I am a postdoctoral researcher under Professor Hendrik Ranocha in the Numerical Mathematics group at Johannes Gutenberg University, Mainz. I am funded by the Mainz Institute of Multiscale Modeling (M3ODEL).

Prior to my current position, I was a PhD student under Professor Praveen Chandrashekar at Tata Institute of Fundamental Research - Centre for Applicable Mathematics. My work is on development of efficient numerical algorithms for simulation of advection dominated fluid flows. The broad class of numerical algorithms that I study are higher order methods. These methods are notable for having better accuracy with fewer grid points and doing more number crunching and lesser memory transfers, something that modern computers like.

The particular higher order methods that I worked on during my PhD are Lax-Wendroff Flux Reconstruction (LWFR) schemes. These simulate time dependent flows without depending on an Ordinary Differential Equation (ODE) solver and can thus achieve higher order accuracy in a single stage, minimizing memory transfers even more than standard higher order methods. My PhD thesis can be found here. In collaboration with my colleagues, my PhD thesis includes the following contributions to the LWFR scheme.

  1. Enhancement of stability and accuracy: Article Preprint
  2. Provably admissibility-preserving shock capturing with particular focus on maintaining the benefits of high order accuracy: Article Preprint
  3. Embedded error-based time step computation, tested on adaptive curvilinear meshes. Article Preprint
  4. Advection-diffusion equations like Navier-Stokes Preprint
  5. Generalized framework for admissibility preservation, source terms Preprint
  6. Proven linear equivalence with ADER schemes where local evolution is performing by solving an implicit equation Preprint
  7. Accurate and robust multiderivative Runge-Kutta method in a Flux Reconstruction framework Preprint

My latest list of publications can be found here. You can see my cv here. Thanks for visiting!

Presenting our work at ICOSAHOM 2023, Yonsei University, Seoul, Korea

Photo credits to Kedar Wagh