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Hi there 👋

I am Gagandeep, a Software Engineer at @Quansight. I am also core developer of LFortran/LPython/LC. Take a look at some of my work below,

Current Work

  • Quansight - Software Engineer II. Working on SciPy & NumPy along side client projects.
  • LFortran - Core Developer. LFortran is a modern open-source (BSD licensed) interactive Fortran compiler built on top of LLVM.
  • LPython - Core Developer. LPython is an ahead-of-time compiler for Python written in C++.
  • LC - Core Developer. LC is the C and C++ frontend to LCompilers.

Personal Work

  • PyDataStructs - PyDataStructs, as the name suggests is a python package for data structures and algorithms. You can learn more about it on the project's website/documentation https://pydatastructs.readthedocs.io/en/latest/. It has participated in Google Summer of Code, 2022.

Past Work

Contacts for Collaboration

If you want to work on some of my ongoing projects then feel free to reach out to me on my email which is, [email protected].

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ਗਗਨਦੀਪ ਸਿੰਘ (Gagandeep Singh)'s Projects

bff icon bff

Standalone AI Counseller

bnn icon bnn

Implementation of Binarized Neural Networks

carte icon carte

Simple Jekyll-based documentation site for APIs.

cmake icon cmake

Mirror of CMake upstream repository

csp icon csp

csp is a high performance reactive stream processing library, written in C++ and Python

dftatom icon dftatom

Routines for Radial Integration of Dirac, Schrödinger, and Poisson Equations

dragon-book-exercise-answers icon dragon-book-exercise-answers

Compilers Principles, Techniques, & Tools (purple dragon book) second edition exercise answers. 编译原理（紫龙书）第2版习题答案。

fpm icon fpm

Fortran Package Manager (fpm)

india icon india

GitHub resources and information for the developer community in India

just-the-docs icon just-the-docs

A modern, high customizable, responsive Jekyll theme for documention with built-in search.

libasr icon libasr

The ASR (Abstract Semantic Representation), backends, optimizations and other tooling

linkpred icon linkpred

Simple yet efficient algorithms for Link Prediction in Dynamic Graphs

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