Assistant Professor
Department of Civil Engineering
Mahindra University
4 Years - Research &
Structural Health Monitoring, Blended Concrete Systems, Non-Destructive Testing and Evaluation, Embedded Piezoelectric Sensors, Strength Monitoring, Damage Detection, Durability monitoring and Machine Learning.
Structural Health Monitoring, Sustainable Concrete Systems and Machine Learning Applications
Mail: ramesh.g@sru.edu.in
Ph.D. - Structural Engineering
M.Tech - Structural Engineering
B.Tech - Civil Engineering
Assistant Professor at SR University, Warangal , from 2025-08-04 to .
Ph.D
7. Gomasa, R., Talakokula, V., Jyosyula, S. K. R., & Bansal, T. (2024). Non-destructive Damage Identification of Blended Concrete Systems Using Embedded Piezo Sensors. Civil Structural Health Monitoring (CSHM) 2024. Lecture Notes in Civil Engineering, vol 516. Springer, Cham. https://doi.org/10.1007/978-3-031-62253-3_5
6. Gomasa, R., Talakokula, V., Jyosyula, S. K. R., & Bansal, T. (2025). EMI-based damage prediction of blended concrete under sulphuric acid exposure using ML and ANN models, IEEE Xplore, doi: 10.1109/ICE63309.2025.10983940.
5. Wang, Q., Kunther, W., Li, Y., Visalakshi, T., Gomasa, R., Amroun, S., ... & Wilson, W. (2025). Sulfate attack testing approaches from concrete to cement paste: A review by RILEM TC 298-EBD. Materials and Structures, https://doi.org/10.1617/s11527-025-02759-x, 58(7), 232. (Q1, SCIE, IF: 3.9)
4. Gomasa, R., Talakokula, V., Jyosyula, S. K. R., & Bansal, T. (2025). Strength Monitoring and Prediction of Blended Concrete Systems from Very Early to Delayed Age Using Embedded Piezo Sensor Data: An Experimental and Machine Learning Approach. Journal of Building Engineering, 112677, https://doi.org/10.1016/j.jobe.2025.112677, (Q1, SCIE, IF: 6.7).
3. Gomasa, R., Talakokula, V., Jyosyula, S. K. R., & Bansal, T. (2025). Chloride-induced degradation in blended concrete systems: A comparative study under ideal and combined exposure conditions using embedded piezo sensors. Construction and Building Materials, 475, 141114. https://doi.org/10.1016/j.conbuildmat.2025.141114, (Q1, SCIE, IF: 7.4)
2. Gomasa, R., Talakokula, V., Jyosyula, S. K. R., & Bansal, T. (2024). Integrating electro-mechanical impedance data with machine learning for damage detection and classification of blended concrete systems. Construction and Building Materials, 445, 137725. https://doi.org/10.1016/j.conbuildmat.2024.137725, (Q1, SCIE, IF: 7.4)
1. Gomasa, R., Talakokula, V., Jyosyula, S. K. R., & Bansal, T. (2023). A review on health monitoring of concrete structures using embedded piezoelectric sensor. Construction and Building Materials, 405, 133179. https://doi.org/10.1016/j.conbuildmat.2023.133179, (Q1, SCIE, IF: 7.4)
Won 1st Place in Paper & Poster Presentation at National Level Virtual Technical Symposium ASTHIVAR 2K21, organized by Dept. of Civil Engg., Sri Ranganathar Institute of Engg. & Tech., Coimbatore (25-11-2021).
