Ming Gu

Ming Gu is a Professor in the Department of Mathematics at the University of California, Berkeley. He specializes in Numerical Linear Algebra and Scientific Computing, with a focus on developing efficient algorithms for structured matrices and large-scale data analysis.

• Organized Matrix Computations and Scientific Computing Seminars (2009-2017)
• Published 15+ papers on QR algorithms, Toeplitz matrices, randomized algorithms, and low-rank approximations

His research addresses rank-revealing factorizations, randomized subspace iteration, and preconditioning techniques, often bridging numerical analysis with applications in machine learning and optimization. Students advised by him (e.g., Jiaming Wang, Onyebuchi Ekenta) have explored spectrum-revealing CUR decomposition and truncated SVD.

• Contact: mgu@math.berkeley.edu
• Office: 861 Evans Hall, UC Berkeley