RAJEEV KUMAR GUPTA
Dayananda Sagar University, National Metallurgical Laboratory, National Institute of Foundry and Forge Technology, BEC Ltd.
0000-0003-2859-2389
About
Dr. Rajeev Kumar Gupta is a researcher and academician in the field of Mechanical Engineering, specializing in Tribology, Machine Design, and Biomedical Implant Wear Analysis. He completed his Ph.D. from the Indian Institute of Science (IISc) Bangalore, where his research focused on understanding the influence of surface topography, roughness, and lubrication conditions on the wear behavior and debris morphology of polymeric biomedical implant materials. His doctoral work involved the design and development of a tribometer, preparation and characterization of varied surface textures, and experimental evaluation of friction, wear, and debris characteristics- providing significant insights into implant material behavior relevant to artificial knee and hip joints.
Dr. Gupta also holds an M.Tech. from NIT Rourkela, where he studied the creep-fatigue interaction and life prediction of high-temperature martensitic steels. His early professional training in foundry and manufacturing strengthened his practical understanding of material processing and industrial component development.
He is currently serving as an Assistant Professor in the Department of Mechanical Engineering at Dayananda Sagar University (DSU), Bengaluru, contributing to both teaching and research. He teaches a range of subjects including Engineering Mechanics, Fatigue and Fracture Mechanics, Finite Element Method, Machine Design, Rapid Manufacturing, and Engineering Drawing & Design Thinking.
With over five years of combined academic, research, and industry experience, Dr. Gupta has guided students from leading institutes such as IITs and NITs and has collaborated with research organizations including CSIR-NML. His work has resulted in several publications in peer-reviewed international journals and conferences, covering topics such as surface wear, corrosion-fatigue behavior of superalloys, and the tribological behavior of polymer composites. He is also co-inventor of a patented tribometer designed for boundary lubrication studies.
Dr. Gupta possesses strong technical skills in mechanical testing, material characterization, and simulation. His expertise spans tensile and fatigue testing, fracture toughness evaluation, surface characterization techniques such as SEM, AFM, 3D Profilometry, and DSC, as well as software tools including CATIA, SolidWorks, Python, MATLAB, and Abaqus. His academic achievements
include securing top ranks in competitive examinations such as BCECE and GATE and being awarded a CSIR fellowship.
Through his background in advanced materials, tribology, and computational analysis, Dr. Gupta continues to contribute toward innovative solutions in mechanical engineering and biomedical implant materials, with a focus on improving real-world performance and reliability.
Employment
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Dayananda Sagar University Assistant Professor2023 - Present
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National Metallurgical Laboratory Senior Research Fellow2014 - 2014
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National Metallurgical Laboratory Junior Research Fellow2011 - 2014
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BEC Ltd. Graduate Engineer Trainee (GET)2009 - 2010
Education
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National Institute of Foundry and Forge Technology B. Tech2005 - 2009
Projects & Funding
Projects & funding information is unavailable.
Publications (16)
- Heat treatment-driven optimization of Al7075-AlN composites: A synergistic approach using experiments, statistics, and machine learning Save
- Directional Surface Roughness Parameters as Predictors of Polymer Wear Debris Size Under Dry and Lubricated Conditions: An Experimental and Machine Learning Approach Save
- Deep learning based optimization of biodiesel production from high free fatty acid milk scum oil using synthetic process data and ablation analysis Save
- Mixed-mode(I/II) fracture behaviour and criterion-based analysis of banana fiber reinforced epoxy composites using asymmetric SCB specimens Save
- Machine Learning-Enabled Analysis of Surface Texture Orientation Effects on Wear Debris Morphology and Tribological Performance of High-Density Polyethene (HDPE) Save
- Experimental and machine learning-based analysis of wear behaviour in CNT and titanium reinforced copper matrix composites Save
- Experimental and Statistical Approach to the Evaluation of Chill Cast LM13/Zircon/Carbon Hybrid Composites’ Wear Characteristics Save
- Impact of Wear Parameters and Heat Treatment on the Wear Rate of Aluminum Alloy/Al Nitride Composite: An Experimental Approach Save
- Advancing biodiesel production from milk scum oil: a deep learning and synthetic data approach with ablation study for process optimization Save
- Effect of Tungsten Carbide Composites on Al6061 Using Powder Metallurgy Technique: Experimental and Machine Learning Approach Save