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Robotics and autonomous systems research from the Gulf region, including work from MBZUAI, Khalifa University, and TII on robot learning and embodied AI.
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A proposed recognition system aims to identify missing persons, deceased individuals, and lost objects during the Hajj and Umrah pilgrimages in Saudi Arabia. The system intends to leverage facial recognition and object identification to manage the large crowds expected in the coming decade, estimated to reach 20 million pilgrims. It will be integrated into the CrowdSensing system for crowd estimation, management, and safety.
Researchers created a cross-cultural corpus of annotated verbal and nonverbal behaviors in receptionist interactions. The corpus includes native speakers of American English and Arabic role-playing scenarios at university reception desks in Doha, Qatar, and Pittsburgh, USA. The manually annotated nonverbal behaviors include gaze direction, hand gestures, torso positions, and facial expressions. Why it matters: This resource can be valuable for the human-robot interaction community, especially for building culturally aware AI systems.
Khalifa University · · Research Education
Khalifa University has announced the accreditation of new PhD programs across various disciplines within its College of Computing and Mathematical Sciences and College of Engineering and Physical Sciences. These programs include Computer & Information Engineering, Computer Science, Robotics, Mathematics, Materials Science & Engineering, Mechanical Engineering, Nuclear Engineering, Petroleum Engineering, and Physics. The university aims to provide an environment where researchers can transform ideas into innovative technological solutions with real-world impact. Why it matters: The expansion of advanced graduate programs at a leading UAE institution strengthens the region's research capabilities and talent pipeline in critical scientific and engineering fields.
Khalifa University · · Research Robotics
Khalifa University has announced the accreditation of several new PhD programs within its colleges. These include programs in Computer & Information Engineering, Computer Science, Robotics, and Mathematics, offered by the College of Computing and Mathematical Sciences. The College of Engineering and Physical Sciences also launched new PhDs in Materials Science & Engineering, Mechanical Engineering, Nuclear Engineering, Petroleum Engineering, and Physics. Why it matters: This expansion of advanced academic offerings strengthens the UAE's research capabilities and talent pipeline in critical scientific and engineering fields, including AI-relevant areas like computer science and robotics.
Khalifa University · · Research Robotics
Khalifa University has announced the accreditation of new PhD programs, including Computer & Information Engineering, Computer Science, Robotics, and Mathematics. These advanced programs are designed to provide researchers with an ideal environment to transform ideas into innovative technological solutions with real-world impact. Dr. Sami Muhaidat, Acting Dean of the College of Computing and Mathematical Sciences, highlighted these new offerings. Why it matters: Expanding doctoral programs in key technological fields like AI and Robotics signals a commitment to developing local research talent and contributing to the UAE's knowledge economy.
An MBZUAI team led by Ph.D. student Dmitry Demidov won the Best Student Paper Award at VISAPP 2023 for their work on fine-grained visual classification. Their paper, 'Salient Mask-Guided Vision Transformer for Fine-Grained Classification,' introduces SM-ViT, a technique using a salient mask to improve Vision Transformer accuracy. The model focuses on defining characteristics of objects, outperforming standard ViT architecture, even with fewer or lower-resolution images. Why it matters: This award recognizes MBZUAI's contribution to advancing computer vision, particularly in applications requiring nuanced object recognition, such as robotics and automated systems.
MBZUAI researchers presented "TransRadar," a study at WACV proposing new uses for radar in object identification. The study, led by Yahia Dalbah, explores fusing radar with other technologies to identify objects, particularly for autonomous vehicles. The "TransRadar" approach uses an adaptive-directional transformer for real-time multi-view radar semantic segmentation. Why it matters: This research addresses the limitations of radar by enhancing its object recognition capabilities, potentially improving the reliability of autonomous systems in adverse conditions.
MBZUAI · · AI Healthcare
MBZUAI will present two assistive AI prototypes at GITEX 2025: smart glasses with a camera and eye tracker that identify objects and medication, and a brain-computer interface (BCI) device integrated with robotics to control a robotic dog's movements. The smart glasses use a multimodal large language model (LLM) to help visually impaired individuals, while the BCI aims to restore hands-free communication for people with mobility limitations. Hisham Cholakkal leads the research team, which received a Meta Regional Research Grant 2025 for its work on multimodal LLM for smart wearables. Why it matters: The research demonstrates the potential of AI to improve the quality of life for vulnerable populations and addresses the challenge of providing cost-effective care for aging societies.
