About Me
Hailing from a small village in Silchar, Assam, my journey into the world of hydrology is driven by a deep-seated curiosity about our planet's most vital resource: water. As a PhD Scholar at the Indian Institute of Technology, Mandi, I specialize in cutting-edge AI-Hydrology, leveraging artificial intelligence and machine learning to decipher the complex signatures of climate change.
My research focuses on developing robust deep learning models to better predict extreme hydrological events and safeguard our future. I am passionate about collaborating on innovative research that bridges the gap between advanced data science and pressing environmental challenges.
Research Focus
- AI-Driven Hydrological Modeling
- Climate Change Impact Assessment
- Extreme Event Prediction
- Deep Learning Applications in Environmental Science
Research Competencies
Professional Experience
PhD Research Scholar
Indian Institute of Technology Mandi
Research Focus: AI-Driven Hydrological Modeling
Junior Research Fellow
National Institute of Hydrology, CIHRC Bhopal
Research Focus: Hydrological Forecasting & Extreme Event Analysis
Academic Journey
PhD in Hydrology
Indian Institute of Technology, Mandi
Research Focus: AI-Driven Hydrological Modeling
Master of Technology
Maulana Azad National Institute of Technology (MANIT), Bhopal
Specialization: Water Resource Engineering
Bachelor of Technology
Maulana Abul Kalam Azad University of Technology, Kolkata
Major: Civil Engineering
Publications
Journal Articles
From Gauged to Ungauged: Large-Scale Deep Learning Rainfall-Runoff Modelling for Reliable Streamflow Estimation in India's Diverse Basins
Authorea. doi:10.22541/au.173801002.25089607/v2
Performance evaluation of ML techniques in hydrologic studies: Comparing streamflow simulated by SWAT, GR4J, and state-of-the-art ML-based models
Journal of Earth System Science, 133 (136) doi:10.1007/s12040-024-02340-0
Assessment of streamflow in the ungauged basin by using physical similarity approach
Arabian Journal of Geosciences, 16 (672) doi:10.1007/s12517-023-11786-3
Book Chapters
Assessing the Impacts of Climate Change on Hydroclimatic Regimes in Beas River Basin
In: Nanda, A., Gupta, P.K., Gupta, V., Jha, P.K., Dubey, S.K. (eds) Navigating the Nexus. Water Science and Technology Library, vol 102. Springer, Cham. doi:10.1007/978-3-031-76532-2_14
Performance Evaluation of Lumped Conceptual Rainfall-Runoff Genie Rural (GR) Hydrological Models for Streamflow Simulation
In: Timbadiya, P.V., Patel, P.L., Singh, V.P., Sharma, P.J. (eds) Hydrology and Hydrologic Modelling. HYDRO 2021. Lecture Notes in Civil Engineering, vol 312. Springer, Singapore. doi:10.1007/978-981-19-9147-9_22
Nonstationary Flood Frequency Analysis: Review of Methods and Models
In: River, Sediment and Hydrological Extremes: Causes, Impacts, and Management, Disaster Resilience and Green Growth. Springer, Singapore. doi:10.1007/978-981-99-4811-6_15
Conference Papers
Comparative Analysis of Satellite and Gauge-Based Precipitation Data for Landslide Risk Assessment in Himalayas
EGU General Assembly 2025, Vienna, Austria. doi:10.5194/egusphere-egu25-19794
Analysing precipitation extremes in South Asia Using Expert Team on Climate Change Detection and Indices (ETCCDI) Indices
AGU Fall Meeting Abstracts (Vol. 2024, pp. H05-06)
Will Mamba Rise or Fall? A Real-World Test of Its Rainfall-Runoff Modelling in Indian Basins
AGU Fall Meeting Abstracts (Vol. 2024, pp. H02-28)
Trend Analysis and Forecasting of Streamflow using RF and LSTM Models
EGU General Assembly 2023 doi:10.5194/egusphere-egu23-10952