Information
- Designation : Assistant Professor (Gr. II)
- Email : debtanay@mech.nits.ac.in
- Phone :
Introduction [Biosketch]
- Dr. Debtanay Das is a researcher in Manufacturing Technology with a strong research interest in machine learning and deep learning-based predictive modelling for manufacturing applications, together with a fundamental focus on process-structure-property relationships. His work emphasizes the close integration of data-driven approaches with computational and experimental methods to enhance process understanding, defect prediction, and optimization in additive manufacturing and advanced welding processes.
- He obtained his Ph.D. in Mechanical Engineering from IIT Guwahati, where his doctoral research involved detailed numerical and experimental characterization of surface and sub-surface defects in friction stir welding (FSW). His research combined advanced Coupled Eulerian-Lagrangian (CEL) finite element modelling with machine learning-based predictive approaches, enabling improved prediction of material flow, defect evolution, and thermo-mechanical behaviour in both similar and dissimilar material systems. For his doctoral work, he received two Best Ph.D. Thesis Awards, one from IIT Guwahati and another from the Indian Institute of Welding (IIW).
- Dr. Das completed his M. Tech in Production Engineering from NIT Agartala, where he was awarded the Departmental Gold Medal, and his B. Tech in Mechanical Engineering from NERIST, establishing a strong academic foundation in manufacturing and mechanical engineering.
- Dr. Das is also an inventor on multiple patents related to friction stir welding tools and portable FSW systems, reflecting his strong interest in translational research and industry-relevant manufacturing solutions. Through his research, he aims to contribute to the development of next-generation solid-state and additive manufacturing technologies that are predictive, reliable, scalable, and suitable for real-world industrial deployment.
Areas of Interest
- • Friction Stir Welding and Processing
- • Wire Arc Additive Manufacturing (WAAM)
- • Finite Element Modelling of Manufacturing Processes
- • Physics-informed machine learning and deep learning-based predictive modelling for manufacturing applications
| Institution | Year | Degree |
|---|---|---|
| Indian Institute of Technology (IIT) Guwahati | 2023 | Doctor of Philosophy (Ph. D.) |
| National Institute of Technology (NIT) Agartala | 2018 | Master of Technology (M. Tech.) |
| NERIST | 2015 | Bachelor of Technology (B. Tech.) |
Teaching Experience
NIT Silchar
Industrial/Research Experience
IISc Bangalore
IISc Bangalore
IIT Guwahati
Awards And Honours
- 1. Weldwell Speciality Award for the Best Ph. D. thesis 2024 from The Indian Institute of Welding.
- 2. Best Ph.D. thesis award 2024 from the Indian Institute of Technology (IIT) Guwahati.
- 3. Departmental Gold Medallist 2018 in the Department of Production Engineering from the National Institute of Technology (NIT) Agartala.
