The first cycle (2024) concluded with 24 projects from 13 universities and 43 academic entities selected for grants. These projects benefitted 219 researchers and addressed key challenges through advanced R&D.
Dr. Yacine Hadijat
Associate Professor, Mohammed Bin Rashid University of Medicine and Health Sciences
“I am honored and excited to be part of the inaugural Dubai Research, Development, and Innovation (RDI) Grant Initiative, which stands at the forefront of advancing global solutions in health and technology. Our project presents a tremendous opportunity to transform how patients and clinicians assess and manage pain, a critical issue in healthcare. By combining advanced technologies with health sciences excellence, we aim to provide millions of patients suffering from pain with accurate, objective, and personalized measurement solutions. In collaboration with Professor Jinane Mounsef from RIT Dubai UAE and Professor Lars Arendt-Nielsen from Aalborg University Danmark, we are eager to develop innovative, Tech-driven approaches that leverage real-time data, wearables and digital biomarkers. This initiative not only fosters groundbreaking research but also reinforces Dubai’s commitment to innovation, excellence, and a future defined by knowledge, technology, resilience and better patient care.”
PainDetect is a pioneering research and development initiative aiming to redefine the way healthcare providers assess and manage pain. Traditional methods rely on patients’ subjective self-reports, which can be unreliable or impossible to obtain in cases where individuals cannot communicate effectively—such as infants, sedated patients, or those with specific neurological conditions. Our multidisciplinary team is developing a cutting-edge platform that integrates wearable sensor technologies, AI, and personalized data analytics to provide an objective measure of pain in real time.
By using physiological biomarkers—including heart rate variability, electrodermal activity, and other autonomic indicators—PainDetect will establish a novel “Pain Index” that transcends traditional scales and turns subjective interpretation into objective measurement.
Through advanced deep learning models and extensive clinical validation, the platform aims to accurately gauge pain levels with high degrees of accuracy against standard pain-rating systems. In addition to enabling immediate clinical decision-making, the system’s adaptability will cater for a wide range of medical settings, from post-surgical recovery to cancer pain management.
The impact of PainDetect’s work goes beyond simple technological enhancement. By offering a more reliable measure of pain, healthcare providers can optimize treatments and therapeutic benefit/risk balance, particularly for treatments with known risk profiles and complex conditions.
This paradigm shift could contribute significantly to improving pain evaluation, measurement and management for millions of suffering people, including underserved populations such as non-communicant patients.
Led by Dubai Health and the Mohammed Bin Rashid University of Medicine and Health Sciences, supported by renowned collaborators at Rochester Institute of Technology in Dubai and Aalborg University in Denmark, PainDetect aligns with the UAE’s vision for innovative healthcare solutions and sets the stage for global transformation in pain management. The project aims to deliver cutting-edge technologies, major scientific advancement, and enhanced clinical practices for the benefit of people suffering from pain globally.
Dr. Firuz Kamalov
Professor, Canadian University DubaiCanadian University Dubai
“The Dubai RDI program exemplifies Dubai’s commitment to advancing health and AI research on a global scale. Being part of this initiative is both an honor and an exciting opportunity. We are eager to contribute to the city’s research ecosystem and showcase the exceptional talent driving innovation in Dubai.”
This project, led by Canadian University Dubai, pioneers an Explainable Artificial Intelligence (AI) system aimed at the early detection of dementia and its potential progression, particularly prodromal Alzheimer’s disease (AD). By combining cognitive, neuropsychiatric, and biomarker data, the system identifies subtle changes associated with the earliest stages of dementia. It leverages an innovative Explainable AI algorithm, designed to provide transparent and human-interpretable insights that enhance clinical and patient trust.
Aligned with Dubai’s RDI Grant Program in Health and Life Sciences, the initiative underscores a commitment to advancing healthcare through cutting-edge technology. An international consortium of senior academics and researchers, each with extensive expertise in AI, cognitive neuroscience, and biomarker analysis, will collaborate to consolidate large-scale datasets—sourced in part from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
Key deliverables include a diagnostic software platform that integrates machine learning models with new rule-based methods, accessible via a cloud-based service and intuitive web interface. The system’s robust design facilitates earlier detection of prodromal dementia, enabling timely interventions and management strategies. Beyond its technical achievements, the project aims to publish its findings in top tier journals and explore patent opportunities.
The expected impact is significant: earlier diagnosis can improve patient care, guide clinical decision-making, and offer vital support to families. By training and involving Emirati staff, the project also contributes to the UAE’s broader objective of empowering local talent in health technology. Overall, this research represents a major step toward transforming dementia care through AI-driven innovation.
Dr. Ananth Bharadwaj
Assistant Professor, Birla Institute of Technology & Science, Pilani, Dubai Campus
” With extensive research experience in near-field resonant wireless power transfer, I am excited to advance wireless charging technology for electric drones through this RDI Grant. This project focuses on developing an efficient, misalignment-tolerant charging system to overcome key limitations in extending drone range. I look forward to contributing to innovations that enhance autonomous drone operations for critical applications.”
The proposed project, titled Development of an Efficient, Misalignment-Tolerant Wireless Charging System to Extend the Range of Electric Drones, aims to address the critical limitations of electric drones restricted operational range due to frequent manual recharging. By developing a high-efficiency wireless charging system capable of misalignment tolerance, the project seeks to enhance the reliability and functionality of drones for diverse applications, including medical emergencies, disaster management, continuous surveillance, and efficient package delivery.
This project employs a novel hybrid approach integrating field-forming techniques and advanced circuit designs to create optimized transmitter (Tx) and receiver (Rx) coil pads. The system will achieve over 90% power transfer efficiency while ensuring precision alignment through a real-time localization mechanism. By strategically deploying multiple charging pads, the initiative will demonstrate extended drone range and operational capabilities.
