Utkarsh Gupta
Principal Engineer at CRED
Bengaluru, Karnataka, India
Summary
🤩
Rockstar🎓
Top SchoolUtkarsh Gupta is a Senior Software Engineer with a decade of hands-on experience building reliable backend systems, currently at Graviton Research Capital in Gurugram. He blends competitive programming rigor with production engineering, having taught CP and DSA to thousands via a popular YouTube channel and served as a CodeChef educator. His open-source contributions include modernizing the BIF reader/writer in pgmpy, improving file compatibility and maintainability for a key Bayesian networks library. Comfortable across Java/Spring and Python stacks, he has practical payments experience from an Uber internship and a track record of shipping bug fixes and refactors in complex codebases. Known for concise, teachable explanations, he pairs algorithmic depth with pragmatic software craftsmanship.
10 years of coding experience
7 years of employment as a software developer
Intermediate, Intermediate at HAL School Korwa, AmethiBachelor of Technology (BTech) Information Technology, Bachelor of Technology (BTech) Information Technology at Motilal Nehru National Institute Of TechnologyHigh School, High School at Kendriya Vidyalaya AFS Ojhar, Nashik
English, Hindi
Stackoverflow
141reputation
2kreached
0answers
2questions
Github Skills (9)
bayesian-network10
python10
xml8
data-structure7
data-structures7
urllib6
multithreading6
python-unittest6
python-requests6
Programming languages (8)
Github contributions (5)
pgmpy/pgmpy
Nov 2015 - Feb 2019
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:106 commits, 55 PRs, 9 pushes in 3 years 3 months
Contributions summary:Utkarsh primarily focused on modifying and refactoring code related to reading and writing files in BIF format. Their work included replacing deprecated modules and addressing compatibility issues, indicating an effort to modernize the codebase. The commits also involved fixing bugs and improving the implementation of specific functionalities, like the handling of variable properties. This suggests a focus on improving the reliability and maintainability of the library's BIF reader and writer modules.
causal-modelspythondagbayesian-inferencecausal
AntidoteLabs/Antidote-DM
Nov 2015 - Jan 2016
Contributions:40 commits, 29 PRs, 23 pushes in 1 month
lotantidotedownloaderdownload-manager
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