MBZUAI · · Robotics Healthcare
Professor Cesare Stefanini of MBZUAI discusses his journey from Pisa to global prominence in robotics. He credits his time at Scuola Superiore Sant’Anna and mentorship from Paolo Dario for shaping his career. Stefanini won an international robotics competition in Japan, which inspired him to pursue a Ph.D. and further research. Why it matters: This highlights MBZUAI's commitment to attracting top international talent in robotics and fostering innovation in healthcare technology.
MBZUAI · · Healthcare Robotics
The inaugural Abu Dhabi AI-Robotics Conference was held at MBZUAI, focusing on AI-powered robotics to transform healthcare. Experts explored applications in microsurgery, biorobotics, and personalized treatment, with keynotes from H.E. Abdulla Abdulalee AlHumaidan, Timothy Baldwin, and Sami Haddadin. Dr. Hassa Al Mazrouei highlighted the potential for personalized care and automation driven by AI. Why it matters: The conference underscores the UAE's commitment to advancing AI and robotics in healthcare, potentially positioning the region as a leader in innovative medical technologies.
MBZUAI will showcase AI applications for energy transformation at ADIPEC 2025 in Abu Dhabi, highlighting technologies for safety, efficiency, and competitiveness. Demonstrations will include intelligent cooling, autonomous inspection robotics, and AI-powered decision support. Sami Haddadin emphasizes AI's role as critical infrastructure, while Ramzi Ben Ouaghren notes its role in enabling a sustainable energy future. Why it matters: This participation underscores the UAE's commitment to leveraging AI for global impact in the energy sector, promoting innovation and technology transfer.
MBZUAI researchers have developed a new action tokenization method called LipVQ-VAE to improve in-context robot learning. LipVQ-VAE combines VQ-VAE with a Lipschitz constraint to generate smoother robotic motions, addressing limitations of traditional methods. The technique was tested on simulated and real robots, showing improved performance in imitation learning. Why it matters: This research advances robot learning by enabling more fluid and successful robot actions through improved action representation, drawing inspiration from NLP techniques.
MBZUAI researchers have developed a "divide-and-conquer" technique to improve learning from demonstration in robotics. The approach breaks down complex dynamical systems into independently solvable subsystems, modeled as linear parameter-varying systems. This method aims to simplify computations while maintaining stability and accurately capturing joint interactions for robots in complex environments. Why it matters: The research addresses a key challenge in robotics, potentially enabling more efficient and safer robot learning from human demonstrations.
MBZUAI's Ke Wu is developing bio-inspired robots, including a transmedia drone modeled after the diving beetle that can move in both air and water. The design will be presented at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2025) in Hangzhou, China. The research explores how principles from nature and evolution can inform robot design, control, and learning, integrating AI with embodied intelligence. Why it matters: This work contributes to the rapidly evolving field of soft robotics and offers new insights for developing more adaptive, biologically grounded intelligent systems in the region and globally.
MBZUAI · · AI Education MBZUAI
The International Olympiad in AI (IOAI), a competition for high school students in NLP, CV, and robotics, will be hosted in Abu Dhabi by MBZUAI in 2026. MBZUAI faculty members Yova Kementchedjhieva and Maxim Panov are part of IOAI's International Scientific Committee and helped bring the event to the UAE. The IOAI 2025 in Beijing included individual contests, team challenges, and the GAITE program, testing participants with AI tasks and generalization challenges. Why it matters: Hosting IOAI in Abu Dhabi highlights the UAE's commitment to fostering AI talent and positions MBZUAI as a key player in global AI education.
MBZUAI researchers developed AnomalyGen, a framework using foundation models to help household robots anticipate and react to dangerous scenarios. The system uses collaborative agents to brainstorm hazards, recreates scenarios in a 3D simulation, and develops mitigation methods. AnomalyGen will be presented at the upcoming NAACL conference. Why it matters: This research advances the development of trustworthy AI for real-world applications, specifically enabling robots to proactively ensure safety in home environments.
