Dr. Abhijeet Das: Research Consultant at C.V. Raman Global University (CGU), Bhubaneswar, Odisha, India
Dr. Abhijeet Das is a highly skilled and passionate water resource engineer with a comprehensive background in civil engineering, specializing in water quality management, hydrological modeling, and the application of emerging technologies like machine learning and GIS. Currently holding a Ph.D. in Water Resource Engineering from C.V. Raman Global University, Dr. Das has established himself as an expert in assessing and managing surface water resources, particularly in the context of climate change. His interdisciplinary approach combines environmental engineering with advanced data analytics to address the complexities of water scarcity, pollution, and sustainability. Throughout his career, he has collaborated on multiple international projects with prestigious institutions in Europe, the United States, the Middle East, and Africa. Dr. Das aims to make a lasting impact on global water resource management and environmental sustainability through innovative solutions and research-driven methodologies.
Online Profiles
Citations: 196 citations from 98 documents
h-index: 7 (h-index is a measure of both the productivity and citation impact of the author’s publications)
Education
Ph.D. in Water Resource Engineering – C.V. Raman Global University, Bhubaneswar (2024), CGPA: 9.38
Dr. Das’s doctoral research focused on advanced hydrological modeling techniques and their application to sustainable water resource management. He employed machine learning algorithms, GIS, and remote sensing to address challenges in flood control, drought management, and water quality monitoring in India.M.Tech in Water Resource Engineering – Biju Patnaik University of Technology, Rourkela (2017), CGPA: 9.32
During his M.Tech studies, Dr. Das worked on integrating machine learning models with traditional hydrological modeling tools to predict water quality in Indian river basins, paving the way for his future research in the use of AI in water resources.B.Tech in Civil Engineering – Biju Patnaik University of Technology, Rourkela (2015), CGPA: 8.55
His undergraduate degree laid the foundation for his engineering knowledge, with a strong focus on structural and environmental engineering, providing him with a deep understanding of civil engineering principles.Intermediate/+2 Science – Stewart Science College, Cuttack (2011), 70.5%
Matriculation/10th – S.C.B. Medical Public School, Cuttack (2009), 79.86%
Research Focus
Dr. Das’s research primarily focuses on water resource engineering, emphasizing hydrological modeling, water quality assessment, and climate change impacts. He is particularly interested in understanding the relationship between water availability and human activities, as well as exploring the potential of machine learning, remote sensing, and GIS to improve water resource management. His work on the Food-Energy-Water (FEW) Nexus and optimization of water quality using multi-criteria decision-making approaches has significantly contributed to improving resource sustainability. Additionally, his innovative work in the application of artificial neural networks (ANN), fuzzy logic, and other AI-based approaches in water quality management has made him a leading researcher in this domain.
Experience
Dr. Das has accumulated over a decade of experience in both academic and practical fields, blending theoretical knowledge with real-world applications. His career spans multiple roles, including:
Project Consultant at Madhu Smita Design & Engineers Studio (2022–2025) – Working on projects related to water resource management, optimization of water quality indices (WQI), and GIS-based hydrological modeling.
Assistant Professor in Civil Engineering at IGIT Sarang and CET Bhubaneswar (2017–2022) – Where he taught courses in environmental and water resources engineering and mentored undergraduate and postgraduate students.
Intern at A.B. Consultancy Private Ltd. (2015–2017) – Gained hands-on experience in hydrological analysis and water resource management in Odisha.
In addition to his academic and consulting roles, Dr. Das has also been involved in several collaborative projects with international organizations, including projects in Saudi Arabia, Oman, Tunisia, and the United States, focusing on advanced water quality assessment and flood management using AI and GIS technologies.
Research Timeline & Activities
Dr. Das’s research journey has spanned several key projects and activities, including:
June 2024 – December 2024: Project Assistant at Eremology and Combatting Desertification Laboratory, IRA Medninine, Tunisia, focusing on wastewater resources and salinity predictions in Saudi Arabia.
January 2025 – April 2025: GIS Consultant for the “Surface Water Management and Water Quality Index Optimization” project at Texas Christian University, USA.
2024–2025: Collaborative research on water quality contamination detection and management through remote sensing and machine learning techniques, working with the University of Technology and Applied Sciences, Oman.
2019–2024: Involvement in projects such as surface water potential zone identification in the UK and integration of geospatial algorithms for surface water characterization in South Africa.
These experiences have expanded his research scope across global contexts, offering practical solutions for water sustainability and quality control.
