Dr. Muhammad Wakil Shahzad, a research scientist at KAUST's Water Desalination and Reuse Center, won the 'Best Oral Presentation' award at the 2nd Global Conference and Expo on Applied Science, Engineering and Technology in Amsterdam. The award recognized Shahzad's research and presentation on the "Fallacy of Energy Efficiency of Desalination processes Comparison." He also delivered the opening ceremony speech during the conference. Why it matters: This award recognizes KAUST's contribution to research in water desalination, a critical area for Saudi Arabia and the broader Middle East.
KAUST research scientist Muhammad Wakil Shahzad won the 'best presenter' award at the 2019 Global Summit and Expo on Power & Energy Engineering in Dubai. His presentation focused on the energy efficiency of seawater desalination processes. Shahzad's research at KAUST's Water Desalination and Reuse Center aims to improve desalination methods and develop water reclamation strategies. Why it matters: This award highlights KAUST's contributions to innovative desalination technologies, which are crucial for addressing water scarcity in the Gulf region and drought-stricken areas globally.
MBZUAI Ph.D. candidate Muhammad Maaz has been awarded the 2025 Google Ph.D. Fellowship in Machine Perception. Maaz is the first student from MBZUAI and the first from the Gulf region to receive this recognition, which includes funding, mentorship, and $50,000. He has published extensively in top-tier CV/NLP venues and has over 4,500 citations. Why it matters: This award highlights the growing prominence of MBZUAI and the increasing quality of AI research in the Gulf region on the global stage.
Dr. Abdelrahman AlMahmoud from TII's Secure Systems Research Center (SSRC) will participate in a WGISTA webinar on adopting a digital mindset in auditing and fighting corruption. The webinar, organized by the International Organization of Supreme Audit Institutions (INTOSAI), will discuss the impact of emerging technologies on public sector auditing. Dr. AlMahmoud will share insights on how AI and Big Data can enable auditors to process data at a new scale. Why it matters: This highlights the UAE's growing role in applying advanced technologies like AI and big data to improve governance and accountability in the public sector.
Professor Mohammad Younis, a new Associate Professor of Mechanical Engineering at KAUST, focuses his research on micro and nanotechnology, specifically the interface between nonlinear dynamics and micro/nano electromechanical systems (MEMS and NEMS). He is developing a generic platform for sensing and actuation with potential uses in detecting poisonous gases, biohazards, and earthquake signals. He is also working on actuator systems that can assist elderly people after a fall by automatically calling for help. Why it matters: This research has significant implications for safety, environmental monitoring, and elderly care in the Middle East and beyond.
MEDAD, a KAUST spin-off, won the 2020 MEED Sustainability Medal for its "Innovative Hybrid Solar Desalination Cycle." The MEDAD hybrid cycle desalinates seawater using solar energy at 60-80 degrees Celsius, combining adsorption with multi-effect desalination. The cycle achieved performance levels of 20% of thermodynamic limits and a water production cost of $0.48/m3. Why it matters: This award recognizes the potential of KAUST-developed technology to address critical water scarcity challenges in the GCC region through sustainable and cost-effective desalination.
MBZUAI alumnus Adnan Khan is pursuing a Ph.D. at Carleton University, focusing his research on using computer vision to improve accessibility in healthcare, particularly for the visually impaired. His work builds upon his master's thesis at MBZUAI, which focused on domain generalization, enabling models to adapt across different data domains. Khan credits his experiences at MBZUAI for shaping his community spirit and career path. Why it matters: This highlights the role of AI education in fostering socially impactful research and driving innovation in healthcare accessibility in the region and beyond.
Technology Innovation Institute's (TII) Directed Energy Research Center (DERC) is integrating machine learning (ML) techniques into signal processing to accelerate research. One project used convolutional neural networks to predict COVID-19 pneumonia from chest x-rays with 97.5% accuracy. DERC researchers also demonstrated that ML-based signal and image processing can retrieve up to 68% of text information from electromagnetic emanations. Why it matters: This adoption of ML for signal processing at TII highlights the potential for advanced AI techniques to enhance research and security applications in the UAE.