Rohit Singh is a software engineer with 11 years of experience based in Noida, India, currently working at MIT in a role labeled "rel." He brings deep expertise in probabilistic programming and ML infrastructure, evidenced by substantive contributions to the widely used pyro-ppl/pyro repository where he improved inference robustness, handled discrete enumeration edge cases, and enhanced tutorials like SS-VAE. Rohit pairs practical engineering with research-minded rigor, adding utilities (clipped softmax/sigmoid) and optimizing critical code paths to stabilize complex workflows. Colleagues can rely on him for hard-to-reproduce bug fixes and for making advanced probabilistic tools more usable for practitioners. He balances low-level implementation care with clear attention to pedagogical materials, showing a drive to both harden libraries and help others adopt them.
Deep universal probabilistic programming with Python and PyTorch
Role in this project:
ML Engineer
Contributions:11 commits, 4 PRs, 5 pushes in 5 months
Contributions summary:Rohit primarily contributed to the `pyro-ppl/pyro` repository, focusing on improving the library's functionality and stability. They addressed issues related to inference, particularly handling edge cases like empty models or guides and ensuring the correct behavior of enumeration with discrete variables. The user also added utilities like clipped softmax and sigmoid, improved the SS-VAE tutorial, and optimized existing code to address various issues within the probabilistic programming framework. Their work demonstrates a strong understanding of probabilistic modeling and deep learning concepts.
Contributions:87 pushes, 2 branches in 9 years 10 months
templatejekylljekyll-themejekyll-template
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.