Veerababu Dharanalakota
Indian Institute of Science Bangalore, Indian Institute of Technology Hyderabad, Indian Institute of Science, Bajaj Auto Ltd, Jawaharlal Nehru Technological University Kakinada
0000-0002-7696-2842
About
Dr. Veerababu Dharanalakota has been working in the field of Acoustics and Vibration. He obtained his master's degree from Indian Institute of Science, Bengaluru, and his Ph.D. degree from Indian Institute of Technology Hyderabad, India. Before joining the Ph.D. programme, he worked as an Assistant Manager in R&D at Bajaj Auto Limited in Pune, India. As part of his PhD work, he developed a semi-analytical method using Green's functions to study sound propagation in lined circular ducts. He received prestigious awards from the International Union for Pure and Applied Physics (IUPAP), the Acoustical Society of America (ASA), and the International Institute of Noise Control Engineering (I-INCE). He is currently a member of the Acoustical Society of India, ASA, IIAV, INCE-USA, AIAA, and IEEE. His expertise includes Computational Acoustics, Numerical Modelling, Scientific Machine Learning, and Numerical Optimization. Currently, he is working as a postdoctoral fellow at the Indian Institute of Science, Bengaluru, India. His current research focusses on the use of physics-informed neural networks for acoustic applications.
Employment
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Indian Institute of Science Bangalore Postdoctoral Fellow2021 - 2025
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Indian Institute of Technology Hyderabad Postdoctoral Fellow2021 - 2021
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Bajaj Auto Ltd Assistant Manager2013 - 2015
Education
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Indian Institute of Technology Hyderabad PhD2015 - 2020
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Indian Institute of Science ME2011 - 2013
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Jawaharlal Nehru Technological University Kakinada B.Tech2007 - 2011
Projects & Funding
Projects & funding information is unavailable.
Publications (22)
- Solving 2-D Helmholtz equation in the rectangular, circular, and elliptical domains using neural networks Save
- Prediction of Acoustic Field in 1-D Uniform Duct with Varying Mean Flow and Temperature Using Neural Networks Save
- Physics-informed neural networks for predicting acoustic pressure inside ducts Save
- Improving neural network training using dynamic learning rate schedule for PINNs and image classification Save
- Estimation of the Acoustic Field in a Uniform Duct with Mean Flow using Neural Networks Save
- Prediction of one-dimensional acoustic field with axial temperature gradient using neural networks Save
- Neural network based approach for solving problems in plane wave duct acoustics Save
- Scaling Laws for acoustic duct performance measurement Save
- Solution of 1-D Helmholtz equation using artificial neural networks Save
- Loss-based optimizer switching to solve 1-D Helmholtz equation using neural networks Save