Education
- Ph.D., Michigan Technological University, 1993
- M.S., Washington State University, 1989
- B.Tech. (Hons.) IIT Kharagpur, India, 1987
Background
Dr. Melkote began at Tech in 1995 as an Assistant Professor. Prior to this, he was a Post-doctoral Research Associate at the University of Illinois at Urbana-Champaign where he conducted research in Machining and Machine Tools Systems in the group led by Professors Richard E. DeVor and Shiv G. Kapoor.
Research
- Manufacturing and Tribology; Precision machining, hybrid processes, surface modification, AI/ML for manufacturing, robotics for manufacturing
Dr. Melkote’s primary area of research is Manufacturing, and his secondary area of research is Tribology. His research interests in these areas focus on the science of precision material removal processes, new manufacturing process development including novel surface modification methods, application of artificial intelligence and machine learning (AI/ML) to solve complex problems in manufacturing, and advanced industrial robotics for precision manufacturing.
His research in precision material removal process science focuses on understanding material removal and surface generation mechanisms, process-structure-property relationships, and extreme tribological behavior of metals and non-metals through experiments and modeling. His work on new process development is focused on novel surface modification processes such as water cavitation peening and ultrasonic cavitation assisted hybrid processes for improving the surface finish and surface mechanical properties of conventionally and additively manufactured metal parts for aerospace and biomedical applications. His research in application of AI/ML in manufacturing is focused on using data-driven and human-machine interaction techniques to infer complex manufacturing process capability knowledge typically acquired by human experts through years of experience and using this knowledge to enable the creation of resilient on-demand cyber manufacturing mesh networks for on-demand supplier identification. Finally, his research in advanced robotics for manufacturing is focused on both offline and real-time sensing and control methods to improve the accuracy of industrial robots in complex manufacturing processes such as machining, finishing, and hybrid additive and subtractive manufacturing. Dr. Melkote’s research in these areas is supported by industry, government, and internal sources.
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- Milton C. Shaw Manufacturing Research Medal, 2024
- Assistant Director for Technology, Advanced Manufacturing National Program Office, NIST, Gaithersburg, MD, 2015-2016
- Society of Manufacturing Engineers (SME)
- SME Gold Medal, 2023
- Fellow, 2015
- President, North American Manufacturing Research Institution of the SME (NAMRI/SME), 2014-2015
- Scientific Committee Chair, NAMRI/SME, 2010-2012
- Member, Board of Directors, NAMRI/SME, 2008-2017
- Outstanding Paper Award, NAMRC, 1998
- Dell K. Allen Outstanding Young Manufacturing Engineer Award, 1998
- Research Initiation Award, 1995
- College International Pour La Recherche En Productique (CIRP) (The International Academy for Production Engineering), Paris, France
- Fellow, 2018
- Chair, Scientific Technical Committee – Cutting, 2022 - 2025
- Woodruff School & Institute
- Interim School Chair, Woodruff School of Mechanical Engineering, May – December 2025
- Outstanding Achievement in Research Engagement and Outreach, Office of the Executive Vice President for Research, 2024
- Associate Director, Georgia Tech Manufacturing Institute, 2008-2025
- Woodruff Faculty Fellow, 2006-2010
Representative Publications
- Kumar, M., Melkote, S.N., “Process Capability Study of Laser-Assisted Micro Milling of a Hardened Tool Steel,” Journal of Manufacturing Processes, Vol. 14, No. 1, pp. 41-51, 2012.
- Fernandez-Zelaia, P., Melkote, S.N., “Process-Structure-Property Relationships in Bimodal Machined Microstructures using Robust Structure Descriptors,” Journal of Materials Processing Technology, Vol. 273, 116251, p. 1-16, 2019.
- Kumar, A., Melkote, S.N., “Wear of Diamond in Scribing of Multicrystalline Silicon,” Journal of Applied Physics, Vol. 128, p. 065101, 2018.
- Jeon, J.-H., Ahn, S.-H., Melkote, S.N., “In-situ Analysis of the Effect of Ultrasonic Cavitation on Electrochemical Polishing of Additively Manufactured Metal Surfaces,” ASME Transactions, Journal of Manufacturing Science and Engineering, April 2024; 146(4): 041003.
- Rashid, A., Vatandoust, F., Kota, A., Melkote, S.N., “Bead Geometry Prediction in Wire Arc Directed Energy Deposition using Physics-Informed Machine Learning and Low-Fidelity Data,” Additive Manufacturing, Vol. 109, July 2025, 104881.
- Kota, A., Shanghavi, N.M., Singh, P.M., Jeon, J.H., Melkote, S.N., “Enhancing the Properties of a Low Carbon Steel and SS316L Bimetallic Interface via Mesoscale Groove Engineering in Hybrid Wire-Arc Directed Energy Deposition,” Journal of Manufacturing Processes, 153 (2025): 602-618.
- Zhao, C., Dinar, M., Melkote, S.N., “Automated Classification of Manufacturing Process Capability Utilizing Part Shape, Material, and Quality Attributes,” ASME Transactions, Journal of Computing and Information Science in Engineering, Vol. 20, No. 2, 2020, 021011 (13 pages).
- Yan, X., Wang, Z., Puvvada, M.M., Dinar, M., Rosen, D.W., Melkote, S.N., “A Federated Learning Approach to Automated and Secure Supplier Selection in Cyber Manufacturing As-a-Service,” Journal of Manufacturing Systems, Vol. 77, December 2024, 170-183.
- Nguyen, V., Cvitanic, T., Melkote, S., “Data-driven Modeling of the Dynamic Properties of a 6-DoF Industrial Robot within its Workspace and Its Application to Robotic Milling,” ASME Transactions, Journal of Manufacturing Science and Engineering, Vol. 141, Issue 12, 2019, 121006 (12 pages).
- Cvitanic, T., Melkote, S.N., “A New Method for Closed-Loop Stability Prediction in Industrial Robots,” Robotics and Computer-Integrated Manufacturing, Vol. 73, 2022, 102218.