Scholar
Chinmay Datar
Google Scholar ID: JyE0nzcAAAAJ
Doctoral Researcher, Technical University of Munich
Citations & Impact
Citations
53
H-index
3
i10-index
1
Publications
13
Co-authors
12
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Supervised Master's Theses: Solving PDEs with SWIM networks using domain decomposition; Predicting fluid dynamics using convolutional random feature models; Sampling neural networks to approximate Hamiltonian functions; Using neural networks with domain decomposition to solve partial differential equations.
Research Experience
- Started doctoral studies in July 2022; Engineering Summer Internship at Koshizuka-Shibata Lab, University of Tokyo, Japan; Summer Research Internship at the Hanson Lab, Stanford University, USA (2017).
Education
- PhD candidate at the Institute of Advanced Study (IAS), TUM, focusing on 'Scientific Machine Learning', under the supervision of Prof. Wil Schilders and Prof. Felix Dietrich; MSc in Computational Engineering, FAU, Erlangen (2018-2022); Bachelor's degree in Mechanical Engineering from the University of Pune (2017).
Background
- Research interests: Combining classical methods in scientific computing and deep learning for solving Partial Differential Equations (PDEs); developing novel neural network architectures for simulating dynamical systems; back-propagation-free training of neural PDE solvers; combining domain decomposition and neural networks for solving PDEs.
