Dr. Kota Venkateswarlu is an accomplished academician, researcher, and administrator in the field of Mechanical Engineering with extensive experience in teaching, research, accreditation, and institutional development. He has been actively involved in undergraduate and postgraduate engineering education, contributing significantly to Outcome-Based Education (OBE), NBA accreditation processes, curriculum development, and research activities.
His research interests include Manufacturing Engineering, Friction Stir Welding, Composite Materials, Condition Monitoring, Artificial Intelligence Applications in Mechanical Engineering, and Sustainable Manufacturing Technologies. Dr. Venkateswarlu has published several research papers in reputed national and international journals and conference proceedings, including publications indexed in Scopus and other leading databases.
In addition to his academic contributions, he has served in various administrative capacities such as NBA Criterion Coor
EDUCATION
• Awarded a Doctor of Philosophy ( in Mechanical Engineering from Pondicherry University, Puducherry, in 2025.
• Awarded M. Tech (Machine Design) from QIS College of Engineering and Technology (QISCET), affiliated with JNTU Kakinada, Ongole, in 2014.
• Completed B. Tech in Mechanical Engineering from Vignan’s Engineering College, Guntur, affiliated with JNTU Hyderabad (JNTUH), in 2008.
• Completed Intermediate Education from Sri Chaitanya Junior College, Vijayawada, in 2004.
• Completed Secondary School Education (SSC) from A.B.C. High School, Vijayawada, in 2002
Refurbishing ANN with the aid of adaptive crow search optimisation for effectively diagnosing railway wheel condition Kota Venkateswarlu, V.S.K. Venkatachalapathy, K. Velmurugan, A. Thiagarajan International Journal of Intelligent Systems Technologies and Applications, 2020 The research intends to diagnosis the railway wheel condition with the aid of artificial neural network (ANN). In diagnosing, ANN has been proven its convenience over manual computation in various applications. The research utilises optimisation techniques for identifying appropriate hidden layers and their associated neurons to enhance the performance of ANN techniques. This configuration process includes optimisation techniques like evolutionary algorithm (EA), genetic algorithm (GA), particle swarm optimisation (PSO), and crow search optimisation (CSO). Also, this research includes modified and improved conventional strategy in CSO, which urge incorporating novel strategy called adaptive crow search optimisation (ACSO) to enhance the performance. The proposed strategy unveils proficient performance of 99.2% accuracy, which is 1.7% greater than the conventional ANN model and an average of 0.9% greater than other contest techniques consider for configuration. The credibility of the ANN model gets increased while employs the optimisation techniques in diagnosing the railway wheel condition.
Diagnosing railway wheel conditions with the aid of AI-techniques International Journal of Mechanical Engineering and Technology, 2018
Publications
1. Refurbishing ANN with the aid of adaptive crow search optimisation for effectively diagnosing railway wheel condition Kota Venkateswarlu, V.S.K. Venkatachalapathy, K. Velmurugan and A. Thiagarajan Published Online: January 5, 2021 pp. 555- 570
2. Modelling and fabrication of catalytic converter for emission reduction K. Venkateswarlu, Revuri Ajay Kumar, Ram Krishna, M. Sreenivasan 10.1016/j.
3. Experimental investigation of the friction stir welding process with two dissimilar materials July 2020 Materials Today Proceedings 33 DOI: 10.1016/j.
4. Railway Wheel Condition Diagnoses with the Assistance of ANFIS Technique ISSN: 0011-9342 | Year 2021 Issue: 7 | Pages: 10362 - 10376
5. International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 12, December 2018, pp. 439–448, Article ID: IJMET_09_12_047 Available online at ISSN Print: 0976-6340 and ISSN Online: 0976-6359
6. Design an Artificial Neural Network Based Predictive Model for Automotive Applications ISSN: 0011-9342 Vol 2021 Issue 7 | Pages: 13335 - 13344
7. Experimental Investigation On Different Materials With Cnc Machining Process By Using Taguchi Method Vol 10, Issue 12, Dec/ 2019 Issn No: 0377-9254
8. Vibration Analysis Of Tapered Beam , T. Seshaiah Http:// Volume 1, Issue 1, Oct - Dec 2013
1. Diagnosing The Railway Wheel Conditions
RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)
1. Utility Patent Grant on Technology Titled as Compact Lightweight number LD-20260181429
2. Published Patent on Technology Titled as Optimizing Employee Engagement in a Post-Pandemic Era using Hybrid Work Models and Organizational Number 202641017670A
3. Published Patent on Technology Titled as Cryptocurrency Adoption in Emerging Markets Opportunities and Risks for Financial Inclusion Application Number 202641017673A
4. Published Patent on Technology Titled as The Investigation of Efficiency Optimization for Heavy-Duty Number 202541117726A
5. Published Patent on Technology Titled as IOT-Integrated Digital Twin Framework for real-time CNC machine monitoring and turning. Application Number 202541053941A