Aligned with Dubai’s vision for sustainable urban mobility and smart city initiatives, this innovation will foster autonomous recharging infrastructure, reduce human intervention, and enable transformative applications across commercial and emergency domains. The project will culminate in a functional prototype, along with patents and high-impact scientific publications, contributing significantly to the RDI ecosystem in Dubai.
Dr. Abigail Copiaco
Director of Computer Engineering and Assistant Professor, University of Dubai
“I am excited about this project because it has the potential to make a real difference in autism diagnosis and management. Using AI to improve early intervention and personalize support could be life-changing for individuals with autism and their families. It is truly rewarding to work on technology that bridges the gap between research and real-world impact.”
The prevalence of Autism Spectrum Disorder (ASD) has increased by 70% from 2000 to 2022, posing significant challenges in communication, behavior, and focus for affected individuals. Current diagnostic methods are effective but time-consuming, contributing to high social and economic costs. Moreover, these methods are primarily focused on initial diagnosis, making it difficult to track an individual’s progress over time and adapt interventions to their evolving needs.
This project introduces an AI-powered assistive technology aimed at streamlining ASD diagnosis and management, improving convenience for individuals and efficiency for caregivers and therapists. The system combines Artificial Intelligence techniques with three-dimensional and phenotypic data to accurately assess ASD levels, utilizing the Autism Diagnostic Observation Schedule (ADOS) as a reference. Delivered through a user-friendly mobile application, the technology supports home-based periodic assessments, reducing stress for both individuals and caregivers.
The system ensures updated insights into an individual’s development by enabling regular progress monitoring, allowing personalized recommendations tailored to their changing support requirements. It also facilitates seamless communication between guardians and therapists, fostering collaboration for better outcomes.
To improve performance, machine learning and deep learning models will be compared and fine-tuned using quantitative metrics and hyper-parameter optimization. This approach ensures precise, adaptive support, continuously monitoring intervention effectiveness and improving outcomes for individuals with ASD. As a collaborative effort between the University of Dubai, Al Amal Psychiatric Hospital, and renowned international research experts, the impact of this technology extends to the UAE and beyond, offering potential solutions to address the growing ASD diagnosis gap worldwide.
Dr. Hamzah Alkhazaleh
Associate Professor, University of Dubai
“As a researcher specializing in artificial intelligence and computational optimization, I am honored to lead the GAP-AD project, which introduces a pioneering approach to early Alzheimer’s detection through the integration of graphene-based biosensors, advanced deep learning models, and metaverse-enabled diagnostics. This project aligns with my commitment to leveraging AI for transformative healthcare solutions, addressing critical challenges in non-invasive, cost-effective, and scalable diagnostics. Through interdisciplinary collaboration and cutting-edge innovation, we aim to redefine early disease detection, enhance patient outcomes, and position Dubai as a global leader in next-generation medical technologies.”
The GAP-AD project, entitled “Early Alzheimer’s Detection Using Graphene-Based Biosensors, Deep Learning and Metaverse for Non-Invasive Diagnostics” aims to revolutionize the early detection of Alzheimer’s Disease (AD) by developing an innovative diagnostic solution that integrates graphene-based biosensors, deep learning, and metaverse technology.
The proposed Point-of-Care (PoC) device leverages the high sensitivity and conductivity of graphene to detect key AD biomarkers, such as amyloid-beta peptides and tau proteins, in non-invasive samples like blood and saliva. Complemented by advanced deep learning algorithms, the device enables precise biomarker analysis, disease onset prediction, and progression monitoring, significantly improving diagnostic accuracy. Additionally, the integration of a metaverse-based virtual platform provides an immersive environment for clinician-patient engagement, facilitating visualizations of disease progression and simulated treatment plans.
The project aligns with the Dubai RDI Grant Program’s strategic goals in the Health and Life Sciences sector, addressing critical global healthcare challenges through innovative and accessible diagnostic methods. It promotes Dubai’s vision of fostering cutting-edge medical technologies and becoming a global leader in healthcare innovation. By integrating cross-disciplinary expertise in artificial intelligence, biosensing, and virtual healthcare, the project directly contributes to advancing personalized medicine and scalable healthcare solutions.
Collaboration between institutions such as the University of Dubai, Al Amal Hospital for Mental Health, the University of Sharjah, Qatar University, and Macquarie University forms a robust multidisciplinary research network. Key deliverables include a graphene-based biosensor, deep learning models for biomarker analysis, an immersive metaverse platform, and validated clinical trials to pave the way for commercialization and training programs.
This project sets new benchmarks in non-invasive, cost-effective AD diagnostics, enhancing accessibility and patient care. It is poised to significantly impact Dubai’s research and development ecosystem, elevate its global reputation, and contribute to the advancement of Alzheimer’s detection and treatment on a worldwide scale.
Dr. Mohammed Alkhaldi
Assistant Professor, Canadian University Dubai
“I am honored to have received a prestigious grant from the Dubai Future Foundation, which enables me to leverage over 15 years of experience in global health research, policy, education, and practice to lead a multidisciplinary research project instituted at the Canadian University Dubai. With great excitement, I look forward to partnering with UAE health authorities and collaborating with two leading universities, McGill and Bonn, to implement this important project, which aims to conduct a comprehensive system analysis and digitize the Health Technology Assessment (HTA) system in the UAE. The project aligns directly with the UAE’s vision of becoming a global leader in healthcare innovation and with global health strategic direction on HTA which is an innovative approach to improve healthcare decision-making and ultimately enhance the quality of life for the population.”
