Faculty & Staff
Contact
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Email
pramoda.me.et@msruas.ac.in
- Phone 080 4906 5555
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Websites
ORCID, Web of Science, Google Scholar,Research Gate,Linkedin
Dr. Pramod A
Assistant Professor
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School/College
Faculty of Engineering and Technology
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Department
Department of Mechanical and Manufacturing Engineering
Dr. Pramod A joined Ramaiah University of Applied Sciences (RUAS) as an Assistant Professor. He received his Ph.D. in Smart Manufacturing in 2025 from the National Institute of Technology Calicut, India. He completed his M. Tech. in Product Design and Manufacturing from R.V. College of Engineering, Bangalore, in 2019, graduating with a CGPA of 9.30 and earning the distinction of being the topper of his batch.
His passion for research runs deep in areas such as Smart Manufacturing, Multi-Sensor Data Fusion, Signal Processing, Robot Vision, Deep Learning, and Cloud Computing.
Dr. Pramod has also demonstrated a strong commitment to academic scholarship by serving as a reviewer for over 70 articles in internationally recognized, peer-reviewed journals published by Elsevier, Springer, and SAGE.
Qualifications
- Ph.D.
National Institute of Technology Calicut , 2025, CGPA – 9.17
- M.Tech.
R.V. College of Engineering, Bangalore, 2019, CGPA – 9.30 (Topper)
- B.E.
P.E.S. College of Engineering, Mandya , 2012, CGPA – 8.69
Experience
Total Years of Experience10 years 3 months
Academic Experience
- The National Institute of Engineering, Mysore – 1 year 1 month
- NIE Institute of Technology, Mysore – 5 months
- National Institute of Technology Calicut (Research Scholar), Kozhikode – 5 years
Industry Experience:
- QuEST Global Engineering Pvt. Ltd., Bangalore – 2 years 10 months
- TVS Motor Company Pvt. Ltd., Mysore – 11 months
- Smart Manufacturing
- Sensor Signal Processing
- Multi Sensor Data Fusion
- Robot Vision
- Artificial Intelligence
- Cloud Computing
- Rajaram, V., Ingle, Y., Rajayogeshwar, G., Pramod, A., Deepak Lawrence, K. (2025). Milled Surface Defect Detection and Classification on Inconel 617 Using Machine Vision Based on YOLO Algorithm. In: Chakrabarti, A., Suwas, S., Arora, M. (eds) Industry 4.0 and Advanced Manufacturing, Volume 2. I-4AM 2024. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-97-6176-0_7
Reviewer for leading publishers below are the details:
| Sl.No. | Journal Name | Publishers |
|---|---|---|
| 1 | Engineering Applications of Artificial Intelligence | Elsevier |
| 2 | Journal of Manufacturing Processes | Elsevier |
| 3 | The International Journal of Advanced Manufacturing Technology | Springer Nature |
| 4 | Journal of Mechanical Science and Technology | Springer Nature |
| 5 | Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture | Sage |
Completed nine courses on NPTEL:
| Sl.No. | Course Name | Performance |
|---|---|---|
| 1 | Python for Data Science | Elite |
| 2 | IntroductionTo Internet of Things | Elite + Silver |
| 3 | CloudComputing | Elite |
| 4 | ToyotaProduction System | Elite + Silver |
| 5 | EngineeringMetrology | Elite |
| 6 | Introductionto Industry 4.0 and Industrial Internet of Things | Elite |
| 7 | RapidManufacturing | Elite |
| 8 | Fundamentalsof manufacturing processes | Elite |
| 9 | Design forQuality, Manufacturing and Assembly | Elite |
Below are the details of the Courses & Certifications:
| Sl.No. | Course Name | Platform |
|---|---|---|
| 1 | Crash Courseon Python | Coursera |
| 2 | AWSFundamentals: Going Cloud-Native | Coursera |
| 3 | Art andScience of Machine Learning | Coursera |
| 4 | Google CloudPlatform Fundamentals: Core Infrastructure | Coursera |
| 5 | Connectingwith the Internet of Things | InfosysSpringboard |
International Conference Papers
- Pramod A, Deepak Lawrence K, Jose Mathew. “Deep learning-based neural network for flank wear prediction using acoustic emission signals on Inconel 617 alloy”. 9th International & 30th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2023), Dec 08-10, 2023, at Indian Institute of Technology (BHU) Varanasi.
- Pramod A, Deepak Lawrence K, Jose Mathew. “Deep learning-enabled power prediction for Inconel 718 pocket milling”. 13th International Conference on Precision, Meso, Micro and Nano Engineering (COPEN), Dec 12-14, 2024, at National Institute of Technology Calicut
International Journal Papers
- Pramod A, Deepak Lawrence K, Jose Mathew. “The multi-sensor-based measurement of machining signals and data fusion to develop predictive tool wear models for TiAlN-PVD coated carbide inserts during end milling of Inconel 617”. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 2024; 238 (6-7): 886-903. https://doi.org/10.1177/09544054231185155
- Pramod A, Allada Satish, Dhanish P B, Jose Mathew, Deepak Lawrence K. “Analysis of the power during machining of Inconel 718 for different geometrical profiles and the development of power prediction models using multi-sensor data”. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 2024; 0(0). https://doi.org/10.1177/09544089241291743
- American Society of Mechanical Engineers (ASME) - Student
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