Abhinav Sagar
Research at Vrije Universiteit Brussel
Belgium
Summary
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Rockstar🎓
Top SchoolAbhinav Sagar is a research-focused computer vision and machine learning engineer based in Belgium with seven years of experience and a current research appointment at Vrije Universiteit Brussel. He has combined industry roles at Spyne and internships at InterDigital and Instacart with hands-on ML engineering, shipping production vision systems and algorithmic improvements. An active open-source contributor, he’s worked across notable projects from the artist-friendly p5.js front end to OpenAI Gym environments and the C++ mlpack library, showing rare breadth across JS tooling, RL environments, and low-level ML code. Colleagues describe him as pragmatic and detail-oriented — he frequently improves tests, docs, and linters in addition to core implementations, bridging creative tooling and rigorous research code.
7 years of coding experience
1 year of employment as a software developer
University of Maryland
French, Hindi, English
Stackoverflow
31reputation
9kreached
4answers
1question
Github Skills (37)
algorithm10
creativecloud10
environmental10
algorithms10
machine-learning-model10
javascript10
c-language10
dev-environment10
python10
datastructure10
openai-gym10
machine-learning10
p5js10
datastructures10
reinforcement-learning10
Programming languages (15)
Github contributions (5)
openai/gym
May 2019 - Jul 2019
A toolkit for developing and comparing reinforcement learning algorithms.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 7 commits, 25 PRs in 2 months
Contributions summary:Abhinav primarily contributed to the environment files, implementing and modifying game environments within the OpenAI Gym library. Their work includes updating documentation, fixing constants, and adding constraints. They also modified the `car_racing.py`, `acrobot.py`, `pendulum.py`, `continuous_mountain_car.py`, and `mountain_car.py` files, indicating a focus on enhancing and improving the existing environments. This includes fixing errors and adding new features like the velocity goal constraint.
comparingreinforcement-learning-algorithmsdevelopingdeep-learningreinforcement-learning
processing/p5.js
Jun 2019 - Aug 2019
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:Full-stack Developer
Full-stack DeveloperContributions:17 commits, 20 PRs, 10 comments in 2 months
Contributions summary:Abhinav contributed to the p5.js library by updating core JavaScript files such as `p5.Matrix.js`, `mouse.js`, and `p5.Element.js`, indicating a focus on the library's core functionality. They fixed typos in the `p5.Vector.js` test suite and modified the documentation-related `documented-method.js`, showing attention to code quality and developer experience. The user also updated linting configurations in `sample-linter.js` and made improvements to the test suite, demonstrating contributions across multiple aspects of the project.
designersprinciplesartclient-sidecanvas
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