Prof. Mai ElBarachi
Head of School of Computer Science, University of Wollongong in Dubai
“I am thrilled to lead the ChatEV project, an initiative that leverages cutting-edge AI to transform the electric vehicle ecosystem and drive Dubai’s vision for sustainable mobility. By integrating Generative AI, Large Language Models, and agentic AI in the EV ecosystem, we aim to enhance user experience, optimize energy efficiency, and support the UAE’s Net Zero 2050 strategy. This project represents an exciting step forward in AI-driven transportation, and I am eager to see its impact on smart transportation and urban resilience.”
The Dubai government proudly announces ChatEV, an innovative project funded by the Dubai Research, Development, and Innovation (RDI) Program, aimed at revolutionizing electric vehicle (EV) ecosystems. This groundbreaking initiative aligns with Dubai’s vision as a cognitive city and a global leader in research, innovation, and technology adoption.
ChatEV leverages cutting-edge generative AI, including Large Language Models (LLMs) such as LLAMA 3, Mistral, and Gemma, to deliver transformative chatbot-enabled solutions for three critical EV use cases: Advanced Driver Assistance Systems (ADAS), EV Charging Infrastructure Optimization, and Vehicle-to-Grid (V2G) Integration. The project enhances urban mobility through real-time updates on traffic, charging availability, and EV-friendly amenities, fostering seamless integration with smart infrastructure and boosting user trust in autonomous EV systems.
The societal and environmental impact of ChatEV is substantial. By offering 24/7 personalized support and tailored recommendations, the project elevates user satisfaction, making EV adoption more accessible and appealing. Its AI-powered frameworks optimize energy consumption and grid integration, directly contributing to the UAE’s Net Zero 2050 strategy and advancing sustainable practices that strengthen Dubai’s resilience as a smart city.
ChatEV’s global partnerships with leading institutions, including the University of Wollongong in Dubai, Sharjah University, Eurecom (France), and INRS (Canada), underscore Dubai’s commitment to fostering innovation and attracting top talent and investment. The project’s deliverables not only enhance EV ecosystems but also position Dubai as a leader in technology, ensuring its competitive edge on the world stage.
Through ChatEV, Dubai reaffirms its role as a trailblazer in sustainable urban development, offering a model of technological excellence that inspires global progress toward cleaner, smarter, and more connected cities.
Dr. Sreejith Balasubramanian
Associate Professor, Chair of the Office of Research, Head of Centre for Supply Chain Excellence, Middlesex University Dubai
“As the Principal Investigator, I’m excited and deeply honoured for the opportunity to contribute to Dubai’s bold and futuristic vision through this groundbreaking project. By harnessing AI and digital twin technology, we aim to empower SMEs with innovative, cost-effective solutions that enhance efficiency, sustainability, and technological advancement in manufacturing. A heartfelt thank you to the Dubai Research, Development, and Innovation (RDI) Initiative by the Dubai Future Foundation for supporting this transformative initiative to reshape the landscape of manufacturing, not just in Dubai, but across the globe.”
The global manufacturing sector faces persistent challenges, including fragmented data, inefficient resource allocation, and outdated processes, particularly for SMEs, which are constrained by limited resources and technical expertise. Empowering SMEs, which constitute 95% of businesses worldwide, to adopt cutting-edge technologies is critical for driving economic growth and job creation. Artificial Intelligence (AI)-enabled advancements in digital twin ecosystems, which are dynamic virtual representations of physical assets, present a transformative opportunity for SMEs. These advancements address challenges such as fragmented systems, heterogeneous data, limited technical expertise, and high costs, enabling SMEs to design, simulate, operate, and optimize intelligent production facilities.
This project aims to develop a cutting-edge cognitive digital twin ecosystem powered by AI and generative AI to transform Dubai’s manufacturing sector, a priority in Dubai’s Economic Agenda D33. By integrating platforms such as NVIDIA AI, Omniverse, and OpenUSD, the project seeks to democratize digital twin technology for resource-constrained SMEs. It enables them to create hyper intelligent and hyper-realistic digital twins at a fraction of the cost of conventional methods. This will empower manufacturing SMEs to explore multiple design iterations, identify potential issues, and optimize engineering solutions without costly physical prototyping, allowing them to scale and develop factories, enhance efficiency, and simulate scenarios that reduce costs and improve sustainability.
The project directly supports Dubai’s D33 Economic Agenda of strengthening its manufacturing sector while solidifying Dubai’s position as a global knowledge hub and a testbed for AI innovation. Project outputs, including demonstrable proof-of-concept (PoCs) in real-world settings, academic and industry publications, and capacity-building workshops, will advance research and practical applications in cognitive digital twins and the digital transformation of SMEs and the manufacturing sector. The insights and outcomes of this project are transferable and applicable across multiple industries beyond manufacturing, including logistics, cognitive cities, construction, real estate, and urban development.
Dr. Linda Smail
Professor, Zayed University
“Receiving the Dubai RDI Grant for our project on Advanced Bayesian Networks for Quranic Qira’at Classification is an incredible milestone. This support drives our mission to blend AI with cultural preservation, enhancing the study and analysis of Quranic recitations. Excited for what’s ahead!”
The project “Advanced Bayesian Networks for the Classification of Quranic Qira’at” aims to develop a cutting-edge Artificial Intelligence (AI) model to classify Quranic Qira’at, which are diverse and culturally significant recitation styles of the Quran. These recitations are central to Islamic tradition and culture and are characterized by intricate phonetic and linguistic nuances. Traditional methods of analyzing these styles often fall short in accuracy and efficiency. This project introduces an innovative solution by leveraging Bayesian Networks to identify the most critical features for classification, ensuring a balance between computational efficiency, interpretability, and precision.
