Ketan Mittal
Computational Mathematician
San Jose, California, United States
Summary
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Rockstar🎓
Top SchoolKetan Mittal is a computational mathematician with 9 years of experience developing high-order finite element methods, adaptive mesh optimization, and data-driven hp-adaptivity at Lawrence Livermore National Laboratory. He combines deep numerical analysis and HPC performance engineering—contributing backend optimizations to the widely used MFEM C++ finite element library—with applied research in Lagrangian hydrodynamics and shape/topology optimization. His work spans algorithm design (hrp-adaptivity, immersed boundary methods) and practical performance improvements such as memory allocation and solver tuning. Trained with a PhD from UIUC, he has a track record of automating complex mesh generation for challenging geometries and applying reinforcement learning to adaptivity, blending theoretical rigor with production-ready implementation.
9 years of coding experience
9 years of employment as a software developer
Texas A&MUniversity of Illinois Urbana-ChampaignBachelor of Science (B.S.), Mechanical Engineering, 3.86/4, Bachelor of Science (B.S.), Mechanical Engineering, 3.86/4 at University of Nevada-Reno
English, Hindi, Punjabi
Github Skills (15)
finite-element-analysis10
cluster-computing10
differential-equations10
mathematical10
c-language10
cprogramming-language10
numerical-methods10
performance-optimization10
linear-algebra10
computational-science10
modeling10
scientific-computing10
c-templates9
parallel-computing9
cpp-templates9
Programming languages (7)
Github contributions (5)
mfem/mfem
Jul 2017 - Jan 2023
Lightweight, general, scalable C++ library for finite element methods
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:206 reviews, 804 commits, 70 PRs in 5 years 7 months
Contributions summary:Ketan implemented and optimized the performance of solvers and integrators within the MFEM library, specifically focusing on solving partial differential equations with finite element methods. This involved adding functionality for various solvers, including the LBFGS solver, and enabling specific performance optimizations like adaptive surface fitting, highlighting a focus on mathematical and computational aspects. Furthermore, the user made several adjustments in the implementation of the interface and documentation to facilitate further development of the framework. The user also focused on improving the memory allocations of the library.
c-plus-plusfinitefemamrc-library
kmittal2/mfem
May 2017 - Aug 2024
Contributions:46 pushes, 12 branches in 7 years 4 months
scalablecppc-libraryfinite-element-methodsc-plus-plus
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