Portrait of Dr. Vikas Dwivedi

Dr. Vikas Dwivedi

Postdoctoral Researcher
CREATIS Biomedical Imaging Laboratory, INSA-Lyon, France
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About

I am a Postdoctoral Researcher at CREATIS Biomedical Imaging Laboratory, INSA-Lyon, France, working on scientific machine learning for forward and inverse PDE problems, with applications in computational fluid dynamics and medical imaging. I completed my M.Tech from IIT Delhi and Ph.D. from IIT Madras under the supervision of Prof. Balaji Srinivasan. I bring 2+ years of industry experience as a Data Scientist at Vunet Systems and over 3 years of postdoctoral research experience across India, the United States, and France. I was also awarded the Best PhD Thesis Award in Data Science by IIT Madras.

Journal Articles

  1. 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.2026.133090.
  2. Dwivedi, V., Sixou, B., & Sigovan, M. (2025). Curriculum learning-driven PI-ELMs for fluid flow simulations. Neurocomputing. doi:10.1016/j.neucom.2025.130924.
  3. Dwivedi, V., Srinivasan, B., & Krishnamurthi, G. (2024). Physics-informed contour selection for rapid image segmentation. Scientific Reports. doi:10.1038/s41598-024-57281-x.
  4. Dwivedi, V., & Srinivasan, B. (2022). A normal equation-based extreme learning machine for solving linear partial differential equations. Journal of Computing and Information Science in Engineering. doi:10.1115/1.4051530.
  5. 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.
  6. Dwivedi, V., & Srinivasan, B. (2020). Solution of biharmonic equation in complicated geometries with physics informed extreme learning machine. Journal of Computing and Information Science in Engineering. doi:10.1115/1.4046892.
  7. 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.
  8. Dwivedi, V., & Srinivasan, B. (2018). Prediction of transition in temporal mixing layer using ILES. International Journal of Advances in Engineering Sciences and Applied Mathematics. doi:10.1007/s12572-018-0218-9.

Google Scholar

Citations 659
h-index 8
i10-index 7
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Conferences

  • Dwivedi, V., Sigovan, M., & Sixou, B. (2026). Kernel-Adaptive Physics-Informed Meta-Learning for Parametric Linear PDEs. AI&PDE: ICLR 2026 Workshop on AI and Partial Differential Equations. openreview.
  • Daniel, A., Dwivedi, V., & Srinivasan, B. (2026). AB-PIELMS: Adaptive-Basis Physics-Informed Extreme Learning Machines for Residual-Driven Domain Decomposition. AI&PDE: ICLR 2026 Workshop on AI and Partial Differential Equations. openreview.
  • Dwivedi, V., Sigovan, M., & Sixou, B. (2025). Curriculum-Learning PIELMs for Hemodynamic Flows. OPT 2025: Optimization for Machine Learning. openreview.
  • Dwivedi, V., Sigovan, M., & Sixou, B. (2025). Empirical-Bayes XTFC for Inverse Parameter Estimation. OPT 2025: Optimization for Machine Learning. openreview.
  • Srinivasan, A. G., Dwivedi, V., & Srinivasan, B. (2025). Deep vs. Shallow: Benchmarking Physics-Informed Neural Architectures on the Biharmonic Equation. ML4PS 2025: Machine Learning for the Physical Sciences Workshop. paper.
  • Dwivedi, V. (2024). Global Versus Local: Evaluating AlexNet Architectures for Tropical Cyclone Intensity Estimation. International Conference on Pattern Recognition. doi:10.1007/978-3-031-78186-5_27.

Preprints

  • Dwivedi, V., Sigovan, M., & Sixou, B. (2026). Meta-Learned Basis Adaptation for Parametric Linear PDEs. arXiv:2604.09289.
  • Dwivedi, V., Sigovan, M., & Sixou, B. (2026). Soft Partition-based KAPI-ELM for Multi-Scale PDEs. arXiv:2601.08719.
  • 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.