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I am Devansh Tripathi, a final-year student in the five-year integrated BS-MS dual degree in Mathematics at the Indian Institute of Science Education and Research, Thiruvananthapuram (IISER TVM), Kerala, India. I came to machine learning through numerical analysis. In summer 2024, I worked with Prof. Praveen Chandrashekar at TIFR-CAM, Bangalore, on the distributed-memory parallelization of the Lax-Wendroff Flux Reconstruction solver TrixiLW.jl. In summer 2025, I was an ETH4D Fellow in Prof. Siddhartha Mishra's group at ETH Zürich, where I proved that the Geometry Aware Operator Transformer (GAOT) is a universal approximator. My master's thesis, supervised by Dr. K. R. Arun in collaboration with Dr. Nicolas Crouseilles (Inria & ENS Rennes, France), develops asymptotic-preserving schemes for the Euler-Poisson-Boltzmann system. I am looking for PhD positions starting in 2027.

Email: devansh22 (at) iisertvm (dot) ac (dot) in

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Research

My research interests include:

  • Numerical approximation of PDEs, especially multiscale problems and asymptotic-preserving, structure-preserving schemes.
  • Scientific Machine Learning (SciML) and AI for Science, in particular the approximation theory of neural operators.
  • High-performance and scientific computing.

Awarded Fellowships

Presentation

Here are some of my recent presentations:

  1. Distributed memory parallelization of Lax-Wendroff Flux Reconstruction, on August 11, 2024 at TIFR-CAM, Bangalore, India.
Isentropic vortex (density)
Kelvin-Helmholtz instability (density)

Simulations from my TIFR-CAM project on parallelizing TrixiLW.jl. More details on the Projects page.

Some random pictures

Contact & CV

  • Please download my curriculum vitae here.
  • Feel free to write an email to me here!


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