I am currently an MS student in Computer Science at KAUST’s Image and Video Understanding Lab (IVUL), advised by Prof. Bernard Ghanem, where I am passionate about applying robust machine learning algorithms to tackle real-world challenges. For my future PhD studies, I am eager to leverage these machine learning tools to make a positive impact in the fields of medical imaging, medicinal chemistry, and healthcare.
My undergraduate research at Cornell University, where I worked with Prof. Fengqi You at the Process-Energy-Environmental Systems Engineering (PEESE) lab, gave me a solid foundation in large-scale system optimization, particularly in the area of hybrid quantum-classical approaches to industrial scheduling. Currently, in my MS studies, I am engaged in machine learning research, including continual learning from image and video data, robustness and domain generalization, and molecular conformation generation.
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MS in Computer Science, 2021-Present
BS in Electrical and Computer Engineering, 2021