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December 31, 2024
Tourism and Hospitality Management: A Global Gateway to Career Opportunities
May 28, 2025
Dr. K. Ravindranath Tagore
Faculty
Dr. K. Ravindranath Tagore is well versed as an academic, researcher, and practitioner in engineering design with particular emphasis in artificial intelligence, machine learning, deep learning, data analytics, and mechanical engineering. His areas of interest for teaching and research include neural network, optimization, advanced and additive manufacturing, and computational engineering.
He has authored a number of research articles in peer-reviewed and Scopus indexed journals focusing on artificial neural networks, deep learning, diesel sprays classification using convolutional neural networks, forecasting, as well as optimization of manufacturing processes. Besides, he has participated in many national and international conferences on computer science, artificial intelligence, engineering, and materials science and presented research papers.
Dr. Tagore has advanced skills and considerable knowledge with various technical software such as Python, SQL, Power BI, neural networks, CAD/CAM, AutoCAD, ANSYS, and software for data visualization. He has been awarded many Best Teacher Awards for his work in technical education and research.
Publications
Journal Publications
- “Integration of Machine Learning Based Advanced Neural Networks for Various Applications”, published in International Journal of Advanced Technology and Engineering Exploration (Paper ID: IJATEE_1/25_212535), 2026, ISSN: 2394-5443, Q3 (1.6842)/2.7, indexed in Scopus, Google Scholar, and listed in the UGC Care List.
- “Deep Learning Approaches for the Classification of Diesel Injector Spray Pattern”, published in International Journal of Information Technology & Computer Engineering, Vol-13, Issue-1, 2025, pp. 789–795, ISSN: 2347-3657, DOI Prefix: 10.62647, Impact Factor: 6.091, indexed in CROSSREF, ROAD, and THE KEEPERS, and listed in the UGC Care List.
- “Information Retrival and Summerizing of Documents Using Artificial Neural Networks”, published in Res Militaris, Social Science Journal, Vol-13, Issue-3, 2023, pp. 6206–6213, ISSN: 2265-6294, Q4 / 0.102 SJR, listed as a peer-reviewed academic journal in the UGC Care List.nal in the UGC Care List.
- “Automated Diesel Spray Classification Using Convolution Neural Networks”, published in Journal of Computational Analysis and Applications, Vol-33, Issue-7, 2024, pp. 1828–1835, ISSN: 1521-1398, Q3 / 2.82, indexed in Scopus and databases including EBSCO.
- “Global Optimization Technics for Training Feed Forward Neural Networks in Forecasting Applications”, published in Journal of Engineering Sciences, Vol-14, Issue-4, 2023, pp. 1666–1678, ISSN: 0377-9254, Impact Factor: 6.54, listed as a peer-reviewed academic journal in the UGC Care List.
Book Publications
- “Deep Learning Approaches for the Classification of Diesel Injector Spray Pattern”, published in the proceedings of the 4th International Conference on Innovation and Recent Trends in Computer Science (ICIRTCS-2024), Hyderabad, 2024, ISBN: 978-93-94246-59-1, published by St. Martin’s College of Engineering.
- “Global Optimization Techniques for Training Feed-Forward Neural Networks”, published in the proceedings of the 2nd International Conference on Innovation and Recent Trends in Computer Science (ICIRTCS-2023), Hyderabad, 2023, ISBN: 978-93-91420-22-2, published by St. Martin’s College of Engineering.