This initiative represents a collaboration between Zayed University and the University of Sharjah, uniting their strengths in AI, Natural Language Processing, and Quranic studies. The project is uniquely positioned to address the complex challenges of classifying Quranic Qira’at by bringing together technical expertise and cultural insights. The outcomes will include a carefully annotated dataset of Quranic recitations, a high-performing AI model for classification, and a user-friendly application designed to support educators, scholars, and students in understanding and preserving these recitation styles.
More than just a technical achievement, this project aligns with Dubai’s Cognitive Cities initiative and the UAE’s broader vision for a sustainable, knowledge-driven future. By integrating cutting-edge AI into the study of Quranic recitations, the project aims to make a vital part of Islamic heritage more accessible to practitioners, learners, and researchers worldwide. This effort bridges the gap between tradition and technology, ensuring this rich cultural practice is preserved and adapted for future generations. The project’s outcomes will contribute to the UAE’s strategic goals of digital transformation, inclusivity, and building a sustainable, knowledge-based economy under the “We the UAE 2031” Agenda. This initiative sets a new benchmark for AI applications in cultural studies while preserving a vital aspect of Islamic heritage for future generations.
Prof. Nandu Goswami
Professor, Mohammed Bin Rashid University of Medicine and Health Sciences
“In this exciting project, an extensive search of biomarkers from astronauts in existing public health-related databases will be done using AI techniques. This AI project has the potential to create endless possibilities in implementing personalized medicine and new frontiers in human health.”
This project leverages an astronaut database to identify biomarkers predicting health risks during spaceflight and develop personalized medicine solutions for astronauts and terrestrial populations. Using artificial intelligence (AI) and multi-omics approaches, it aims to create an advanced genomics database and foster collaboration between engineers, data scientists, and healthcare professionals. The project will build a MedTech ecosystem connecting Dubai Health, Mohammed Bin Rashid University of Medicine and Health Science (MBRU) Centers (Space and Aviation Health, Applied and Translational Genomics, Innovation & Technology), UAE institutions (Mohammed Bin Rashid Space Center (MBRSC) and Dubai Health), and international collaborating partners (Canada, UK, Belgium, Austria, Norway, Germany).
The project deliverables include: 1. Enhanced Astronaut Health: Key biomarkers and pathways will be identified to predict and mitigate space-induced health risks, enabling tailored interventions such as personalized nutrition, exercise, or pharmaceuticals. 2. Innovative Personalized Medicine: Biomarkers may translate into therapies for age-related diseases, cancer, and immune disorders, advancing personalized healthcare. 3. Scientific Collaboration: A multi-omics astronaut database will provide researchers with resources for genomics, AI, and personalized medicine discoveries.
The innovative aspects of the project include: 1. Establishing Dubai’s first centralized astronaut biobank integrating genomics, transcriptomics, proteomics, and metabolomics. Historical and new UAE astronaut data will be structured for cross-referencing mission metadata and health outcomes. 2. AI-Driven Biomarker Identification: AI models will analyze multi-omics data to detect biomarkers of space-induced health risks. Earth-based datasets will validate these biomarkers for terrestrial applications. 3. Personalized Medicine Application: Risk profiles based on genomic responses will guide individualized interventions.
The potentials for impact include: 1. Discovery of novel biomarkers through SOMA data for understanding spaceflight effects, aging, and chronic illness 2. Networking and training opportunities for Emirati researchers in advanced -omics and AI technologies, enhancing UAE’s research capabilities.
Dr. Sabarinath Prasad
Assistant Professor, Mohammed Bin Rashid University of Medicine and Health Sciences
“As human beings, all of us have dreams. Most of us are able to articulate them; some work towards translating them into action, and a few are lucky enough to receive the necessary support and encouragement to realize those dreams. As clinicians and researchers, the support extended to us for the Data-driven Real-Time Evaluation and AI-powered Monitoring of Sleep (DREAMS) project will serve as the catalyst for transforming our DREAMS into products and services that ultimately advance health for humanity.”
A good night’s sleep is essential for health and well-being, yet millions struggle with sleep related issues. Sleep deprivation is not merely a personal health issue; it is also a systemic problem with societal implications. Industrialized nations with long work hours, 24/7 economies, and incessant digital distractions are the worst hit, as is Dubai.
In the Data-driven Real-time Evaluation and Artificial Intelligence (AI)-powered Monitoring of Sleep (DREAMS) project, we are developing an AI-powered wearable device that uses advanced technology and multiple sensors to do more than just track how long one sleeps. Unlike some current bulky and uncomfortable systems, the DREAMS device will be small, lightweight, and discreet, permitting users to sleep comfortably without being obtrusive.
With the DREAMS wearable device, sleep will be transformed from a passive, unexamined experience into an active, personalized health optimization journey. The AI-powered wearable device will provide detailed, easy-to-understand insights into sleep patterns and practical tips to help users sleep better. Focusing on seamless monitoring will empower users to understand their sleep patterns and share valuable information with healthcare professionals when needed.
Over time, as users continue using the device, it becomes smarter by learning the unique sleep habits of an individual, with the possibility of offering even better insights. It is like having a personal guide for healthier and more refreshing sleep every night. DREAMS will thus focus on ensuring good sleep and hopefully, more amazing dreams.
Dr. Obada Al Khatib
Assistant Professor, University of Wollongong in Dubai
“We are very enthusiastic and excited for this project that contributes to positioning Dubai at the forefront of sustainable smart city innovations and solutions. The proposed technology will be fundamental for the integration of AI-based energy harvesting and management into large-scale smart city networks to provide solutions for battery-free IoT sensor networks.”
