SS
Satheeskumar S
SAVEETHA ENGINEERING COLLEGE, Institute of Aeronautical Engineering, ANNA UNIVERSITY, RAJA COLLEGE OF ENGINEERING AND TECHNOLOGY, CMR Group of institutions, THIAGARAJAR COLLEGE OF ENGINEERING
Employment
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SAVEETHA ENGINEERING COLLEGE PROFESSOR2025 - Present
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Institute of Aeronautical Engineering PROFESSOR2021 - 2025
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CMR Group of institutions Professor2018 - 2021
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Latha Mathavan Engineering College PROFESSOR/HEAD2017 - 2018
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LATHAMATHAVAN ENGINEERING COLLEGE ASSOCIATE PROFESSOR / HEAD2011 - 2017
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RAJA COLLEGE OF ENGINEERING AND TECHNOLOGY ASSOCIATE PROFESSOR2008 - 2011
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RAJA COLLEGE OF ENGINEERING AND TECHNOLOGY ASSISTANT PROFESSOR2005 - 2007
Education
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ANNA UNIVERSITY Ph.D2011 - 2017
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RAJA COLLEGE OF ENGINEERING AND TECHNOLOGY M.E - CAD/CAM2006 - 2008
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THIAGARAJAR COLLEGE OF ENGINEERING B.E2001 - 2005
Projects & Funding
Projects & funding information is unavailable.
Publications (83)
- Performance Evaluation of Hybrid Kenaf–Pineapple Leaf–Flax Fiber Reinforced Vinyl Ester Composites: Mechanical and Thermal Characteristics for Diverse Engineering Prototype Applications Save
- Agro-waste sugarcane/pineapple/sisal hybrid epoxy composites: Mechanical, morphological and spectroscopic analysis for various engineering applications Save
- Machine learning-augmented prediction of static, dynamic mechanical, and thermal properties of luffa, Morinda tinctoria, and myrobalan-reinforced epoxy hybrid biocomposites Save
- Machine learning for mechanical property assessment and optimisation in hybrid natural fibre/epoxy composites Save
- Machine learning-based prediction and SHAP interpretation of mechanical properties in Kenaf/PALF/flax reinforced vinyl ester hybrid composites Save
- Advanced machine learning assisted prediction of multi-fiber hybrid natural fiber/epoxy composites based on jute, coconut coir, banana, and pineapple leaf fibers Save
- Experimental characterisation and machine learning (ML)-based tensile strength prediction of sugarcane bagasse, hemp and flax fibre hybrid composites for potential biomedical applications Save
- Computational modelling and optimization of mechanical properties of red brick dust‐epoxy composites using machine learning approach Save
- Parametric appraisal and wear prediction of red brick dust filled epoxy composites using finite element method Save
- Wear and Frictional Performance of Epoxy Composites Reinforced with Natural Waste Fibers and Fillers for Engineering Applications Save