Artificial Intelligence-based Prediction of Groundwater Quantity, and It's Drivers across Parts of South Asia
I have a background in Geoscience, working at the intersection of groundwater Hydrology and data science. I am presently a senior research scholar at the Indian Institute of Technology, Kharagpur. I completed my bachelor’s degree in Geological Sciences from Jadavpur University and my master’s from IIT Kharagpur in Geology. I work on the natural and human-induced impact on groundwater resources based on artificial intelligence, machine learning, and spatiotemporal statistics. The data-driven understanding of groundwater response to major drivers could provide a blueprint for the assessment and prediction of the emerging threats to global food and water security. My research interests focus on rigorously understanding the link between groundwater, climate, and human influence, driven by observations and data in large parts (i.e., transboundary basins, countries) of South Asia. In addition, I use large spatio-temporal data and develop machine learning-based models to predict (and forecast) groundwater quantity and assess their implications for crop production and drinking water supply. It provides an understanding of how groundwater responds to natural and human-induced changes at present and in future times in South Asia’s critical aquifer systems. I also worked on the change in groundwater recharge rates in response to the land-use change using fieldwork experiment-based unsaturated zone chemical tracers in the semi-arid regions of West Bengal, India.
Doctoral Research Scholar
Department of Geology and Geophysics
Indian Institute of Technology Kharagpur India.
Phone: +91 890 228 3259
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