This project addresses the urgent need for sustainable and efficient power solutions to support the expanding ecosystem of Internet of Things (IoT) devices in smart cities such as Dubai. By revolutionizing urban life, IoT devices are driving innovation and advancements across various domains, including traffic management, environmental monitoring, healthcare systems, and public safety. However, the reliance on battery-powered sensors poses significant challenges, including high maintenance costs, environmental harm, and frequent battery replacements, especially for devices in remote or hard-to-reach locations. To overcome these barriers, this project proposes an innovative rectenna system designed to harvests ambient Radio Frequency (RF) energy from sources such as Wi-Fi, mobile networks as well as dedicated wireless power transmissions. This proposed rectenna technology provides a sustainable and low maintenance solution to efficiently power IoT devices.
The main objective of this project is to develop scalable rectennas with multidirectional reception capability, ensuring efficient energy harvesting across multiple frequency bands regardless of RF source direction. This advanced technology is coupled with AI-driven Power Management Units (PMUs) to dynamically allocate, regulate, and optimize harvested energy, enabling uninterrupted operation of IoT sensor nodes without relying on conventional batteries. This is important as it reduces the dependence on traditional batteries, minimizes electronic waste, lowers maintenance costs, and enables sustainable IoT deployment, even in challenging environments. By facilitating these battery free sensor networks, it paves the way for a smarter, greener future in urban and industrial settings.
In addition to the development of the energy harvesting system, the project will produce a comprehensive RF power density dataset for Dubai and document its findings through detailed reports. These contributions will advance academic understanding and support the practical implementation of energy-efficient wireless power solutions. Aligning with sustainability goals, the project aims to reduce environmental impact while enhancing the efficiency and durability of IoT networks.
Dr. Anang Amin
Assistant Professor, Higher Colleges of Technology
“I am honoured to receive this prestigious grant from Dubai Future Foundation, supporting our research on AI-enabled digital-twin technology for solar-powered atmospheric water harvesting. This project presents an exciting opportunity to drive sustainable water solutions through innovation and advanced technology. I am eager to contribute to shaping a future where clean and reliable water is accessible to all.”
Dr. Nishtha Lamba
Associate Professor, Middlesex University Dubai
“The funding empowers our team to explore tech-mediated pathways to address trauma and promote healing. It has the potential to foster both individual and collective wellbeing. Honored to contribute to DFF’s vision to foster a healthier, more resilient world!”
This project proposes the development of an innovative Artificial Intelligence (AI) powered coach within Virtual Reality (VR) to deliver a first-of-its-kind, automated, and trauma-informed therapeutic interventions. Trauma-induced mental health issues are a significant global concern. Post Traumatic Stress Disorder (PTSD) becomes the root cause of several psychological and physiological illnesses. By 2030, mental health challenges are anticipated to cost the world economy 6 trillion dollars. Unresolved trauma leads to dysfunctionality with symptoms such as crippling anxiety, hopelessness, being on edge, emotional numbness, and disconnection from self. While there have been technological advancements in physical health, they have not trickled down to structured and holistic solutions for mental health.
Evidence-based prototypes will be developed within VR, where a virtual coach will facilitate trauma treatment. The AI-powered coach will be capable of natural speech interactions with the patient, and will deliver a customized treatment plan, based on established psychological principles. The treatments will include tackling symptoms of trauma (using VR-based mindfulness and meditation techniques) and also work towards rewiring trauma related memories that may have remained unprocessed for a long time. This will be implemented through an innovative embodied ‘time travel’ technique, where one will be able to virtually travel to the past or future, and compassionately interact with their younger or older selves (developed using cutting-edge avatar generation and deageing/ageing techniques) in VR to resolve their emotional wounds.
Experiences in VR lead to profound behavioral change in the real-world as well, leading to deeper emotional processing – factors essential for building mental health interventions. The project addresses gaps in trauma treatment by offering a radical and innovative solution, advancing Dubai’s vision of promoting wellbeing within the futuristic city. The project has the potential to transform how we view mental health treatments by increasing accessibility, automation, cost-effectiveness, and reducing overreliance on medications.
Dr. Shadi Atalla
Associate Professor and Director of the Computing & Information Systems Program, University of Dubai
“With extensive experience in AI, IoT, and digital transformation, I am excited to lead this innovative project integrating smart digital twin technology into high-rise building management. My research focuses on leveraging data-driven solutions to enhance efficiency, sustainability, and urban resilience, and this project provides a great opportunity to apply that expertise. Collaborating with a multidisciplinary team, I look forward to contributing to Dubai’s vision for a more intelligent and sustainable urban landscape.”
The SDT-HBM project, entitled “Smart Digital Twin Platform for High-Rise Building Management in Dubai”, aims to develop a groundbreaking Smart Digital Twin Platform (SDT-HBM) to revolutionize high-rise building management in Dubai. Leveraging artificial intelligence (AI), Internet of Things (IoT), and data-driven analytics, the platform will integrate real-time IoT data into a 3D Building Information Model (BIM) to enhance sustainability, operational efficiency, and resilience. The SDT-HBM aligns with the UAE’s Net Zero 2050 Strategy by optimizing energy usage, reducing carbon footprints, and improving building performance. Key innovations include AI-driven predictive maintenance, blockchain-secured data integrity, and an interactive dashboard using AR/VR for advanced decision-making. The platform’s scalability across Dubai’s high-rise ecosystem supports city-wide communication, positioning it as a cornerstone of Dubai’s cognitive smart city vision.
The project is directly aligned with the Dubai RDI Grant Program, addressing priorities in Smart Built Infrastructure and Cognitive Cities. It introduces transformative solutions to Dubai’s unique urban challenges, integrating AI, IoT, and BIM to achieve sustainable urban development. Designed to foster interdisciplinary collaboration, the project brings together experts from the University of Dubai, the University of Sharjah, Qatar University, and Macquarie University, ensuring a comprehensive and innovative approach to urban management challenges.
