Abhijeet Das | Hydrology | Best Industrial Research Award Published on 03/10/202503/10/2025 by MTE Awards Dr. Abhijeet Das | Hydrology | Best Industrial Research Award Project Consultant at C. V. Raman Global University | India Dr. Abhijeet Das is a researcher specializing in Civil and Water Resource Engineering with expertise in watershed hydrology, hydrological modeling, climate change impact assessment, and geoinformatics. He earned his Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar, following an M.Tech and B.Tech in Civil Engineering from Biju Patnaik University of Technology, Rourkela. With over ten years of cumulative professional experience, he has served in academia and consultancy, including roles at IGIT Sarang, CET Bhubaneswar, and Madhu Smita Design & Engineers Studio, Kolkata. His research encompasses hydrologic extremes, water quality management, and the integration of machine learning with GIS for sustainable resource planning. Dr. Das has collaborated internationally on multiple projects across Tunisia, the USA, Oman, the UK, South Africa, Syria, and Lebanon, addressing water quality, surface water management, and remote sensing applications. He has authored 89 research documents indexed in Scopus, receiving 217 citations with an h-index of 8. His scholarly output includes numerous conference presentations, books such as Futuristic Trends in Construction Materials & Civil Engineering and Waste Water Management, and several patents on AI- and IoT-based environmental technologies. Recognized globally, Dr. Das has received awards including the “Research Excellence Award-2024” and “Asia’s Most-Promising Researcher Award” for his contributions to water resource engineering. His work reflects a strong commitment to advancing hydrological research, sustainable water management, and interdisciplinary innovation. Profile: Scopus | ORCID Feautured Publilcations Das, A. (2025). Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning analysis. Desalination and Water Treatment, 323, 1304–1319. Das, A. (2025). Geographical Information System–driven intelligent surface water quality assessment for enhanced drinking and irrigation purposes in Brahmani River, Odisha (India). Environmental Monitoring and Assessment, 197(6), 629.
Dr. Abhijeet Das is a researcher specializing in Civil and Water Resource Engineering with expertise in watershed hydrology, hydrological modeling, climate change impact assessment, and geoinformatics. He earned his Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar, following an M.Tech and B.Tech in Civil Engineering from Biju Patnaik University of Technology, Rourkela. With over ten years of cumulative professional experience, he has served in academia and consultancy, including roles at IGIT Sarang, CET Bhubaneswar, and Madhu Smita Design & Engineers Studio, Kolkata. His research encompasses hydrologic extremes, water quality management, and the integration of machine learning with GIS for sustainable resource planning. Dr. Das has collaborated internationally on multiple projects across Tunisia, the USA, Oman, the UK, South Africa, Syria, and Lebanon, addressing water quality, surface water management, and remote sensing applications. He has authored 89 research documents indexed in Scopus, receiving 217 citations with an h-index of 8. His scholarly output includes numerous conference presentations, books such as Futuristic Trends in Construction Materials & Civil Engineering and Waste Water Management, and several patents on AI- and IoT-based environmental technologies. Recognized globally, Dr. Das has received awards including the “Research Excellence Award-2024” and “Asia’s Most-Promising Researcher Award” for his contributions to water resource engineering. His work reflects a strong commitment to advancing hydrological research, sustainable water management, and interdisciplinary innovation. Profile: Scopus | ORCID Feautured Publilcations Das, A. (2025). Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning analysis. Desalination and Water Treatment, 323, 1304–1319. Das, A. (2025). Geographical Information System–driven intelligent surface water quality assessment for enhanced drinking and irrigation purposes in Brahmani River, Odisha (India). Environmental Monitoring and Assessment, 197(6), 629.