معرفی
Shuyang Ling is an Assistant Professor of Data Science at NYU Shanghai and a Global Network Assistant Professor at the Tandon School of Engineering, New York University. He joined NYU Shanghai in September 2019 as an Assistant Professor Faculty Fellow of Data Science, after serving as a Courant Instructor/Assistant Professor at the Courant Institute of Mathematical Sciences and Center for Data Science at NYU from 2017-2019.
Dr. Ling received his PhD in Applied Mathematics from the University of California, Davis in 2017 under the supervision of Thomas Strohmer. He also earned an MS in Statistics from UC Davis in 2016 and completed his undergraduate studies in Mathematics and Applied Mathematics at Fudan University in Shanghai, China in 2012.
Dr. Ling's research focuses broadly on the mathematics of data science, with particular interest in tackling inverse problems from engineering applications and extracting meaningful information from large-scale and heterogeneous datasets. His work spans a broad spectrum of subjects including:
- Optimization (convex and non-convex)
- Probability and statistics
- Computational harmonic analysis
- Numerical linear algebra
- Signal processing and machine learning theory
His recent publications demonstrate a strong focus on synchronization problems, neural collapse phenomena, and optimization landscapes. He has made significant contributions to understanding the theoretical foundations of spectral methods, non-convex optimization, and convex relaxations in data science applications. His work often bridges theoretical guarantees with practical algorithms for problems in signal processing and machine learning.
Dr. Ling has received several prestigious awards and grants including the SIAM Student Paper Prize in 2017, Shanghai Eastern Scholar for Young Professionals (2019), Shanghai Rising Star Program (A-type) (2024), and grants from the Natural Science Foundation of Shanghai and National Key R&D Program of China.
He is actively involved in mentoring the next generation of researchers, currently advising three Ph.D. students at NYU Shanghai: Jiayang Yin (co-advised with Prof. Mathieu Lauriere), Wanli Hong, and Ziliang Samuel Zhong. He has also supervised numerous undergraduate thesis projects at NYU Shanghai since 2020. Dr. Ling is part of the Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning at NYU Shanghai, where he organizes seminars and reading groups on data science and machine learning.
