I am a computer scientist specializing in machine learning, with a particular interest in developing scalable algorithms and data-driven methods to address complex scientific and societal challenges. My research spans statistical learning theory, deep learning, and parallel computing, with applications in healthcare, biomedical imaging, and interdisciplinary data science.

I earned my Ph.D. in Computer Science from the University of Colorado Boulder, where I conducted research in scientific computing under the supervision of Prof. Xiao-Chuan Cai. My academic work reflects a strong commitment to both theoretical foundations and real-world applications—leveraging machine learning to uncover meaningful insights from large, heterogeneous datasets.

I am deeply engaged in interdisciplinary collaboration and particularly interested in connecting machine learning with fields such as quantitative psychology, cognitive science, and environmental science.