KAUST has 16 researchers on the 2025 Clarivate Highly Cited Researchers list, representing 59% of the total from Saudi Arabia. The list recognizes researchers whose publications rank in the top 1% of citations between 2014 and 2024. Some notable research includes work on land degradation, the Red Sea's blue economy, and quantum random number generation. Why it matters: This recognition highlights KAUST's growing research influence and its ability to attract top international talent, contributing to Saudi Arabia's scientific advancement.
The Technology Innovation Institute (TII) congratulated Prof. Merouane Debbah, Chief Researcher of AI & Telecoms Systems, for being included in Clarivate’s 2021 Highly Cited Researchers List. This list recognizes Prof. Debbah as being in the top 1% of researchers worldwide. TII expressed pride in this global recognition of Prof. Debbah's work. Why it matters: This highlights the UAE's growing prominence in attracting and supporting top AI researchers, enhancing its reputation as an innovation hub.
KAUST has been ranked No. 1 in the Times Higher Education (THE) Arab University Rankings for the third consecutive year. The 2025 edition of the rankings evaluated universities across 20 key indicators, including global citation impact and industry collaboration. Sixteen of KAUST's faculty were named on the 2025 Clarivate highly cited list. Why it matters: This recognition reinforces KAUST’s position as a leading research university in the Arab world and reflects Saudi Arabia’s increasing global competitiveness in research, innovation, and advanced education.
KAUST has the most Clarivate Highly Cited Researchers in the Middle East for 2024, with 14 faculty members on the list. This represents 61% of the highly cited researchers in Saudi Arabia and 7% of KAUST's total faculty. Three KAUST researchers—Osman Bakr, Carlos Duarte, and Yoshihide Wada—are highly cited across multiple categories. Why it matters: This recognition reinforces KAUST's position as a leading research university in the region and contributes to Saudi Arabia's Vision 2030 goals.
Eighteen KAUST scientists were named among the world's most influential researchers by Clarivate. These researchers have authored studies in the top 1% of scholarly citations worldwide over the past decade. This is an increase from 15 in 2022, representing almost 10% of KAUST's total faculty. Why it matters: This recognition highlights KAUST's growing influence in global research and its commitment to producing impactful scientific contributions in the Middle East.
Clarivate's 2022 list of Highly Cited Researchers includes multiple KAUST faculty members. These researchers are recognized for being in the top 1% of cited research globally, with representation across computer science, materials science, and other fields. The KAUST faculty named include Carlos Duarte, Pierre Magistretti, Matthew F. McCabe, and Mark Tester. Why it matters: Recognition of KAUST faculty highlights the university's growing research prominence and impact in key scientific domains.
Clarivate Web of Science Group recognized fifteen KAUST faculty members and one postdoctoral researcher among the 2020 Highly Cited Researchers. These individuals rank in the top 1% of research cited worldwide across diverse fields. They are leaders in health, environment, communications, and food security. Why it matters: This recognition highlights KAUST's commitment to pioneering research and its growing influence in addressing globally relevant challenges.
MBZUAI visiting professor of computer vision, Xiaojun Chang, has been named to Clarivate’s 2024 Highly Cited Researchers list, placing him in the top 1% of researchers worldwide. Chang has accumulated over 18,000 citations from around 200 papers, with his research focusing on multimodal foundation models and their applications to embodied AI and healthcare. Chang also holds positions at the University of Technology Sydney and RMIT University in Australia. Why it matters: This recognition highlights MBZUAI's growing impact and its role in fostering interdisciplinary collaboration and innovation in AI research, attracting further opportunities and collaborations.