Nan Chen

Nan Chen

University of Wisconsin-Madison

H-index: 22

North America-United States

About Nan Chen

Nan Chen, With an exceptional h-index of 22 and a recent h-index of 17 (since 2020), a distinguished researcher at University of Wisconsin-Madison, specializes in the field of Uncertainty quantification, Data assimilation, Stochastic modeling, Climate dynamics, Machine learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Statistical Response of ENSO Complexity to Initial Value and Model Parameter Perturbations

Particle-continuum multiscale modeling of sea ice floes

A Causation-Based Computationally Efficient Strategy for Deploying Lagrangian Drifters to Improve Real-Time State Estimation

A Physics-Informed Auto-Learning Framework for Developing Stochastic Conceptual Models for ENSO Diversity

Launching drifter observations in the presence of uncertainty

CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation

LEMDA: A Lagrangian-Eulerian Multiscale Data Assimilation Framework

A physics-informed data-driven algorithm for ensemble forecast of complex turbulent systems

Nan Chen Information

University

Position

Assistant Professor of Mathematics

Citations(all)

1285

Citations(since 2020)

978

Cited By

631

hIndex(all)

22

hIndex(since 2020)

17

i10Index(all)

37

i10Index(since 2020)

34

Email

University Profile Page

University of Wisconsin-Madison

Google Scholar

View Google Scholar Profile

Nan Chen Skills & Research Interests

Uncertainty quantification

Data assimilation

Stochastic modeling

Climate dynamics

Machine learning

Top articles of Nan Chen

Title

Journal

Author(s)

Publication Date

Statistical Response of ENSO Complexity to Initial Value and Model Parameter Perturbations

arXiv preprint arXiv:2401.03281

Marios Andreou

Nan Chen

2024/1/6

Particle-continuum multiscale modeling of sea ice floes

arXiv preprint arXiv:2303.07819

Quanling Deng

Samuel N Stechmann

Nan Chen

2023/3/14

A Causation-Based Computationally Efficient Strategy for Deploying Lagrangian Drifters to Improve Real-Time State Estimation

arXiv preprint arXiv:2402.10034

Erik Bollt

Nan Chen

Stephen Wiggins

2024/2/15

A Physics-Informed Auto-Learning Framework for Developing Stochastic Conceptual Models for ENSO Diversity

arXiv preprint arXiv:2402.04585

Yinling Zhang

Nan Chen

Jerome Vialard

Xianghui Fang

2024/2/7

Launching drifter observations in the presence of uncertainty

Physica D: Nonlinear Phenomena

Nan Chen

Evelyn Lunasin

Stephen Wiggins

2024/2/3

CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation

arXiv preprint arXiv:2404.06749

Chuanqi Chen

Nan Chen

Jin-Long Wu

2024/4/10

LEMDA: A Lagrangian-Eulerian Multiscale Data Assimilation Framework

arXiv preprint arXiv:2401.18048

Quanling Deng

Nan Chen

Samuel N Stechmann

Jiuhua Hu

2024/1/31

A physics-informed data-driven algorithm for ensemble forecast of complex turbulent systems

Applied Mathematics and Computation

Nan Chen

Di Qi

2024/4/1

Stochastic Toolkits

Nan Chen

2023/3/14

Introduction to Information Theory

Nan Chen

2023/3/14

Quantifying the predictability of ENSO complexity using a statistically accurate multiscale stochastic model and information theory

Journal of Climate

Xianghui Fang

Nan Chen

2023/4/15

Combining Stochastic Parameterized Reduced‐Order Models With Machine Learning for Data Assimilation and Uncertainty Quantification With Partial Observations

Journal of Advances in Modeling Earth Systems

Changhong Mou

Leslie M Smith

Nan Chen

2023/10

Data-Driven Low-Order Stochastic Models

Nan Chen

2023/3/14

Parameter Estimation with Uncertainty Quantification

Nan Chen

2023/3/14

A simple multiscale intermediate coupled stochastic model for El Niño diversity and complexity

Journal of Advances in Modeling Earth Systems

Nan Chen

Xianghui Fang

2023/4

Uncertainty quantification of nonlinear Lagrangian data assimilation using linear stochastic forecast models

Physica D: Nonlinear Phenomena

Nan Chen

Shubin Fu

2023/10/1

An efficient data-driven multiscale stochastic reduced order modeling framework for complex systems

Journal of Computational Physics

Changhong Mou

Nan Chen

Traian Iliescu

2023/11/15

Stochastic methods for modeling and predicting complex dynamical systems: uncertainty quantification, state estimation, and reduced-order models

Nan Chen

2023/3/13

Basic Stochastic Computational Methods

Nan Chen

2023/3/14

Instruction Manual for the MATLAB Codes

Nan Chen

2023/3/14

See List of Professors in Nan Chen University(University of Wisconsin-Madison)

Co-Authors

H-index: 49
John S. Wettlaufer

John S. Wettlaufer

University of Oxford

H-index: 47
Jin-Yi Yu

Jin-Yi Yu

University of California, Irvine

H-index: 42
Song Gao

Song Gao

University of Wisconsin-Madison

H-index: 29
Jordan Ellenberg

Jordan Ellenberg

University of Wisconsin-Madison

H-index: 28
Dimitrios Giannakis

Dimitrios Giannakis

New York University

H-index: 26
R.S. Ajayamohan

R.S. Ajayamohan

New York University

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