Harsh Mathur is a Ph.D. candidate in Solar Physics at the Indian Institute of Astrophysics. His thesis is about the inference of the stratification of magnetic fields in the Solar atmosphere using high spatial and spectral resolution observations. He has utilized non-LTE inversion codes and numerical simulations to interpret the observations. He has also utilized machine learning algorithms in solar data analysis, such as k-means clustering, to detect features in imaging and spectro-polarimetric data efficiently. Additionally, He has trained supervised deep learning models to map the real observables to the 3D MHD atmospheres to interpret the observations faster compared to the utilization of the non-LTE radiative transfer codes. Harsh is skilled in Python scripting, C/C++, data reduction and statistical analysis, data visualization, and preparing detailed scientific reports and papers. During his Ph.D., he was involved in many works, resulting in 5 first-author and 1 third-author publication in reputed peer-reviewed journals in the field of Astronomy.