I am working with Prof. Colin Cotter on PDE-driven Digital Twins and Uncertainty Quantification using the Firedrake platform.
Interests
- Scientific Computing
- Uncertainty Quantification
Publications
T. Anandh, D. Ghose, H. Jain, S. Ganesan. FastVPINNs: Tensor-driven acceleration of VPINNs for complex geometries (2025), SIAM Journal on Scientific Computing (SISC) 47(3), C578–C600.
T. Anandh, D. Ghose, A. Tyagi, A. Gupta, S. Sarkar, S. Ganesan. An efficient hp-Variational PINNs framework for incompressible Navier-Stokes equations (2025), arXiv preprint arXiv:2409.04143.
T. Anandh, D. Ghose, S. Ganesan. FastVPINNs: An efficient tensor-based Python library for solving partial differential equations using hp-Variational Physics Informed Neural Networks (2024), Journal of Open Source Software 9(99).
D. Ghose, T. Anandh, H. Jain, P. Sunkad, S. Ganesan. Improving hp-variational physics-informed neural networks for steady-state convection-dominated problems (2025), Computer Methods in Applied Mechanics and Engineering (CMAME) 438.
Education
College of Engineering Pune | Pune, India
B.Tech (Hons.) in Mechanical Engineering | Sept 2015 – June 2019
