Bin Shi | Applied Mathematics | Research Excellence Award

Prof. Bin Shi | Applied Mathematics | Research Excellence Award

Fudan University | China 

Bin Shi is an associate professor with tenure whose research spans mathematics, machine learning, and the physical sciences, with a strong emphasis on theoretical foundations and interdisciplinary applications. His work focuses on optimization methods for machine learning, where he develops mathematically rigorous algorithms to improve efficiency, stability, and generalization in large-scale and complex learning systems. He has made significant contributions to numerical analysis and scientific computing, particularly in designing and analyzing computational methods for high-dimensional and nonlinear problems arising in science and engineering. A central theme of his research is data assimilation, integrating observational data with mathematical models to enhance prediction and uncertainty quantification in complex dynamical systems. He also explores quantum algorithms, investigating how quantum computing paradigms can accelerate optimization and learning tasks. His background in nonlinear and stochastic sciences underpins his studies of systems influenced by randomness, multiscale interactions, and long-term dynamics. In addition, his research extends to fluid dynamics, including turbulence, geophysical flows, and astrophysical phenomena, where advanced mathematical and computational techniques are used to understand highly nonlinear and chaotic behaviors. Overall, his work bridges rigorous theory with computational practice, contributing to the development of reliable algorithms and models for modern data-driven and physics-informed scientific challenges.

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Featured Publications

Understanding the Acceleration Phenomenon via High-Resolution Differential Equations

B. Shi, S.S. Du, W. Su, M.I. Jordan — Mathematical Programming, 195, 79–148 (2022) · 379 citations
Acceleration via Symplectic Discretization of High-Resolution Differential Equations

B. Shi, S.S. Du, W. Su, M.I. Jordan — Advances in Neural Information Processing Systems (NeurIPS), 32 (2019) · 166 citations
On Learning Rates and Schrödinger Operators

B. Shi, W.J. Su, M.I. Jordan — Journal of Machine Learning Research, 24(379), 1–53 (2023) · 85 citations
Mathematical Theories of Machine Learning: Theory and Applications

B. Shi, S.S. Iyengar — Springer International Publishing (2020) · 44 citations
Gradient Norm Minimization of Nesterov Acceleration: o(1/k³)

S. Chen, B. Shi, Y. Yuan — arXiv preprint, arXiv:2209.08862