Vikas Kumar
Ph.D.
Development of a Machine Learning Framework for Real-Time Source Apportionment of Particulate Matter
Vikas Kumar completed his Bachelor of Technology in Mechanical Engineering from the National Institute of Technology, Arunachal Pradesh in 2017. After graduating, he worked as an Associate/Software Engineer at CGI ISMC Pvt. Ltd. for 3.4 years.He then worked as a research assistant at the Indian Institute of Technology Bombay for 10 months on the project “Pilot Study for Assessment of Reducing Particulate Air Pollution in Urban Areas by Using Air Cleaning System (sometimes called as Smog Tower)”. He joined the Interdisciplinary Programme (IDP) in Climate Studies at IIT Bombay as a Ph.D. student in 2021. In March 2023, he received the Schindler Ph.D. Fellowship from Schindler India Pvt. Ltd.
Research Projects
Evaluation of machine learning algorithms for calibration of low-cost sensors
This work focuses on the application of machine learning (ML) algorithms for low-cost sensor calibration and performance evaluation. This study validates the capability of ML algorithms for the calibration of LCS.
Kumar and Sahu (2021) J. Aerosol Sci
Spatiotemporal analysis of fine particulate matter for India (1980–2021) from MERRA-2 using ensemble machine learning
A machine learning (ML) framework is implemented to reconstruct PM2.5 from MERRA-2 data components, namely black carbon (BC), organic carbon (OC), dust (DUST), sea salt (SS), and sulfate (SO4) mass concentration.The long-term trend analysis shows that most of the states in India have seen a significant increase in PM2.5 concentration but states in the Indo-Gangetic plain such as Delhi, Punjab, Haryana, and Uttar Pradesh are the most polluted regions of India.
