Sujay Raghavendra Naganna

About

Dr. Sujay Raghavendra Naganna is currently an Associate Professor in the Department of Civil Engineering at Manipal Institute of Technology, Bengaluru, Karnataka, India. He specializes in Water Resources Engineering and Management. His principal research interests include estimation of streambed hydraulic properties, stream-aquifer interaction modeling, statistical and geostatistical analysis, etc. Other interests include advanced concrete technology, the built environment, and the sustainable design of architectural concrete. He is a member of professional bodies like the Soft Computing Research Society, IWRA, IAHS, ICI, IEI, IAENG etc. He has authored several research articles in various international journals and conferences. In addition to this, he has served as a reviewer for many indexed journals.

Employment

• Manipal Institute of Technology Bengaluru Associate Professor
  2024 - Present
• Manipal Institute of Technology Bengaluru Assistant Professor
  2023 - 2024
• Siddaganga Institute of Technology Assistant Professor
  2020 - 2023
• Shri Madhwa Vadiraja Institute of Technology and Management
  2018 - 2020
• National Institute of Technology Karnataka Research Scholar
  2014 - 2018

Education

• National Institute of Technology Karnataka Ph.D
  2014 - 2018
• National Institute of Technology Karnataka M.Tech (Water Resources Engineering & Management)
  2012 - 2014
• Bangalore Institute of Technology B.E (Civil Engineering)
  2007 - 2011

Projects & Funding

Projects & funding information is unavailable.

Publications (66)

• Fiber‐Modified Open‐Graded Friction Courses: Unveiling Enhanced Workability and Durability in Pavements
  Engineering Reports 2026 DOI: 10.1002/eng2.70580
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• Prediction of the Shear Strength of Steel-Fiber-Reinforced Concrete Using a Swarm Intelligence Based Extreme-Learning Machine
  International Journal of Concrete Structures and Materials 2026 DOI: 10.1186/s40069-026-00888-3
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• Improving Bridge Safety: A Spider Monkey Optimization-based ANN Model for Scour Depth Prediction
  Water Resources Management 2025 DOI: 10.1007/s11269-025-04224-4
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• Urban transportation challenges: Analysis and the mitigation strategies for road accidents, noise pollution and environmental impacts
  Open Engineering 2025 DOI: 10.1515/eng-2025-0123
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• An Investigation Into the Axial Capacity of Hot‐Rolled I‐Section Steel Columns Using Machine Learning
  Engineering Reports 2025 DOI: 10.1002/eng2.70261
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• Enhanced oily wastewater treatment: silver nanoparticles-coated graphene oxide/MXene nanocomposite membranes
  Applied Water Science 2025 DOI: 10.1007/s13201-025-02459-5
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• Analysis and Modeling of Thermogravimetric Curves of Chemically Modified Wheat Straw Filler-Based Biocomposites Using Machine Learning Techniques
  Journal of Composites Science 2025 DOI: 10.3390/jcs9050221
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• Axial Strength of Short Hot-Rolled Steel Equal Angle Members: Experimental Analysis, Numerical, and Machine Learning Modeling
  Journal of The Institution of Engineers (India): Series A 2025 DOI: 10.1007/s40030-025-00907-8
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• Prediction of scour depth around bridge abutments using ensemble machine learning models
  Neural Computing and Applications 2024 DOI: 10.1007/s00521-023-09109-4
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• Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data
  IEEE Access 2024 DOI: 10.1109/ACCESS.2024.3502361
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