MBZUAI will participate as an official partner at Machines Can See 2025 (MCS 2025) during Dubai AI Week, showcasing AI innovation with expert speakers and live demos. MBZUAI will present BiMediX2, a multimodal virtual assistant that answers medical questions in Arabic and English and won Meta’s Llama Impact Innovation Award. They will also demonstrate Voodoo XP, a one-shot face re-enactment tool, and LAIKA, an AI-powered robot dog. Why it matters: This event highlights MBZUAI's contributions to AI and robotics, strengthening the UAE's position as a leader in science and technology, especially in healthcare and advanced robotics.
Gregory Chirikjian presented an overview talk on applying probability, harmonic analysis, and geometry to robotics, emphasizing the need for robots to function beyond traditional industrial programming. He discussed a new approach where robots define affordances of objects, using simulation to 'imagine' object use and enabling reasoning about novel objects. Probabilistic methods on Lie-groups, initially developed for mobile robot state estimation, are now adapted for one-shot learning of affordances, with plans to integrate large language models. Why it matters: This research direction aims to enhance robot intelligence and adaptability, crucial for service robots in dynamic environments and aligning with broader goals of advanced AI integration in robotics.
Yoshihiko Nakamura from the University of Tokyo discusses the computational challenges of humanoid robots, extending beyond sensing and control to understanding human movement, sensation, and relationships. The talk covers recent research on mechanical humanoid robots with a focus on actuators and computational problems related to human movements. Nakamura highlights the need for humanoid robots to interpret human actions and interactions for effective application. Why it matters: Addressing these computational challenges is crucial for developing more sophisticated and human-compatible robots for use in various human-centered applications within the region and globally.
This article discusses a talk by Houda Elmimouni on designing technology with user values in mind, using privacy and robotic telepresence research as examples. The first study examines privacy practices, while the second focuses on values in robotic telepresence in classrooms. Elmimouni highlights the importance of aligning technology design with social values like privacy. Why it matters: The emphasis on user-centered design and social values provides insights applicable to AI development in the Middle East, where cultural context and ethical considerations are paramount.
Cyrill Stachniss from the University of Bonn presented recent work on agricultural robotics and self-driving cars. The talk covered autonomous field robots and their ability to perceive, model, and predict future developments in complex farming environments. The presentation also included developments in supervised and unsupervised learning for autonomous car perception systems. Why it matters: This highlights the growing interest in robotics research at MBZUAI and the potential for AI to transform key sectors in the GCC region like agriculture and transportation.
Dr. Xiaoming Liu from Michigan State University discussed computer vision techniques for 3D world understanding at a talk hosted by MBZUAI. The talk covered 3D reconstruction, detection, depth estimation, and velocity estimation, with applications in biometrics and autonomous driving. Dr. Liu also touched on anti-spoofing and fair face recognition research at MSU's Computer Vision Lab. Why it matters: Showcasing international experts and research directions helps to catalyze computer vision and 3D understanding research efforts within the UAE's AI ecosystem.
Jingjin Yu from Rutgers University presented research on multi-robot coordination and robotic manipulation at MBZUAI. The talk covered Rubik Table algorithms for collision-free path planning for multiple robots in dense settings. It also discussed algorithms for long-horizon manipulation tasks like rearrangement and object retrieval. Why it matters: Advancements in multi-robot coordination and manipulation are crucial for deploying robots in various sectors within the UAE and beyond, such as logistics and elder care.
A presentation discusses the evolution of Vision-and-Language Navigation (VLN) from benchmarks like Room-to-Room (R2R). It highlights the role of Large Language Models (LLMs) such as GPT-4 in enabling more natural human-machine interactions. The presentation showcases work using LLMs to decode navigational instructions and improve robotic navigation. Why it matters: This research demonstrates the potential of merging vision, language, and robotics for advanced AI applications in navigation and human-computer interaction.
