Dr. Huang is an Assistant Professor in the Departments of Computational Mathematics, Science and Engineering and Mathematics at Michigan State University. Her research develops scalable and reliable computational methods for extracting structure from large, incomplete, and noisy datasets. By combining computational harmonic analysis, numerical linear algebra, and optimization, she studies matrix and tensor methods, structured sampling, and robust data recovery. Her work supports the analysis and reconstruction of high-dimensional spatiotemporal data arising from complex scientific systems and advances mathematical tools for data-driven scientific computing. She also prepares students for careers in computational science through interdisciplinary research and mentoring in applied mathematics, data science, and scientific computing.