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PhD Research Scholar Department of Astronomy Astrophysics and Space Engineering, Indian Institute of Technology Indore, Madhya Pradesh, India
Email: phd2201121012@iiti.ac.in
Address: POD 1E- 402, Indian Institute of Technology Indore, Madhya Pradesh India
Research Group: SIGMA Research Lab – DAASE IIT Indore

About
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Vaibhav Tyagi received his Bachelor’s degree in Physics from the University of Delhi, India, in 2020 and a Master’s degree in Physics from the Indian Institute of Technology Palakkad in 2022. He is currently pursuing his doctoral studies at the Department of Astronomy, Astrophysics and Space Engineering (DAASE) at the Indian Institute of Technology Indore. His research focuses on Doppler Weather Radar-based wind field retrieval, quality control of radar observations, algorithm development and understanding the role of near-surface to low-level winds in the genesis of organized mesoscale systems. He has gained international research experience as a Visiting Research Scholar at Colorado State University, USA, and as a Visiting Scientist at the Royal Netherlands Meteorological Institute (KNMI), Netherlands, focusing on radar signal processing, wind retrieval, and rain-induced effects in scatterometer wind observations during his Ph.D. He has published several peer-reviewed articles and has received multiple recognitions including the IEEE AP-S Fellowship (2025-26), various travel grants and Best Student Paper Awards at major radar meteorology conferences. He is an active member of the IEEE Geoscience and Remote Sensing Society (GRSS) and the IEEE Antennas and Propagation Society (AP-S). He has served in several volunteer roles, including as Chair of the IEEE GRSS Student Branch Chapter at IIT Indore, actively contributing to professional development and scientific engagement within the remote sensing community.
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Research Interests
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My primary research interest lies in atmospheric remote sensing and radar meteorology, with a focus on weather radar observations, remote sensing of precipitation, algorithm development and radar signal processing. My current research interest is in the development and implementation of statistical and machine learning techniques for improving data quality and retrieving atmospheric wind fields from ground-based and satellite observations.
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