This article discusses the reliability of Deep Neural Networks (DNNs) and their hardware platforms, especially regarding soft errors caused by cosmic rays. It highlights that while DNNs are robust against bit flips, errors can still lead to miscalculations in AI accelerators. The talk, led by Prof. Masanori Hashimoto from Kyoto University, will cover identifying vulnerabilities in neural networks and reliability exploration of AI accelerators for edge computing. Why it matters: As DNNs are deployed in safety-critical applications in the region, ensuring the reliability of AI hardware is crucial for safe and trustworthy operation.
MBZUAI · · Robotics Healthcare
Researchers have developed robotic path-planning and control algorithms for minimally invasive surgery (MIS) that steer flexible needles, incorporating teleoperation and haptic feedback. An AI algorithm was designed to predict target motion due to respiratory movement, improving needle placement accuracy. GANs were used to generate synthetic images visualizing organ and tumor motion. Why it matters: This research demonstrates the potential of AI and robotics to enhance precision and adaptability in MIS, potentially reducing patient trauma and improving recovery times in the region and beyond.
Maha Elgarf from NYU Abu Dhabi presented research on using social robots to stimulate creativity in children through subconscious mimicry, leveraging the 'chameleon effect'. The research involved a series of studies where children engaged in storytelling with a social robot, and their creativity was assessed. Elgarf also discussed using Large Language Models (LLMs) in education and challenges in the field. Why it matters: This explores innovative applications of social robotics and AI in education within the UAE, potentially enhancing children's learning and creativity.
Marc Pollefeys from ETH Zurich and Microsoft Spatial AI Lab will discuss building 3D environment representations for assisting humans and robots. The talk covers visual 3D mapping, localization, spatial data access, and navigation using geometry and learning-based methods. It also explores building rich 3D semantic representations for scene interaction via open vocabulary queries leveraging foundation models. Why it matters: Advancements in spatial AI and 3D scene understanding are critical for enabling more capable robots and AI assistants in various applications within the region.
Gregory Chirikjian presented an overview of research on robot navigation in unstructured environments, using computer vision, sensor tech, ML, and motion planning. The methods use multi-modal observations from RGB cameras, 3D LiDAR, and robot odometry for scene perception, along with deep RL for planning. These methods have been integrated with wheeled, home, and legged robots and tested in crowded indoor scenes, home environments, and dense outdoor terrains. Why it matters: This research pushes the boundaries of robotics in complex environments, paving the way for more versatile and autonomous robots in the Middle East.
Michael Yu Wang, Chair Professor and Founding Dean of the School of Engineering at Great Bay University, argues for combining "good old fashioned engineering" (GOFE) with learning-based approaches like LLMs for robot skill acquisition, particularly in manipulation. He suggests a modular framework that integrates engineering principles with learning, drawing inspiration from human hand-eye coordination and tactile perception. Wang emphasizes the need to address engineering features of robot tactile sensors, such as spatial and temporal resolutions, to achieve human-like robot manipulation skills. Why it matters: This perspective highlights the importance of hybrid approaches combining traditional engineering with modern AI for advancing robotics, especially in complex manipulation tasks relevant to industries in the GCC region.
Professor Cesare Stefanini will discuss the relationship between AI and natural systems, highlighting robotics inspired by nature. His talk will cover neuro-inspired robot control, bio-hybrid ecosystems, and advancements in biomedical and industrial robotics. Stefanini will share achievements in underwater robot locomotion, AI-powered biomedical systems, and industrial platforms enhancing human manipulation. Why it matters: The talk at Khalifa University reflects the UAE's interest in bio-robotics research and integrating AI into various sectors, potentially fostering collaborations and advancements in the field.
Eliseo Ferrante from NYU Abu Dhabi presented work on increasing the controllability of swarm robotics systems. The research covers microscopic control via implicit intelligent leaders and macroscopic control via automated generation of swarm behaviors. Grammatical evolution and generative AI methods are used to produce collective behaviors aligned with human specifications. Why it matters: This research enhances the applicability of swarm robotics in real-world scenarios by improving control and coordination, potentially impacting industries like logistics, environmental monitoring, and disaster response in the region.
Tetsunari Inamura's talk explores using VR to collect HRI data and tailor assistive robotic functionalities to individual users. He discusses symbol emergence via multimodal interaction, interactive behavior generation through symbol manipulation, and VR for data collection. The talk emphasizes long-term human capability enhancement and avoiding over-reliance on technology. Why it matters: This research promotes independence and growth in human-robot interactions, potentially revolutionizing assistive technologies in the region.
