We work on exploring the redshifted HI 21 cm signal from the Dark Ages (z ≈ 30–100), Cosmic Dawn (z ≈ 15–6) and the Epoch of Reionization (z ≈ 6–7). This faint radio emission shows brightness fluctuations of order 10 mK and carries a direct imprint of the first stars, early galaxies and the surrounding intergalactic medium. By mapping these fluctuations we hope to trace how the first objects heated and ionized the cosmic gas, reveal the timing of key transitions and constrain fundamental cosmological parameters. We use low-frequency radio interferometers such as uGMRT, HERA and SKA1-Low, relying on aperture synthesis, tight gain calibration and careful beam modeling. Our recent simulations demonstrate that at least 1500 hours of integration and post-calibration gain errors below 0.05 percent are needed to recover the full percolation history of ionized bubbles. In the lab we develop and test optimal thresholding techniques for foreground removal, model ionospheric distortions and beam chromaticity, and build end-to-end Python pipelines for calibration, imaging and statistical analysis. These tools will be vital for extracting both the power spectrum and imaging information from upcoming low-frequency surveys.

We work on exploring galaxy clusters, the most massive gravitationally bound systems in the universe, with typical masses around 100 trillion times that of the Sun. When clusters merge, they generate shocks and turbulence that heat the intracluster medium, accelerate particles to high energies, and amplify magnetic fields. This activity produces X-ray and radio emission, which we study to understand how these extreme environments evolve. We focus on diffuse radio sources like halos, relics, mini-halos, and phoenixes, each with distinct origins and morphologies. These emissions trace the movement of relativistic particles and reveal the structure of magnetic fields in clusters. However, many open questions remain, including how short-lived electrons are continuously re-accelerated, why only some mergers produce radio features, and how magnetic fields form and grow. Using data from low-frequency surveys like LOFAR, we aim to better understand the link between radio power, cluster mass, and the physics of large-scale structure formation.

We specialize in Ionosphere research, focusing on ionospheric physics and its dynamic behavior. Our work includes studying the effects of geomagnetic storms on ionospheric conditions, particularly their influence on communication and navigation systems. We analyze scintillation phenomena, investigating rapid signal fluctuations caused by ionospheric irregularities. A key area of our research is understanding plasma bubble characteristics: regions of low-density plasma that disrupt signal transmission. Additionally, we employ ionospheric tomography techniques to reconstruct three-dimensional electron density structures, providing detailed insights into spatial and temporal ionospheric variations. Our goal is to enhance space weather prediction and improve technological resilience.

We work on building innovative, low-cost instrumentation for astronomy and space engineering to make advanced research accessible and practical. One of our key efforts is the IIT Indore Radio Interferometer (IIRI), a campus-based facility for hands-on radio observations, which brings research and training out of remote observatories and into the academic environment. Developing this system involved challenges such as RFI mitigation, synchronization, and mechanical stability. We are also advancing a UAV-based antenna characterization platform that uses drones to map antenna radiation patterns in the field, and this has applications in both astronomical calibration and infrastructure inspection. Another major project is a low-cost Attitude Determination and Control System (ADCS) testing facility, designed to help test satellite orientation control mechanisms affordably and flexibly. In parallel, we’ve contributed to education outreach through astronomy and tinkering labs across schools in Haryana, inspiring students by giving them tools to observe the sky and explore science hands-on.

We work on advancing radio astronomy and cosmology by integrating observational methods with modern data science. Our primary research targets the early universe, focusing on the Cosmic Dawn and the Epoch of Reionization, through the study of the redshifted 21-cm hydrogen signal. We use data from the GMRT and are actively preparing for science with the upcoming SKA, which will offer unprecedented sensitivity and resolution. Alongside cosmology, we apply machine learning and computer vision techniques to astrophysical and heliophysical data, including automated detection of coronal holes, space weather forecasting, and real-time analysis pipelines. Our group addresses key challenges in low-frequency radio astronomy, such as foreground subtraction, calibration errors, and ionospheric distortions. We develop robust algorithms to enhance signal recovery and improve parameter estimation from noisy, high-dimensional data. Recently, we’ve expanded into quantum machine learning, exploring its potential for cosmological model fitting, image classification, and large-scale data processing. Our goal is to build adaptable, high-performance data analysis frameworks that support next-generation telescopes and deepen our understanding of the distant universe and near-Earth space.

Our work focuses on understanding the evolution and formation of galaxies; knowledge of the evolution-driving processes is required. The multiwavelength approach allows us to probe, classify, and determine the accurate age of the objects. We focus on Star Formation Rate (SFR) to understand the evolution of the galaxies. We generate Spectral Energy Distributions (SEDs) to get the global star formation rate using data from infrared to ultraviolet data. We use radio data from uGMRT to understand the properties of populations of star formation galaxies (SFGs), active galactic nuclei (AGNs), and radio galaxies. We separate the AGNs from SFGs using infrared and x-ray data. We also use a combination of radio and x ray data to find new galaxy clusters and determine their properties

We work on understanding the Sun and its interaction with planetary atmospheres using the radio occultation technique, which measures changes in signal as a spacecraft passes behind a planet. By tracking signals from the Indian Mars Orbiter Mission (Mangalyaan) and Japan’s Akatsuki probe, we map solar wind density, speed, and temperature as they sweep past Mars and Venus. We also analyze data from NASA’s MAVEN, Mars Express (MEX), Mars Reconnaissance Orbiter (MRO) and Mars Global Surveyor (MGS) to see how bursts of solar activity strip away ions from Mars, a planet without a global magnetic field. In contrast, Venus develops an induced magnetosphere through its dense atmosphere’s interaction with the same solar wind. This comparative approach helps us reveal fundamental processes that shape planetary climates and atmospheres.