Deliverables include a scalable Smart Digital Twin platform, AI-driven methods for real-time data integration, a pilot digital twin model of the 23 Marina Tower, and secure, energy-efficient AI models for building management. The findings will be disseminated through academic publications and industry workshops, fostering global impact.
This project establishes Dubai as a global leader in smart city technologies, creating scalable and globally relevant solutions for high-rise management. It significantly advances sustainability, energy optimization, and resident satisfaction while driving economic growth and innovation. By addressing the UAE’s Net Zero 2050 goals, the SDT-HBM sets a benchmark for future urban digital twin platforms worldwide.
Dr. Zeenath Reza Khan
Associate Professor, University of Wollongong in Dubai
“The Yathiqu Project is an exciting opportunity to foster global collaboration on AI ethics, bringing together experts from six countries, including the UAE, alongside Dubai-based startups, to explore trust (Yathiqu/يثق) in AI. I am pleased to lead this project where we will develop a custom governance sandbox within a metaverse platform, alongside a MOOC and chatbot to enhance AI literacy in healthcare. With the support of the Dubai Future Foundation, this project aims to advance ethical AI practices and further strengthen Dubai’s leadership in AI governance and innovation.”
The project, “Using AI Simulation for Building Trust (Yathiqu يثق ) in AI and AI Literacy”, aims to develop a method to help the AI ecosystem (developers, managers, users, policymakers and the third sector) to verify and build trustworthy AI relating to healthcare industry. The World Health Organization (WHO) has predicted a shortage of healthcare workers by 2030; hence there is a rapid deployment of AI solutions to help alleviate the strain on healthcare systems. The multifaceted evolving challenges with the adoption and governance trustworthy AI, such as trust, data quality, and regulatory alignment, highlight the fragmentation in definitions, varying needs of stakeholders, and inconsistencies across the AI lifecycle stages.
The project, Yathiqu, will review published research on AI (within the UAE and globally) and use focus groups across countries and healthcare stakeholders to develop a framework for trustworthy AI by identifying key factors at each stage of AI development. The unique methodology includes conducting experiments in a custom-built metaverse simulation as a governance sandbox with a custom-for-purpose large language model (LLM). Our project will contribute to the need for greater AI literacy by developing a MOOC on AI ethics in healthcare, policy briefs and academic articles. Through partnerships across six countries – UAE, UK, USA, Türkiye, Czechia, and Australia, with academia, public institutions, nonprofit organisations and startups, the initiative contributes to the UAE’s focus on trustworthy AI and health (e.g. National Strategy for Artificial Intelligence 2031, UAE Centennial 2071). Further, these objectives align with the AI literacy obligation highlighted by the EU AI Act, especially as AI in the healthcare industry is expected to reach $490.96 billion by 2032, with a CAGR of 43.2%. The project will support AI firms by adding to their knowledge that will support the UAE AI Seal brand (UAI).
Dr. Ruchit Agrawal
Assistant Professor and Head of CS Outreach, University of Birmingham Dubai
“Dubai’s dynamic and futuristic cross-sectoral vision is what pulled me here from Oxford in 2022. As an Assistant Professor of Computer Science at the University of Birmingham Dubai, I am very excited about building research solutions to problems pertinent to the region. My project, titled KAMAL Health (Knowledge Augmented Multi-Modal Arabic LLMs for Healthcare), is an endeavour towards Arabic AI technologies for the healthcare sector, and I look forward to developing innovative solutions to improve patient outcomes and foster the integration of AI-powered platforms with healthcare systems within the UAE and beyond.”
The proposed project aims to develop “KAMAL Health” (Knowledge-Augmented Muli-Modal Arabic LLMs for Healthcare), an advanced bilingual, multi-modal medical platform designed in alignment with the local needs of the United Arab Emirates, supporting Arabic as well as English. In addition to text-based chat, KAMAL Health will also support voice-mode with enhanced accessibility to the diverse diaspora of the UAE, making healthcare more accessible and personalized.
KAMAL Health will integrate neuro-symbolic AI approaches, combining the capabilities of large language models (LLMs) with classical machine learning methods, ensuring high-quality, transparent, and interpretable medical recommendations. The current landscape of healthcare AI models lacks robust solutions for multi-modal personalized medical recommendations and speech-based health diagnostics and are primarily focused on English. KAMAL Health directly addresses this gap by creating specialized, innovative models that combine deep learning techniques with medical domain expertise to create a platform that provides context-aware healthcare consultations and provides information about local doctors and hospitals when appropriate. Additionally, KAMAL Health introduces voice-mode, i.e. the ability to interact with the user in Arabic via verbal communication, in addition to textual communication, which is not readily available in current platforms.
The inclusion of both English and Arabic makes this platform a unique solution for Dubai’s highly diverse population, promoting inclusivity and improving public health for residents across linguistic divides. The project will serve as a key enabler of AI-driven healthcare innovation, improving accessibility to medical services, and reducing the strain on healthcare providers as well as easing mental anxiety of patients with relatively benign ailments. It will also create new opportunities for further research in AI healthcare technologies and have a cross-sectoral impact on related clinical applications. Additionally, KAMAL Health brings a strong potential for commercialization of the bilingual models and sets a precedent for the integration of AI in public health systems.
Dr. Khalil Al Hussaeni
Assistant Professor, Rochester Institute of Technology
“With extensive international experience in cybersecurity, our team are very excited to contribute to the enhancement and protection of Dubai’s digital infrastructure.”
