fall near decision boundaries, simulating adversarial attacks during training. Dr. Jingfeng Zhang from RIKEN-AIP will present on improvements to AT and its application in evaluating and enhancing the reliability of ML methods. Why it matters: As ML models become more prevalent in real-world applications in the GCC region, ensuring their robustness against adversarial attacks is crucial for maintaining their reliability and security.
Dr. Maxim Panov from TII Abu Dhabi will give a talk on uncertainty estimation in neural networks, covering model calibration, ensemble methods, and Bayesian approaches. The talk will focus on efficient single-network methods for quantifying prediction confidence, without requiring ensembles or major training changes. Panov's background includes experience at Skolkovo Institute of Science and Technology and DATADVANCE Company. Why it matters: Improving uncertainty estimation is crucial for deploying reliable AI systems in critical applications across the GCC region.
Ekaterina Kochmar from the University of Bath presented the Korbit Intelligent Tutoring System (ITS), an AI-powered dialogue-based platform providing personalized learning experiences. A comparative study showed that students using Korbit achieved 2-2.5 times higher learning gains and higher completion rates compared to a traditional MOOC platform. Kochmar is also a co-founder and CSO of Korbit AI. Why it matters: The research highlights the potential of AI to deliver personalized education and significantly improve learning outcomes in online STEM education, an area of focus for many GCC universities.
Ted Briscoe from the University of Cambridge discussed using machine learning and NLP to develop learning-oriented assessment (LOA) for non-native writers. The technology is used in Cambridge English courseware like Empower and Linguaskill, as well as Write and Improve. Briscoe is also the co-founder and CEO of iLexIR Ltd. Why it matters: Improving automated language assessment could significantly enhance online language learning platforms in the Arab world and beyond.
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 has appointed Professor Timothy Baldwin as Associate Provost and acting chair of its new NLP Department. Baldwin will focus on strengthening the curriculum and building a world-class faculty team. He previously spent 17 years at the University of Melbourne. Why it matters: The recruitment signals MBZUAI's commitment to becoming a leading center for NLP research and education in the region.
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 Professor Kun Zhang received a Test of Time Award Honorable Mention at ICML 2022 for his 2012 paper “On causal and anticausal learning." The paper, co-authored with researchers from the Max-Planck Institute, is considered foundational for causal learning in machine learning. Zhang's work demonstrated the importance of causality for machine learning tasks, helping to shift views in the field. Why it matters: This award highlights the growing recognition of causal AI research and MBZUAI's role in advancing the field.
MBZUAI has launched online refresher courses in math and programming for its inaugural cohort of 100 admitted students from 31 countries. These courses, taught by MBZUAI faculty, aim to prepare students for the M.Sc. and Ph.D. programs in computer vision and machine learning starting January 2021. The courses are designed to provide a comprehensive refresher in core subjects. Why it matters: This initiative ensures students are well-prepared for the specialized AI education at MBZUAI and helps foster a strong foundation for future AI research in the region.
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.
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.
MBZUAI Professor Timothy Baldwin delivered the presidential keynote at the 60th Annual Meeting of the Association for Computational Linguistics (ACL). Baldwin also published three papers at the conference, including work on biomedical literature summarization, NLP for Indonesian languages, and understanding procedural texts. The papers address challenges such as reducing human effort in reviewing medical documents and digitally preserving Indonesian indigenous languages. Why it matters: Baldwin's contributions and leadership role at ACL highlight the growing prominence of MBZUAI and GCC-based researchers in the global NLP community.
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.