KAUST · · Notable
KAUST Ph.D. students Kai Lu and Yuqing Chen won Best Presentation awards at a Society of Exploration Geophysicists workshop in Beijing. Lu's research focuses on machine learning applications in seismic processing, while Chen uses machine learning for automated semblance spectrum picking. They both leverage KAUST's Shaheen II supercomputer for their work. Why it matters: This highlights the increasing role of AI and ML in the oil and gas industry, and KAUST's contribution to advancing these technologies.
KAUST · machine learning · seismic processing · oil and gas · Shaheen II
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KAUST ·
KAUST Ph.D. student Manal Al-Qahtani won a best poster presentation award. The award was presented in the late summer of 2016. The announcement was made on the KAUST website. Why it matters: Showcases the achievements and talent within KAUST's Ph.D. program.
KAUST ·
KAUST Ph.D. students Amal Hajjaj and Sherif Tella won best paper awards at the American Society of Mechanical Engineers 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference. Tella's paper was on electrothermally actuated microbeams, while Hajjaj's paper focused on the behavior of MEMS resonators. The students are supervised by KAUST Associate Professor Mohammad Younis. Why it matters: The awards recognize significant research contributions in micro- and nanosystems and highlight KAUST's strength in fostering impactful engineering research.
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KAUST Ph.D. student Zhaolun Liu won the best student presentation at the 2017 Society of Exploration Geophysicists (SEG) Full-Waveform Inversion (FWI) and Beyond Workshop in Beijing. Liu's presentation was on "3D Wave-Equation Dispersion Inversion of Surface Waves," based on a paper co-authored with Jing Li and Professor Gerard Schuster. The paper describes a new method called wave equation dispersion inversion (WD) for inverting surface waves. Why it matters: This award recognizes KAUST's contributions to geophysics and seismic imaging, highlighting the university's research capabilities and access to high-performance computing.
KAUST ·
KAUST Ph.D. students David Evangelista and Xianjin Yang won best paper awards at international conferences this summer for their work in mean-field game theory. Evangelista's paper focused on solutions for stationary mean-field games with congestion, while Yang's paper developed numerical methods for homogenization problems. The awards were presented at the 18th International Symposium on Dynamic Games and Applications in France and the 12th American Institute of Mathematical Sciences (AIMS) Conference in Taiwan. Why it matters: The recognition highlights KAUST's strength in applied mathematics and computational science, specifically in the emerging field of mean-field games with applications across various domains.