معرفی
Nan Chen is an Associate Professor at the Department of Mathematics, University of Wisconsin-Madison, and a faculty affiliate of the Institute for Foundations of Data Science (IFDS), a TRIPODS Phase II Initiative. His research spans applied mathematics, data science, geophysics, and machine learning, focusing on modeling complex systems, stochastic methods, numerical algorithms, and uncertainty quantification (UQ) for large-dimensional dynamics.
- PhD: Courant Institute of Mathematical Sciences (CIMS) & Center for Atmosphere and Ocean Science (CAOS), New York University (2016)
- Postdoc: CIMS, NYU (2016–2018)
- Advisor: Andrew Majda
- Master's: School of Mathematical Sciences, Fudan University (2013)
- Bachelor's: Mechanical Engineering, Fudan University (2010)
His work emphasizes UQ, data assimilation, and predictive modeling for systems with turbulence, partial information, and non-Gaussian features. Applications include atmosphere-ocean science (e.g., El Niño, Madden-Julian Oscillation) and material science. He also develops computational tools for excitable media, neuroscience, and high-dimensional data analysis.
He contributes to education through courses like Uncertainty Quantification and Data Assimilation, and public outreach via articles in Elsevier's Reference Module in Earth Systems. He co-organizes the Data Meets Dynamics workshop to promote interdisciplinary collaboration and mentorship.
