Pranav
Computer Scientist
Ahmedabad, Gujarat, India
Summary
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RockstarPranav is a computer scientist with four years of experience building numerical back-end systems that span compiler internals and production ML engineering. A computer science grad from IITJ, he has industry experience as an MLE at Warner Bros. Discovery and research internships including Summer '24 at Quansight Labs, plus GSoC '23 with fortran-lang. He contributes to LFortran (implementing double-precision support, implicit statements, statement functions and implied do loops) and to stdlib-js (JSON serialization/revival for double-precision, tests, benchmarks and docs), demonstrating a focus on numerical correctness and cross-platform robustness. Notably, he pairs low-level fixes like resolving Windows test failures with high-level benchmarking and documentation, making complex numeric features reliable in both open-source compilers and production libraries.
4 years of coding experience
Github Skills (20)
json10
javascript10
fortran-200810
testing10
fortran10
fortran201810
fortran9010
fortran7710
compiler-compiler10
javascripts10
fortran-7710
compiler10
fortran9510
compilers10
benchmark9
Programming languages (13)
Github contributions (5)
lfortran/lfortran
Aug 2022 - Jan 2023
Official main repository for LFortran
Role in this project:
Back-end Developer
Back-end DeveloperContributions:4 releases, 1674 reviews, 71 commits in 5 months
Contributions summary:Pranav primarily contributed to the LFortran compiler project by implementing and fixing features related to double-precision floating-point numbers and intrinsic functions. They added tests for double-precision calculations and fixed an error occurring in windows while performing the tests. The user also added support for the `Variable` symbol and implemented implicit statements. Additionally, they implemented statement functions and implied do loops, improving the functionality of the Fortran compiler.
apljupyter-notebookcompilerfortranrepl
stdlib-js/stdlib
Oct 2022 - Jan 2023
✨ Standard library for JavaScript and Node.js. ✨
Role in this project:Back-end Developer
Back-end DeveloperContributions:775 reviews, 48 commits, 117 PRs in 3 months
Contributions summary:Pranav focused on adding support for serializing and reviving double-precision floating-point numbers to and from JSON format. The user created implementations for both the serialization (`to-json`) and deserialization (`reviver`) functions, and created tests, benchmarks, and documentation. Their work contributed directly to the functionality and utility of the project's standard library, specifically in handling numerical data types. Additionally, the user implemented various special functions and utilities, demonstrating a focus on mathematical computations within the library.
numerical-computingmathematicsutilitiesstatisticsscience
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