Dr. Abdellatif Qamhaieh
Associate Professor, American University in Dubai
“We are extremely humbled to receive this grant and incredibly thankful to the DFF team and the Government of Dubai for this important program. By empowering Dubai-based scholars, the grant helps boost research and highlights confidence in the role of local academic institutions as hubs for knowledge production. It is truly a privilege to be part of such an important initiative.”
Urban livability has re-emerged as a high-priority item for policymakers and city planning departments worldwide. In the wake of the COVID-19 pandemic, the ongoing climate crises, and the fierce global competition between cities aiming to attract businesses and tourism, enhancing urban livability has become a matter of great importance. Yet, while livability has increased in its significance, it remains challenging to define and operationalize as it involves several subjective components and is, therefore, somewhat elusive as a concept. Also, due to the various factors impacting urban livability, it is particularly challenging to conceptualize at the neighborhood level – where it is felt the most.
Considering these complexities, this project aims to develop an innovative approach for evaluating and delivering Urban Livability (UL) in Dubai. By leveraging Geographic Information Systems (GIS) and Artificial Intelligence (AI), the project aims to create an ‘intelligent’ online urban livability dashboard. The project will help define Dubai-specific livability metrics, and the proposed dashboard will assist policymakers in visualizing urban livability conditions in various neighborhoods across the city. The dashboard should help determine priority intervention areas, explore and visualize ‘what-if’ scenarios, and assess proposed solutions. It also enables better collaboration between stakeholders across various disciplines due to its built-in Ai-assistant, which will help bridge knowledge gaps.
The project addresses the difficulties of measuring urban livability indicators in a rapidly growing city like Dubai with its unique urban growth and socio-spatial patterns. Beyond the applied benefits, it will contribute to the academic discourses surrounding GCC urbanism and AI applications in city planning. It will also bolster Dubai’s already impressive reputation as a smart city and hub for global innovation.
Dr. Wael Bazzi
Dean of the School of Engineering and Professor, American University in Dubai
“By combining the power of human intuition with AI-driven analytics, we aim to create intelligent systems that are adaptive, efficient, and ethically aligned with real-world challenges. The Hybrid Human-AI Intelligence project marks a pivotal step toward seamless collaboration between humans and machines, driving innovation across industries and disciplines.”
The “SMART: Augmented Hybrid Intelligence” project pioneers a novel framework that integrates human intelligence with artificial intelligence (AI) to create a groundbreaking paradigm for trustworthy human-AI synergy. This project introduces Hybrid Intelligence (HI), surpassing the capabilities of either human or AI systems independently, by facilitating seamless cooperation and explainable interactions.
SMART’s core innovation is the development of Augmented Hybrid Intelligence (AHI), which combines reliable collective human intelligence, pervasive AI-driven federated learning, cognitive graph-based explainable inference models, and a unified ethical framework. This robust approach addresses critical challenges, including acquiring reliable human intelligence, ensuring AI accuracy under dynamic conditions, and fostering human-AI collaboration that adheres to ethical principles.
A key application of SMART is in the development of a next-generation Clinical Lab Automation (CLA) system. The AHI-enabled CLA system enhances diagnostic accuracy, streamlines workflows, and optimizes treatment decisions in healthcare by integrating domain-specific human expertise with advanced AI algorithms. This system enables real-time process optimization, reduces errors, and delivers rapid, cost- effective diagnostic solutions.
The project is organized into interlinked research objectives, including innovative approaches for acquiring reliable human intelligence, developing adaptive federated learning frameworks, designing explainable reasoning models, and embedding ethics into all phases of development. These advancements are supported by real-world testing and validation in healthcare environments, ensuring practical applicability.
SMART represents a multidisciplinary effort, uniting expertise in computer science, cognitive science, ethics, and healthcare. By addressing technical, ethical, and societal challenges, SMART aims to redefine how human-AI collaboration is realized, offering transformative benefits across mission-critical applications such as medical diagnostics, disaster response, and energy efficiency. This project is poised to significantly advance the state-of-the-art in trustworthy AI systems.
Dr. Claudio Zito
Assistant Professor, Heriot-Watt University Dubai
“The CogWaters project, funded by the Dubai RDI program, is led by Heriot-Watt University Dubai in collaboration with the Edinburgh campus and the UK National Robotarium. This initiative represents a transformative opportunity to integrate cutting-edge AI and robotics into urban decision-making, bridging academic excellence to drive innovation and address real-world challenges in the field. Our team is incredibly excited about this project, as it aligns with Dubai’s vision for innovation and sustainability while promising to make a meaningful impact on the community.”
The CogWaters project, led by Heriot-Watt University’s Dr. Claudio Zito with co-investigators Dr. Radu Mihailescu, Dr. Adrian Turcanu, and Prof. Yvan Petillot, is set to revolutionise debris collection in Dubai’s urban waterways through the development of an advanced cognitive architecture for Unmanned Surface Vehicles (USVs). The lead institution for this initiative is Heriot-Watt University Dubai, in collaboration with Heriot-Watt University Edinburgh and the UK National Robotarium. This project will enable significant advancements in autonomous systems capable of navigating complex environments.
CogWaters addresses pressing urban challenges by enhancing decision-making and situational awareness through the integration of a Semantic World Model and state-of-the-art machine learning and reinforcement learning techniques.
The project will also fund Heriot-Watt University’s Centre for Doctoral Training (CDT) in AI and Robotics, which will train new professionals in the field of intelligent robotics to support Dubai’s growing specialized workforce.
Key deliverables include a comprehensive OWL-based ontology for semantic interoperability, an advanced perception system, and a fully functional USV prototype. The impact of CogWaters extends beyond robotics – promoting sustainable urban initiatives, enhancing local talent, and stimulating innovation within Dubai’s RDI ecosystem. Through public outreach and community engagement, CogWaters aims to raise awareness and foster support for technological advancements in environmental management, ultimately contributing to Dubai’s vision of becoming a global hub for innovation and sustainability.
