Mr. Aditya Kumar Singh: Research Scholar at National Institute of Technology Patna, India
Aditya Kumar Singh is a dedicated Ph.D. Research Scholar in Water Resource Engineering at the National Institute of Technology Patna, with over five years of experience in flood modeling, satellite data analysis, and climate-resilient water management. His academic journey reflects a strong commitment to addressing real-world hydrological challenges using scientific approaches, advanced analytics, and modern geospatial technologies. Passionate about integrating machine learning and remote sensing into hydrological systems, his work aims to contribute toward sustainable and adaptive water resource planning in the face of growing climate variability and extreme events.
Online Profiles
Aditya Kumar Singh’s research contributions have been cited 16 times in scholarly literature, reflecting growing recognition in the water resources and hydrology community. His current h-index is 2, indicating at least two publications have been cited multiple times.
Education
Aditya is currently pursuing a Ph.D. in Water Resource Engineering at NIT Patna (since 2022), where he holds a current CGPA of 9.31/10. He completed his M.Tech in the same specialization from NIT Patna in 2021, graduating with a stellar CGPA of 9.61/10. His foundational degree is a B.Tech in Civil Engineering from R.K. University, completed in 2015 with a CGPA of 7.28/10. Throughout his academic career, he has consistently demonstrated academic excellence and a research-driven mindset, laying a strong foundation for his expertise in hydrological systems and environmental engineering.
Research Focus
His core research focuses on developing an integrated framework for real-time flood prediction by combining satellite-based precipitation products with machine learning algorithms, particularly in the flood-prone Kosi River Basin in India. The work encompasses rainfall-runoff modeling, flood risk mapping, uncertainty assessment of satellite datasets, and land use/land cover dynamics analysis. By leveraging tools like R, Python, ArcGIS, and hydrological models, his research contributes to more accurate and timely flood forecasting systems that can aid disaster management authorities and policymakers in minimizing socio-economic losses due to climate-induced flooding.
Experience
Aditya has a diverse professional background encompassing both academia and industry. As a Teaching Assistant at NIT Patna, he has mentored students in undergraduate and postgraduate laboratory courses including Fluid Mechanics, Water Supply and Wastewater Engineering, Advanced Hydrology, and Groundwater Engineering. Prior to his academic pursuits, he worked as a Site Engineer with RKEC Projects Pvt. Ltd. at the Adani Hazira Port from October 2015 to January 2018, contributing to the construction of a Multi-Purpose Berth. His combined academic and field experience enriches his practical understanding of civil infrastructure and environmental systems.
Research Timeline & Activities
Aditya’s research journey began during his M.Tech with a project focused on flood detection using Sentinel-1A SAR imagery, which led to a broader exploration of satellite-based hydrology. Since 2022, his Ph.D. work has expanded into machine learning for flood forecasting, land use change modeling, and rainfall dataset evaluation. His active participation in workshops and training programs—such as ISRO’s flood management training, NIH Roorkee’s inland water conservation course, and SERB’s advanced R programming workshop—has helped him build strong technical skills. He has also presented at international conferences including EWRA and Hydro-2024, with several high-impact journal publications to his name.
Awards & Honors
Aditya has received several prestigious accolades in recognition of his academic and research excellence. Most notably, he was awarded a Travel Grant by the Anusandhan National Research Foundation (ANRF), Government of India, in 2025 to present his research at an international conference in Palermo, Italy. He is a three-time qualifier of the Graduate Aptitude Test in Engineering (GATE) (2017, 2018, and 2019), and has been the recipient of the Ministry of Education (MoE) scholarship throughout his M.Tech and Ph.D. studies. These achievements reflect his consistency, dedication, and academic caliber.
Top Noted Publication
Among his multiple SCIE-indexed journal publications, one of the most significant is titled “From Bias to Forecast: Advancing Satellite Rainfall Accuracy and Flood Prediction with Transformer Modeling in the Kosi Basin (India)”, published in Stochastic Environmental Research and Risk Assessment (Q1, 2025). This study presents a novel framework that integrates bias-corrected satellite rainfall data with a Transformer-based deep learning model for improved flood prediction. The paper is notable for its methodological innovation, regional relevance, and practical implications in enhancing early warning systems in flood-prone regions like the Kosi Basin.
Singh, A.K., Roshni, T., & Singh, V. (2024). Evaluating the association of flood mapping with land use and land cover patterns in the Kosi River Basin (India). Acta Geophysica, 72(6), 4649–4669. [Citations: 9]
Singh, A.K., & Singh, V. (2024). Assessing the accuracy and reliability of satellite-derived precipitation products in the Kosi River Basin (India). Environmental Monitoring and Assessment, 196(7), 671. [Citations: 7]
Singh, A.K., & Singh, V. (2025). Advancing real-time flood prediction in the Kosi River Basin (India): A machine learning framework leveraging satellite precipitation products. Theoretical and Applied Climatology, 156(9), 496.
Strength for the Best Innovator Award
Pioneering Transformer-Based Flood Prediction Models
Aditya Kumar Singh has demonstrated exceptional innovation by integrating Transformer-based deep learning models with satellite rainfall data to significantly improve flood prediction accuracy in the Kosi River Basin. His work addresses key challenges in bias correction and real-time forecasting, advancing early warning systems for flood-prone regions and setting a new benchmark in hydrological modeling.
Real-Time Flood Forecasting through Multi-Source Data Fusion
Aditya’s development of an integrated framework combining satellite precipitation products and machine learning algorithms represents a major leap in flood risk management. By effectively managing uncertainties in satellite datasets and enhancing rainfall-runoff modeling, he delivers timely and reliable flood forecasts that aid disaster preparedness and reduce socio-economic losses.
Innovative Use of Remote Sensing for Flood and Land Use Analysis
By leveraging Sentinel-1A SAR imagery and analyzing land use/land cover dynamics, Aditya has innovatively mapped flood extents and correlated them with environmental changes. This approach not only improves understanding of flood behavior but also supports adaptive water resource planning by identifying vulnerable regions based on changing landscape patterns.
Expertise in Hydrological Modeling with Advanced Programming and GIS
Aditya’s proficiency in R, Python, ArcGIS, and hydrological modeling tools has enabled him to create robust frameworks for climate-resilient water management. His innovative application of these tools to assess satellite data uncertainty and simulate hydrological processes under climate variability contributes to more sustainable and adaptive water resource planning.
Bridging Research and Practical Engineering for Real-World Impact
Combining his academic excellence with industry experience as a Site Engineer, Aditya effectively bridges theoretical research and practical infrastructure solutions. His interdisciplinary approach enhances the relevance and applicability of his innovations in flood management and environmental engineering, ensuring impactful contributions to both science and society.