Chandan Kapil works in the Remote Radar Department as Postdoctoral researcher, where her research focuses on understanding ionospheric irregularities and scintillations in equatorial and low-latitude regions. She completed her M.Sc. (2018) in Physics and Electronics from Panjab University, India and subsequently earned her Ph.D. (2024) in Physics from Indian Institute of Geomagnetism, India.

Her research has primarily explored how space weather events, including geomagnetic disturbances and electric field variations, trigger and influence ionospheric irregularities, as well as the underlying seeding mechanisms responsible for their development. A significant aspect of her work involves investigating super plasma bubbles, which represent an extreme manifestation of ionospheric instability characterized by highly complex and nonlinear dynamics.

Beyond ionospheric physics, she is extensively engaged in data-driven research approaches. Her interests include applying machine learning techniques to detect and predict ionospheric disturbances such as Total Electron Content (TEC) depletions and scintillations associated with equatorial plasma bubbles. In parallel, she investigates hybrid machine learning frameworks for radar target classification, integrating domain-specific signal features with deep learning models to improve classification performance.

Looking ahead, her research aims to bridge physics-based understanding with advanced machine learning techniques to enhance the monitoring, modeling, and prediction of ionospheric and atmospheric phenomena.

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