Dr. Haythem El-Messiry
Program Director Master of AI and Associate Professor, Canadian University Dubai
“Dr. Haythem El-Messiry serves as the Program Director for the Master of Science in Artificial Intelligence at Canadian University Dubai. His dynamic research is highlighted by many publications in prestigious international journals and conferences focused on computer vision. Dr. El-Messiry also significantly impacts the industry by overseeing various influential grant projects involving intelligent system solutions, DNA profiling systems, and biomedical applications.”
Volume Electron Microscopy (VEM) is at the forefront of 3D structural analysis of biological cells and tissues, essential for understanding the complexities of life. Evolved from traditional 2D microscopy, VEM offers high resolution imaging at nanometer scales, capable of detailing 3D cellular structures and tissues. Recognized by Nature as a leading technology to watch in 2023, VEM utilizes ultra-high-resolution scanning and transmission electron microscopy. It provides continuous nanoscale imaging of biological tissues, bridging the gap between cellular and tissue biology. This positions VEM as a crucial tool in health and life sciences, aiding in disease mechanism understanding, drug discovery, and developmental biology by offering high-resolution 3D reconstructions.
VEM reconstructs isotropic 3D structures through continuous slicing and 2D image stitching, allowing for detailed views of cell bodies and organelles. However, challenges remain in image stitching, alignment, anisotropy correction, and automated segmentation, which are crucial for processing large and complex datasets. To overcome these, the project aims to harness advanced AI techniques, enhancing VEM data accuracy by reducing noise and improving resolution. The development focuses on high-precision image stitching frameworks to manage global and local image transformations and improve 3D alignment using deep learning to repair slice damage. Additionally, self-supervised algorithms for 3D reconstruction, alongside large pre-trained models for segmentation, are targeted to enhance generalization and efficiency, tackling the limitations of traditional methods. These advancements intend to break down current barriers in VEM technology, enriching our understanding of intricate biological systems. The initiative will bolster Dubai’s research and innovation ecosystem by democratizing access to advanced imaging tools, reinforcing its status as a global leader in health and life sciences, and fostering local expertise and innovation in these cutting-edge fields.
Dr. Abhilasha Singh
Professor, American University in the Emirates
This project focuses on developing and integrating a decentralized waste segregation technology tailored for high-rise buildings with chute-based disposal systems. By combining an AI-driven material classification tool with a patented waste segregation system, the solution achieves near- 100% accuracy in recycling at the source. The system incorporates personalized incentives to enhance community participation, addressing key challenges such as contamination and high logistics costs associated with conventional waste management. Leveraging advanced robotics and AI, the project aims to support a financially viable circular economy while minimizing environmental impact.
Aligned with the goals of Dubai’s Future Foundation’s RDI Grant Program, the project enhances urban sustainability through data-driven technologies and social engagement. By integrating adaptable hardware into existing residential infrastructures, it aligns with smart city initiatives to improve recycling rates and reduce pollution, with broader public health benefits. The project emphasizes sustainable waste management in high-density urban environments, optimizing resources and reducing environmental footprints.
The interdisciplinary collaboration includes American University in the Emirates (AUIE), Khalifa University (KU), and Cycled Technologies Middle East, supported by partnerships with Dubai Municipalities and real estate developers like Dubai Holding. This team ensures a comprehensive approach to designing, implementing, and scaling the technology.
Key deliverables include: (1) a smart waste segregation system integrated into high-rise building infrastructures, (2) a personalized recycling incentive platform, (3) pilot implementations in Dubai, (4) data-driven insights on user engagement and recycling incentives, and (5) technical and commercial case studies for policy and commercialization support.
This innovative approach integrates decentralized segregation and AI-powered incentives, offering a scalable and efficient alternative to traditional centralized systems. Its successful implementation could help achieve Dubai’s 90% waste diversion goal by 2030 and provide a replicable model for sustainable waste management globally.
Dr. Mohammad Alsmairat
Associate Professor, American University in the Emirates
Generative models, such as large language and vision-language models, are widely used but often biased toward English culture due to the dominance of English texts in pretraining data. This bias challenges their deployment in Arabic-speaking countries, where cultural alignment is essential for education, media, and public services. Recent evaluations of Arabic-centric models, such as JAIS, highlight these issues. Despite being trained on extensive Arabic corpora, these models can produce outputs that conflict with cultural norms. For instance, JAIS generated the text, “بعد صلاة المغرب سأذهب مع الأصدقاء لنشرب” (“After Maghrib prayer, I’m going with friends to drink …”), which contradicts Arab cultural and religious values. Such examples emphasize the broader problem of cultural misalignment in generative models and the need for efforts to identify and mitigate these biases, ensuring their responsible use in diverse cultural settings.
To address these challenges, we propose the development of safe and culturally-aware language models that align with the diverse cultures and norms of Arabic-speaking countries, including the UAE/Dubai and other regions. Our work spans both Modern Standard Arabic (MSA) and regional Arabic dialects to ensure comprehensive linguistic and cultural representation. Instead of building a new LLM from scratch, this project focuses on (1) evaluating existing Arabic-centric models using a detailed taxonomy to capture the nuances of local contexts and (2) adapting these models to better reflect Arabic culture and values. To comprehensively represent Arabic cultures, the project will deliver three main datasets: (1) an Arabic Cultural Knowledge Graph integrating multimodal and multilingual data to enhance cultural understanding, (2) a regionally diverse Arabic-specific instruction dataset, and (3) a safety dataset tailored to Arabic cultural and religious values. This strategy ensures cultural alignment while minimizing costs and improving the utility of existing models.