An article from KAUST discusses the impact of COVID-19 on automation, material science, and VR. It suggests increased automation, voice activation, and motion detection to reduce transmission in public spaces. KAUST faculty member Derya Baran is working on antimicrobial materials for high-touch locations, and KAUST is exploring VR for virtual labs. Why it matters: The pandemic is accelerating the adoption of AI-driven solutions and advanced materials research within Saudi Arabia to address public health challenges.
Aitonomi, a company specializing in autonomous EV transport systems, held a recruitment event at KAUST to tap into the university's talent pool. Aitonomi aims to support Saudi Arabia's Vision 2030 by developing fully autonomous and electric transport systems and plans to hire up to 12 skilled workers in KSA for 2024. The company hopes to establish an in-Kingdom manufacturing center and training facility. Why it matters: This initiative highlights the growing demand for AI talent in Saudi Arabia and KAUST's role in supporting the Kingdom's technological advancements and goals for sustainable transportation.
This study introduces a reinforcement learning (RL) framework using Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) to optimize the cleaning schedules of photovoltaic panels in arid regions. Applied to a case study in Abu Dhabi, the PPO-based framework demonstrated up to 13% cost savings compared to simulation optimization methods by dynamically adjusting cleaning intervals based on environmental conditions. The research highlights the potential of RL in enhancing the efficiency and reducing the operational costs of solar power generation.
MBZUAI Assistant Professor Qirong Ho is researching AI operating systems to standardize algorithms and enable non-experts to create AI applications reliably. He emphasizes that countries mastering mass production of AI systems will benefit most from the Fourth Industrial Revolution. Ho is co-founder and CTO at Petuum Inc., an AI startup creating standardized building blocks for affordable and scalable AI production. Why it matters: This research aims to democratize AI development and promote widespread adoption across industries in the UAE and beyond.
The MBZUAI Executive Program's fifth module will cover the future of robotics, featuring UC Berkeley Professors Pieter Abbeel and Ken Goldberg. Abbeel will discuss deep learning in robotics, while Goldberg will share insights on robotic technologies in business. The 12-week program aims to support the UAE's AI leadership through education and innovation, with 42 high-level decision-makers participating. Why it matters: By training leaders in AI and robotics, the program can accelerate the adoption of advanced automation technologies across various sectors in the UAE and the broader region.
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.
This paper proposes a smart dome model for mosques that uses AI to control dome movements based on weather conditions and overcrowding. The model utilizes Congested Scene Recognition Network (CSRNet) and fuzzy logic techniques in Python to determine when to open and close the domes to maintain fresh air and sunlight. The goal is to automatically manage dome operation based on real-time data, specifying the duration for which the domes should remain open each hour.