Gagandeep Singh is a Member of Technical Staff in Seattle with 8 years of experience building distributed storage and large-scale services, and a strong systems background spanning OS internals and Windows device drivers. He has deep C/C++/C# expertise and proven production experience in Azure Storage and enterprise storage systems at Pure Storage. An active open-source contributor, he’s fixed numerical and API issues in SciPy and NumPy, improved solver correctness in SymPy, and contributed compiler optimizations and data-structure implementations—work that demonstrates both low-level systems skill and numerical computing fluency. He also contributed to Ray’s runtime stability and cross-platform testing, reflecting practical DevOps sensibilities for distributed runtimes. Colleagues would note his blend of rigorous debugging experience from device-driver servicing and a penchant for improving math-heavy libraries, making him effective at bridging systems reliability with scientific computation.
8 years of coding experience
8 years of employment as a software developer
B.E., Computer Science, B.E., Computer Science at Punjab Engineering College
A python package for data structures and algorithms
Role in this project:
Back-end Developer
Contributions:2 releases, 357 reviews, 38 commits in 2 years 4 months
Contributions summary:Gagandeep primarily contributed to the implementation of data structures and algorithms in Python. Their work includes adding dynamic arrays, order statistics to binary search trees, and optimizing linked list operations. They also made improvements in the C++ backend for some data structures and added comprehensive documentation. The user's contributions demonstrate a focus on core data structure implementation and algorithm design.
Contributions:1086 reviews, 756 commits, 421 PRs in 9 months
Contributions summary:Gagandeep's commits focus on enhancing the Python compiler, `lpython`. Their work involves implementing a function inlining pass to optimize function calls, indicating contributions to compiler optimization techniques. They have also worked on features to support features of structs like memory layout, declaration, as well as a system for building and manipulating them. The user has integrated the concept of a "union" into the compiler, adding support for the creation and manipulation of such data structures. They also worked on code generation of a few intrinsic functions of NumPy such as ``sinh``, ``cosh``, and other math and statistics functions.
compilerpythonpython-compilerhigh-performance
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Gagandeep Singh - Member Of Technical Staff at Pure Storage