Awards & Honors
Dr. Das’s contributions to water resource engineering and environmental science have been recognized with numerous awards, including:
Best Young Researcher Award at the International Conference on Sustainable Growth (2024) for his innovative work in GIS and machine learning for water quality assessment.
Research Excellence Award (2024) for his work on machine learning algorithms for water potential zone identification, awarded by the New Research and Innovation Society (NEWRAINS).
Inspiring Educator Award (2024) for his excellence in teaching and research in water resource engineering.
Asia’s Most Promising Researcher Award (2024) by the Asia Research Awards, recognizing his contributions to sustainable water resource management.
Best Paper Awards at various international conferences such as ISDMME-2023, ICSEEGT-2023, and RASTEMS-2023 for his work on water quality and pollution source assessment in river basins across India.
Dr. Das has also been invited as a speaker at several prestigious global conferences, including the 4th Global Summit on Earth Science and Climate Change (2025, Berlin) and GeoEarth-2025 (Berlin).
Recent Noted Publications
1. An Optimization-Based Framework for Water Quality Assessment and Pollution Source Apportionment
Journal: Discover Environment (2025)
Focus: An optimization-based framework for assessing water quality and identifying pollution sources, utilizing GIS and machine learning techniques.
2. Reimagining Biofiltration for Sustainable Industrial Wastewater Treatment
Journal: Discover Environment (2025)
Focus: A review article on biofiltration as a sustainable method for industrial wastewater treatment.
3. A Data-Driven Approach Utilizing Machine Learning and GIS-Based Time Series Analysis with Data Augmentation for Water Quality Assessment in Mahanadi River Basin, Odisha, India
Journal: Discover Sustainability (2025)
Focus: A study on water quality assessment in the Mahanadi River Basin using machine learning, GIS, and time series analysis.
Citations: 2
4. Evaluation and Prediction of Surface Water Quality Status for Drinking Purposes Using Integrated Water Quality Indices, GIS Approaches, and Machine Learning Techniques
Journal: Desalination and Water Treatment (2025)
Focus: This article discusses the use of integrated water quality indices, GIS, and machine learning to assess water quality for drinking purposes.
Citations: 1
5. Bioplastics: A Sustainable Alternative or a Hidden Microplastic Threat?
Journal: Innovative Infrastructure Solutions (2025)
Focus: An examination of bioplastics, considering whether they are a sustainable alternative or pose a hidden risk in the form of microplastics.
Strength for the Water Conservation Award
1. Innovative Use of AI and Machine Learning for Water Management
Dr. Das has pioneered the application of machine learning algorithms and GIS-based hydrological modeling in water quality management. His use of AI for tasks like water quality assessment, flood control, and drought management is not only innovative but also critical in the context of water conservation. These technologies enhance the precision of water resource management, helping to optimize the use of available water, identify contamination sources, and predict water stress areas before they become critical.
2. Interdisciplinary Approach to Water Resource Sustainability
Dr. Das’s interdisciplinary approach combines environmental engineering with advanced data analytics, effectively addressing the complex challenges of water scarcity, pollution, and climate change. His research on the Food-Energy-Water (FEW) Nexus and optimization of water quality through multi-criteria decision-making approaches has resulted in sustainable solutions for water conservation that integrate water, energy, and food systems.
3. International Collaboration and Global Impact
Dr. Das has worked on international water conservation projects across Europe, the United States, the Middle East, and Africa, focusing on water quality assessment, flood management, and sustainable resource use. His collaborations with institutions such as the University of Technology and Applied Sciences in Oman, Texas Christian University in the USA, and others in Saudi Arabia and Tunisia contribute to global knowledge sharing, helping improve water management practices worldwide.
4. Commitment to Advancing Water Resource Education
As an educator and mentor, Dr. Das has trained undergraduate and postgraduate students in water resources engineering, fostering the next generation of water conservation experts. His recognition with awards like the Inspiring Educator Award showcases his impact in nurturing future leaders in the field of sustainable water management.
5. Practical, Data-Driven Solutions for Local Water Issues
Dr. Das’s research on the Mahanadi River Basin in Odisha and other local water bodies highlights his focus on region-specific water challenges. His data-driven approach using time series analysis, GIS, and machine learning for water quality assessment and prediction is crucial for areas struggling with water pollution, contamination, and resource scarcity. His work directly benefits local communities by providing evidence-based recommendations for water conservation.
6. Track Record of Publications and Research Excellence
With over 196 citations and impactful publications in high-ranking journals, Dr. Das’s work is well-recognized in the academic community. His research on sustainable water resource management is aligned with the goals of many water conservation awards, making him eligible based on his contributions to the field.