I study the long-term evolution of solar magnetism across multiple cycles, focusing on cycle-to-cycle variability, global field diagnostics, and historical reconstructions that connect observations and modeling for space-weather relevant insights.
Solar Cycle Periodicity
I study the long-term evolution of solar magnetism across multiple cycles, focusing on cycle-to-cycle variability, global field diagnostics, and historical reconstructions that connect observations and modeling for space-weather relevant insights.
SFT / AFT Modeling
I use surface flux transport frameworks—including AFT in data-assimilation mode—to evolve photospheric magnetic fields under realistic surface flows. This supports consistent full-Sun maps, validation against synoptic products, and sensitivity studies.
Magnetic Reconnection
I investigate magnetic reconnection as a key mechanism for rapid energy release in the solar atmosphere, combining observational signatures and magnetic context to interpret transient events and connectivity changes.
Spectro-Polarimetry
I work with polarized spectral diagnostics to infer magnetic and thermodynamic properties of solar plasma, emphasizing robust inversions, careful uncertainty handling, and consistent interpretation across instruments and observing conditions.
Machine Learning
I develop ML-ready datasets and models for tasks like geometry-aware cross-calibration, systematic error characterization, and feature detection/tracking—aiming for reproducible evaluation and physically meaningful outputs.
Tool Development
I build reusable tools for data retrieval, archiving, conversion, and analysis—designed for large solar datasets. This includes automated updates, metadata-preserving storage, and visualization/diagnostic utilities that support end-to-end pipelines.