About
I am a Postdoctoral Researcher at CREATIS Biomedical Imaging Laboratory, INSA‑Lyon, France. My main research interest is in scientific ML (SciML) for forward and inverse problems governed by PDEs—with applications to computational fluid dynamics and medical imaging.
Research Interests
Domain‑informed AI
Physics-/biophysics‑informed learning
Scientific machine learning (SciML)
PDE‑constrained learning
Computational fluid dynamics
Medical imaging
Inverse problems
Selected Publications
- Dwivedi, V., Sixou, B., & Sigovan, M. (2025). Curriculum learning‑driven PI‑ELMs for fluid flow simulations. Neurocomputing. doi:10.1016/j.neucom.2025.130924.
- Dwivedi, V., Srinivasan, B., & Krishnamurthi, G. (2024). Physics‑informed contour selection for rapid image segmentation. Scientific Reports. doi:10.1038/s41598-024-57281-x.
- Dwivedi, V., Parashar, N., & Srinivasan, B. (2020). Distributed learning machines for solving forward and inverse PDE problems. Neurocomputing. doi:10.1016/j.neucom.2020.09.006.
- Dwivedi, V., & Srinivasan, B. (2019). Physics informed extreme learning machine (PIELM) — a rapid method for the numerical solution of PDEs. Neurocomputing. doi:10.1016/j.neucom.2019.12.099.
Updates
Februray 2026
Journal Papers
- Dwivedi, V., Schiassi, E. , Sixou, B., & Sigovan, M. (2026). Gated X-TFC: Soft Domain Decomposition for Forward and Inverse Problems in Sharp-Gradient PDEs. Neurocomputing. doi:10.1016/j.neucom.2020.09.006.
October 2025
Conference Papers
- Dwivedi, V., Sigovan, M., & Sixou, B. (Dec 2025). Curriculum-Learning PIELMs for Hemodynamic Flows. 17th OPT Workshop @ NeurIPS, San Diego, USA.
- Dwivedi, V., Sigovan, M., & Sixou, B. (Dec 2025). Empirical-Bayes XTFC for Inverse Parameter Estimation. 17th OPT Workshop @ NeurIPS, San Diego, USA.
- Srinivasan, A. G., Dwivedi, V., & Srinivasan, B. (Dec 2025). Deep vs. Shallow: Benchmarking Physics-Informed Neural Architectures on the Biharmonic Equation. 8th ML4PS Workshop @ NeurIPS, San Diego, USA.
Preprints
- Dwivedi, V., Srinivasan, B., Sigovan, M., & Sixou, B. (2025). Kernel-Adaptive PI-ELMs for Forward and Inverse Problems in PDEs with Sharp Gradients. arXiv:2507.10241. (Submitted to Neural Networks)
July 2025
- Attended summer AI school in Paris — AI Science Summer School 2025 (UChicago Center in Paris).