Anurag University | India
Dr. Shravan Kumar Rudrabhatla is an Assistant Professor at Anurag University, Hyderabad, specializing in fluid dynamics and artificial neural networks. He earned his Ph.D. in Applied Mathematics from the National Institute of Technology (NIT), Warangal in 2023 under the supervision of Prof. D. Srinivasacharya, focusing on the artificial neural network treatment of Casson fluid flow over a radially stretching sheet. His research integrates deep learning, computational fluid dynamics, and heat and mass transfer modeling, contributing to the understanding of complex non-Newtonian flows. Dr. Rudrabhatla has authored 6 research articles, accumulated 49 citations from 43 documents, and achieved an h-index of 4, as indexed by Scopus. His recent works include publications in European Journal of Mechanics B/Fluids, Physics of Fluids, Mathematical Models and Computer Simulations, and Journal of Thermal Analysis and Calorimetry. He has participated in numerous faculty development programs, workshops, and GIAN courses focused on machine learning and computational modeling. His academic journey is complemented by strong technical skills in Python, MATLAB, and C++, and a teaching background spanning over a decade. Dr. Rudrabhatla’s work continues to advance the intersection of mathematics, fluid mechanics, and artificial intelligence, contributing significantly to modern computational sciences.
Featured Publications
Srinivasacharya, D., & Kumar, R. S. (2022). Artificial neural network modeling of the Casson fluid flow over unsteady radially stretching sheet with Soret and Dufour effects. Journal of Thermal Analysis and Calorimetry, 147, 14891–14903. https://doi.org/10.1007/s10973-022-11694-w
Srinivasacharya, D., & Shravan Kumar, R. (2023). Neural network analysis for bioconvection flow of Casson fluid over a vertically extending sheet. International Journal of Applied and Computational Mathematics, 9(5), 80. https://doi.org/10.1007/s40819-023-01556-w
Srinivasacharya, D., & Kumar, R. S. (2023). An artificial neural network solution for the Casson fluid flow past a radially stretching sheet with magnetic and radiation effect. Mathematical Models and Computer Simulations, 15(5), 944–955. https://doi.org/10.1134/S2070048223050101
Nallapu, S., Sneha, G. S., & Kumar, S. R. (2018). Effect of slip on Jeffrey fluid flow through an inclination tube. Journal of Physics: Conference Series, 1000(1), 012041. https://doi.org/10.1088/1742-6596/1000/1/012041
Rudrabhatla, S. K., & Srinivasacharya, D. (2025). Deep learning framework for Casson fluid flow: A PINN approach to heat and mass transfer with chemical reaction and viscous dissipation. European Journal of Mechanics – B/Fluids, 204401. https://doi.org/10.1016/j.euromechflu.2025.204401