DV
Dr. JERRIN JOY VARUGHESE
Dayananda Sagar University, Vellore Institute of Technology University, Anna University, Chennai, St. Thomas College of Engineering & Technology, Mahatma Gandhi University
Employment
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Dayananda Sagar University Assistant Professor2026 - Present
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Vellore Institute of Technology University DOCTORAL RESEARCHER CUM TRA2021 - 2026
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St. Thomas College of Engineering & Technology ASSISTANT PROFESSOR2010 - 2021
Education
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Vellore Institute of Technology University Doctor of Philosophy (Ph.D)2021 - 2026
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Anna University, Chennai MASTER OF ENGINEERING IN CAD/CAM2012 - 2014
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Mahatma Gandhi University BACHELOR OF TECHNOLOGY IN MECHANICAL ENGINEERING2005 - 2009
Projects & Funding
Projects & funding information is unavailable.
Publications (8)
- Investigation on the effect of fibre modifications with nanoparticles on solid particle erosion wear response of advanced epoxy - carbon fibre composites Save
- Solvent‐Assisted Dispersion of Multiwalled Carbon Nanotubes in Epoxy‐Based Glass Fiber‐Reinforced Polymer Composites: Experimental Investigation, Micromechanical Modeling, and Machine Learning Prediction Save
- Molybdenum Disulfide‐Functionalized Multiwalled Carbon Nanotubes Based Epoxy Coating on Epoxy/Carbon Fiber Laminates for Improved Erosion Resistance Save
- Synergistic Enhancement of Mechanical and Interfacial Properties in Carbon Fiber Epoxy Nanocomposites via Dual Functionalization of Fiber and Exfoliated Hexagonal Boron Nitride Nanosheets Save
- Epoxy vitrimer based nanocomposites for EMI shielding: Integrating reprocessability, self-healing, and machine learning predictions Save
- Predictive modelling of hexagonal boron nitride nanosheets yield through machine and deep learning: An ultrasonic exfoliation parametric evaluation Save
- Influence of silane and polyethylene glycol functionalization of boron nitride nanosheets on mechanical and thermal properties of epoxy nanocomposites: Machine and deep learning forecasting Save
- Investigation on enhancement of filler dispersion and prediction of mechanical behavior of hexagonal boron nitride/epoxy nanocomposites through machine learning and deep learning models Save