Tanvi Kumar
Senior Software Engineer at Microsoft
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolTanvi Kumar is a Senior Software Engineer based in Bengaluru with nine years of experience building full-stack systems and machine learning tooling, currently advancing core services at Microsoft. A NIT Trichy alum and GSoC'18 contributor, she blends production-grade backend work with front-end UX improvements—evident from contributions to p5.js DOM features and ML example refinements in the popular "Dive into Deep Learning" lineage. Her background spans algorithmic problem-solving in C/C++, web engineering, and leadership stints such as Interim CTO at Mentor Match India, showing she navigates both code and product strategy. Colleagues would note her attention to code clarity and developer experience, from replacing hard-coded constants to adding visualization helpers that make ML examples more accessible.
9 years of coding experience
8 years of employment as a software developer
Bachelor of Technology (BTech) CE CSE Minor, Bachelor of Technology (BTech) CE CSE Minor at National Institute of Technology, TiruchirappalliSenior Secondary Schooling, Senior Secondary Schooling at D.A.V. Senior Secondary School, Mogappair, Chennai
Stackoverflow
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Github Skills (32)
algorithm10
javascript10
c-language10
bit-manipulation10
python10
mxnet10
machine-learning10
p5js10
c1110
data-structure10
c1710
mask-rcnn10
dom-manipulation10
coding10
deep-learning10
Programming languages (6)
Github contributions (5)
processing/p5.js
Jun 2018 - Dec 2018
p5.js is a client-side JS platform that empowers artists, designers, students, and anyone to learn to code and express themselves creatively on the web. It is based on the core principles of Processing. http://twitter.com/p5xjs —
Role in this project:
Front-end Developer
Front-end DeveloperContributions:9 reviews, 18 commits, 15 PRs in 6 months
Contributions summary:Tanvi primarily contributed to the p5.js library by implementing and improving DOM-related functionalities. Their work includes adding the `createColorPicker` element with associated methods and examples, enhancing its usability. They also modified existing examples for `createFileInput` and `loadModel`, and updated existing color examples. Furthermore, they improved file load error methods and added options for text styling.
designersprinciplesartclient-sidecanvas
zackchase/mxnet-the-straight-dope
Nov 2017 - Dec 2017
An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.
Role in this project:ML Engineer
ML EngineerContributions:6 commits, 4 PRs, 1 comment in 20 days
Contributions summary:Tanvi made several contributions focused on refining and improving the provided deep learning examples. They corrected code usage, removed unused variables, and added code for model prediction visualization. Furthermore, they replaced constants with variables to enhance code readability and made minor indentation changes. These changes indicate a focus on code clarity and functionality within the context of machine learning model implementation.
pytorchd2lmxnetdeep-learninghas-content
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