Song Chaoyang from the Southern University of Science and Technology (SUSTech) presented research on Vision-Based Tactile Sensing (VBTS) for robot learning, combining soft robotic design with learning algorithms to achieve state-of-the-art performance in tactile perception. Their VBTS solution demonstrates robustness up to 1 million test cycles and enables multi-modal outputs from a single, vision-based input, facilitating applications such as amphibious tactile grasping and industrial welding. The talk also highlighted the DeepClaw system for capturing human demonstration actions, aiming for a universal interaction interface. Why it matters: This research advances embodied intelligence by improving robot dexterity and adaptability through enhanced tactile sensing, which is crucial for complex manipulation tasks in various sectors such as manufacturing and healthcare within the region.
Mykel Kochenderfer from Stanford University gave a talk on building robust decision-making systems for autonomous systems, highlighting the challenges of balancing safety and efficiency in uncertain environments. The talk addressed computational tractability and establishing trust in these systems. Kochenderfer outlined methodologies and research applications for building safer systems, drawing from his work on air traffic control, unmanned aircraft, and automated driving. Why it matters: The development of safe and reliable autonomous systems is crucial for various applications in the region, and insights from experts like Kochenderfer can guide research and development efforts at institutions like MBZUAI.
Dr. Hao Dong from Peking University presented research on addressing the challenge of limited large-scale training data in embodied AI, particularly for manipulation, task planning, and navigation. The presentation covered simulation learning and large models. Dr. Dong is a chief scientist of China's National Key Research and Development Program and an area chair/associate editor for NeurIPS, CVPR, AAAI, and ICRA. Why it matters: Overcoming data scarcity is crucial for advancing embodied AI research and enabling more sophisticated robotic applications in the region.
Krishna Murthy, a postdoc at MIT, researches computational world models to enable robots to understand and operate effectively in the physical world. His work focuses on differentiable computing approaches for spatial perception and interfaces large image, language, and audio models with 3D scenes. Murthy envisions structured world models working with scaling-based approaches to create versatile robot perception and planning algorithms. Why it matters: This research could significantly advance robotics by enabling more sophisticated perception, reasoning, and action capabilities in embodied agents.
Giuseppe Loianno from NYU presented research on creating "Super Autonomous" robots (USARC) that are Unmanned, Small, Agile, Resilient, and Collaborative. The research focuses on learning models, control, and navigation policies for single and collaborative robots operating in challenging environments. The talk highlighted the potential of these robots in logistics, reconnaissance, and other time-sensitive tasks. Why it matters: This points to growing research interest in advanced robotics in the region, especially given the focus on smart cities and automation.
Mingyu Ding from UC Berkeley presented research on endowing robots with human-like commonsense and physical reasoning capabilities. The talk covered multimodal commonsense reasoning integrating vision, world models, and language-based task planners. It also discussed physical reasoning approaches for robots to infer dynamics and physical properties of objects. Why it matters: Enhancing robots with these capabilities can improve their ability to generalize across everyday tasks, leading to greater social benefits and impact.
Egor Zakharov from ETH Zurich AIT lab will present research on creating controllable and detailed 3D head avatars using data from consumer-grade devices. The presentation will cover high-fidelity image-based facial reconstruction/animation and video-based reconstruction of detailed structures like hairstyles. He will showcase integrating human-centric assets into virtual environments for real-time telepresence and entertainment. Why it matters: This research contributes to advancements in digital human modeling and telepresence, with applications in communication and gaming within the region.
Qingbiao Li from the Oxford Robotics Institute is researching decentralized multi-robot coordination using Graph Neural Networks (GNNs). The approach builds an information-sharing mechanism within a decentralized multi-robot system through GNNs and imitation learning. It also uses visual machine learning-assisted navigation with panoramic cameras to guide robots in unseen environments. Why it matters: This research could improve the effectiveness of automated mobile robot systems in urban rail transit and warehousing logistics in the GCC region, where smart city initiatives are growing.
