Aswin Karkadakattil
Independent Researcher in Mechanical, Materials, and Aerospace Engineering with Applications in Artificial Intelligence
0009-0004-6141-0545
About
Aswin Karkadakattil is a postgraduate in Materials and Manufacturing Engineering from the Indian Institute of Technology (IIT), India. His postgraduate research focused on laser-based surface post-processing of additively manufactured metallic components and the development of artificial neural network (ANN)-based predictive models for surface quality assessment. He earned his Bachelor of Technology (B.Tech) in Mechanical Engineering from the Government College of Engineering, Kannur, Kerala, India. During his undergraduate studies, he was a recipient of the Prime Minister's Scholarship throughout the four-year program in recognition of his academic excellence. His research interests include additive manufacturing, laser and directed energy processing, artificial intelligence for advanced manufacturing, digital twin technologies, aerospace engineering, and renewable energy systems, with a focus on developing intelligent, physics-informed solutions for next-generation engineering applications.
Employment
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Independent Researcher in Mechanical, Materials, and Aerospace Engineering with Applications in Artificial Intelligence
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (27)
- Laser surface modification of additively manufactured metals: mechanisms, thermal–microstructural evolution, and property enhancement Save
- Physics-Informed Neural Network Modeling of Passive Photovoltaic Cooling Using Experimental Benchmark Data Save
- Physics‐Inspired, Ageing‐Aware Digital Twin Framework for Long‐Term Performance Prediction in Bioreactor Systems Save
- A Physics-Stabilized Self-Updating Digital Twin Framework Using Physics-Informed Neural Networks for Thermal Field Prediction Save
- Mechanics-informed AI laser 4D frameworks for adaptive materials processing and sustainable manufacturing: a quantitative review Save
- Analytical Modelling and Parametric Optimization of Hybrid Hydrogen-Electric Propulsion for Long-Endurance UAVs Save
- Physics-Regularized Neural Networks for Photovoltaic Power Prediction Under Limited Experimental Data Save
- AI and Metaheuristic Optimization in Additive Manufacturing of Lightweight Alloys: A Critical Review Save
- A physics-informed intelligent digital twin using multi-task CNN–LSTM for acoustic emission-based fault prognostics in safety-critical systems Save
- Physics-guided neural network framework for surface roughness prediction in additively manufactured metallic alloys Save