Sami Haddadin from the Technical University of Munich (TUM) discusses a shift in robotics towards machines that autonomously develop their own blueprints and controls. He highlights advancements driven by human-centered design, soft control, and model-based machine learning, enabling human-robot collaboration in manufacturing and healthcare. Haddadin also presents progress towards autonomous machine design and modular control architectures for complex manipulation tasks. Why it matters: This research has implications for advancing robotics and AI in the GCC region, especially in manufacturing and healthcare, by enabling safer and more efficient human-robot collaboration.
MBZUAI Professor Sami Haddadin and his team developed a new framework called Tactile Skills to teach robots manual skills through touch and trial and error. This framework aims to address the gap in robots' ability to learn basic physical tasks compared to AI's advancements in language and image generation. The research, published in Nature Machine Intelligence, focuses on enabling robots to perform manipulation skills at industrial levels with low energy and compute demands. Why it matters: This research could lead to robots capable of performing household maintenance, industrial tasks, and even assisting in medical or rehabilitation settings, potentially solving labor shortages in various sectors in the region and beyond.
MBZUAI researchers have developed "Tactile Skills," a new embodied AI framework enabling robots to rapidly learn complex tactile tasks. The framework combines expert process knowledge with reusable tactile control and adaptation components, reducing reliance on extensive datasets. Tested on 28 industrial tasks, the robots achieved nearly 100% success, demonstrating adaptability to changing conditions. Why it matters: This breakthrough offers a practical and scalable approach to robotic automation, potentially transforming robots into adaptable assistants across diverse industries in the GCC.
KAUST's Rapid Research Response Team (R3T), including Professor Samir Hamdan, is working to understand and counteract the spread of COVID-19. The team assembled a complete homemade, one-step RT-PCR test, comparable to commercial kits, with a patent-free manufacturing recipe. KAUST R3T is also researching faster, more accurate point-of-care tests, including a CRISPR-based molecular test. Why it matters: This research provides accessible testing solutions and contributes to more effective and rapid detection methods for combating viral spread in the region and globally.
MBZUAI's VP of Research, Professor Sami Haddadin, and his team at TUM have developed the 'Tree of Robots,' a new framework for categorizing robots based on capabilities and morphology rather than appearance or purpose. This framework uses a Process Database and Metrics Definitions to assess a robot's fitness for specific tasks, resulting in a fitness score and classification within the tree. The research appears in the March 2025 issue of Nature Machine Intelligence. Why it matters: This systematic approach could fundamentally change how we understand, compare, and develop robotic systems, enabling a deeper understanding of intelligent machines and their potential.
KAUST's Sami Al-Ghamdi is conducting multidisciplinary research on urban sustainability to mitigate climate change and optimize resource consumption. His work supports Saudi Arabia’s Vision 2030, particularly urban gigaprojects like NEOM and Saudi Downtown. He develops computational models to assess the environmental impact of various aspects of the built environment. Why it matters: This research is crucial for advancing sustainable urban development in Saudi Arabia and achieving its ambitious environmental goals.
KAUST Ph.D. candidate Ahmed Alfadhel won the IEEE best research paper award for his work on artificial skin. The artificial skin design uses a flexible magnetic nano-composite cilia surface with a magnetic field sensing element. The device exhibits unprecedented flexibility due to the embedding of magnetic cilia and the sensing element in a polymeric surface. Why it matters: This research enables the development of cheaper, more versatile tactile sensors for health monitoring, robotics, and prosthetics, potentially advancing personalized healthcare and human-machine interfaces in the region.
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.