Pascal Fua from EPFL presented an approach to implementing convolutional neural nets that output complex 3D surface meshes. The method overcomes limitations in converting implicit representations to explicit surface representations. Applications include single view reconstruction, physically-driven shape optimization, and bio-medical image segmentation. Why it matters: This research advances geometric deep learning by enabling end-to-end trainable models for 3D surface mesh generation, with potential impact on various applications in computer vision and biomedical imaging in the region.
Patrick van der Smagt, Director of AI Research at Volkswagen Group, discussed the use of generative machine learning models for predicting and controlling complex stochastic systems in robotics. The talk highlighted examples in robotics and beyond and addressed the challenges of achieving quality and trust in AI systems. He also mentioned his involvement in a European industry initiative on trust in AI and his membership in the AI Council of the State of Bavaria. Why it matters: Understanding control in robotics, along with trust in AI, are key issues for further development of autonomous systems, especially in industrial applications within the GCC region.
Paul Liang from CMU presented on machine learning foundations for multisensory AI, discussing a theoretical framework for modality interactions. The talk covered cross-modal attention and multimodal transformer architectures, and applications in mental health, pathology, and robotics. Liang's research aims to enable AI systems to integrate and learn from diverse real-world sensory modalities. Why it matters: This highlights the growing importance of multimodal AI research and its potential for advancements across various sectors in the region, including healthcare and robotics.
Ivan Laptev from INRIA Paris presented a talk at MBZUAI on embodied multi-modal visual understanding, covering advancements in video understanding tasks like question answering and captioning. The talk highlighted recent work on vision-language navigation and manipulation. He argued that detailed understanding of the physical world through vision is still in early stages, discussing open research directions related to robotics and video generation. Why it matters: The discussion of robotics applications and future research directions in embodied AI could influence the direction of AI research and development in the UAE, particularly at MBZUAI.
MBZUAI will present robotics research and solutions at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) in Abu Dhabi from October 14-18. Professors Yoshihiko Nakamura and Sami Haddadin, renowned robotics experts, lead MBZUAI's robotics initiatives. MBZUAI will be located at Booth 6 at ADNEC. Why it matters: Showcasing MBZUAI's commitment to becoming a global leader in AI and robotics research, attracting top talent and fostering interdisciplinary collaboration in the UAE.
MBZUAI Professor Ivan Laptev is working to bridge the gap between data-driven AI systems and embodied agents (robots). He notes challenges in robotics including data scarcity, the need to generate new data through actions, and the requirement for real-time operation. Laptev aims to transfer innovations from computer vision to robotics, addressing these challenges to improve robots' ability to interpret and respond to the complexities of the real world. Why it matters: Overcoming these hurdles is crucial for advancing robotics and enabling robots to effectively interact with and navigate dynamic real-world environments.
MBZUAI Professor Yoshihiko Nakamura discusses his career in robotics, starting from its early days as a field. He notes the initial skepticism towards robotics as an academic discipline in the 1970s and its gradual formalization. Nakamura's research is driven by the mathematics of movement, optimization, and non-linearity, drawing inspiration from neuroscience, psychology, and linguistics. Why it matters: Nakamura's insights provide a historical perspective on the evolution of robotics research and highlight the interdisciplinary nature of the field, with implications for the future of AI development in the region.
MBZUAI's new robotics department, launched in August 2023, aims to develop AI-driven robotic solutions for key UAE sectors. Professor Dezhen Song, the inaugural Professor of Robotics, highlights the department's focus on the "brain side" of robotics, enhancing perception, navigation, and control. Specific applications include automated infrastructure inspection for the energy sector and AI-driven precision agriculture techniques to improve crop yields and resource efficiency. Why it matters: MBZUAI's robotics research will contribute to the UAE's strategic goals in energy, food security, and sustainable development.
MBZUAI Professor Ian Reid discusses his career in embodied AI, from early work on active vision at Oxford to current research. He highlights three key developments: cameras as geometric sensors, visual SLAM, and advancements in robot navigation. Reid distinguishes embodied AI from systems like ChatGPT, emphasizing its need for understanding and interaction with the physical world. Why it matters: The insights from a leading expert underscore the importance of embodied AI as the next frontier in intelligent systems and robotics in the region.