KAUST Associate Professor Aamir Farooq has been named a co-recipient of the 2019 Hiroshi Tsuji Early Career Researcher Award, co-sponsored by Elsevier and The Combustion Institute. Farooq, who leads the KAUST Chemical Kinetics and Laser Sensors Laboratory, is recognized for his work on fuel ignition chemistry. His research aims to improve fuel efficiency and reduce greenhouse gas emissions in transportation and power generation. Why it matters: This award highlights KAUST's commitment to fostering talented faculty and advancing research in clean combustion, a critical area for Saudi Arabia's energy future.
Jysoo Lee, Facilities Director of Research Computing Core Labs at KAUST, received the SCA HPC Leadership/Achievement Award at SupercomputingAsia 2022 in Singapore. The award recognizes Lee's leadership in developing South Korea's HPC community and advancing international cooperation. Lee led the legislation of the “National Supercomputing Promotion Act” and founded the National Institute of Supercomputing and Networking (NISN) in South Korea. Why it matters: This award highlights KAUST's role in attracting top global talent in HPC and showcases the increasing importance of supercomputing infrastructure in the region.
KAUST Professor Yoshihide Wada has been awarded the 2025 Joanne Simpson Medal by the American Geophysical Union (AGU). The award recognizes Wada's pioneering research modeling the human impact on the global hydrological cycle. Wada joined KAUST in 2022 and has collaborated with Saudi stakeholders to develop scalable solutions for the Kingdom. Why it matters: This award highlights KAUST's growing prominence in environmental research and its commitment to addressing critical global challenges related to water resources and climate change.
KAUST Ph.D. student Raid AlRowais won the best paper award at the 11th International Meeting on Advances in ThermoFluids in Japan. The conference took place at Kyushu University. AlRowais received the award from Professor Takahiko Miyazaki. Why it matters: This award recognizes promising research and talent at KAUST in thermal and fluid sciences.
KAUST Discovery Ph.D. student Chun-Ho Lin received the best paper award at the 2nd International Symposium on Devices and Application of Two-dimensional Materials in June 2016. The award recognizes Lin's contributions to the field of two-dimensional materials. Why it matters: Recognition of KAUST student research highlights the university's contributions to advanced materials science.
Mae AlMansoori from TII's Directed Energy Research Center won the Young Scientist Award at URSI Kleinheubacher Tagung 2020. Her paper introduced a correlation metric to evaluate the influence of random variables on high-power electromagnetic sources, specifically a Vircator model. The study combined extreme value theory and descriptive statistics to analyze peak output power variability and identify dominant factors. Why it matters: The research offers a framework for managing uncertainties in high-power electromagnetic sources and optimizing their efficiency, relevant for defense and energy applications in the region.
KAUST Professor Tadeusz Patzek has received the EAGE Desiderius Erasmus Award for his contributions to energy supply research. The award recognizes Patzek's analysis of shale gas and biofuels, as well as his work on climate change and environmental damage. Patzek currently directs the Ali I. Al-Naimi Petroleum Engineering Research Center at KAUST, focusing on the impact of fossil fuels and agrofuels on social and ecological systems. Why it matters: The recognition highlights KAUST's contribution to research on sustainable energy strategies and their impact on global environmental policy.
KAUST Ph.D. student Jinhui Xiong won the best paper award at the 24th International Symposium on Vision, Modeling, and Visualization in Germany for his paper "Stochastic Convolutional Sparse Coding". The paper, co-authored with KAUST Professors Peter Richtárik and Wolfgang Heidrich, introduces a novel stochastic spatial-domain solver for Convolutional Sparse Coding (CSC). The proposed algorithm outperforms state-of-the-art solutions in terms of execution time and offers an improved representation for learning dictionaries from sample images. Why it matters: This award recognizes significant research in efficient image representation and dictionary learning, contributing to advancements in visual computing and AI at KAUST.