Research

RESEARCH INTERESTS

Data-driven Stochastic Modeling and Prediction for Earth and Space Sciences, Theory-Informed Machine Learning, Advanced Spectral Methods and Time Series Analysis,Nonlinear Dynamical Systems, Data Assimilation. 

Summary bibliometrics (December 2025)

Web of Science: 53 indexed publications, h-index = 27

Curriculum Vitae

• WoS Profile

• ORCID

Presentation at Kavli Institute for Theoretical Physics Program on “Machine Learning and the Physics of Climate“

REAL-TIME CLIMATE PREDICTION

1. ARCTIC SEA ICE
2. ENSO

PROJECTS 

1. •NSF: Collaborative Research: GEM–Towards Developing Physics-informed Subgrid Models for Geospace MagnetoHydroDynamics (MHD) Simulations, Lead PI, 2024-2026
2. •NSF: Collaborative Research: Advancing predictive understanding of summertime Arctic sea ice cover, Lead PI, 2025-2027
3. •NSF: EAGER Machine Learning and Data Assimilation for Discovery of Generalized Fokker-Planck Equation for Radiation Belt Modeling, PI, 2022 – 2024
4. •NSFGEO-NERC: Multiscale Stochastic Modeling and Analysis of the Ocean Circulation, Lead PI, 2017 – 2020
5. •NSF: Collaborative Research: EaSM 2: Stochastic Simulation and Decadal Prediction of Large-Scale Climate, Lead PI, 2013 – 2017
6. •ONR-MURI: Extended-Range Environmental Prediction Using Low-Dimensional Stochastic-Dynamic Models: A Data-driven Approach, co-PI, 2012 – 2017
7. •UC: UCLA-LANL RADIATION BELTS REANALYSIS PROJECT, co-I, 2009 – 2012
8. •NSF: EAGER Direct Assimilation of Low-altitude Magnetic Perturbations in a Global Magnetosphere Model, co-PI, 2013 – 2016
9. •NSF: CLIMATE SENSITIVITY, STOCHASTIC MODELS AND GCM-EASM OPTIMIZATION, co-PI,  2011 – 2014
10. •NSF: GAP FILLING OF SOLAR WIND DATA BY SINGULAR SPECTRUM ANALYSIS, PI, 2011-2013

SOFTWARE

• DATA-ADAPTIVE DECOMPOSITION AND STOCHASTIC MODELING

• SINGULAR SPECTRUM ANALYSIS AND SSA-MTM TOOLKIT 

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