Utkarsh Upadhyay
Stealth at Grand Teton Systems Inc
Cottbus - Chóśebuz, Brandenburg, Germany
Summary
👤
Senior🎓
Top SchoolUtkarsh Upadhyay is a machine learning researcher and engineer with 16 years of experience building models and methods for large-scale real-world networks, currently working at a stealth startup after co-founding and leading engineering at Reasonal. His PhD work at the Max Planck Institute focused on information and knowledge dissemination online, and he has a strong track record translating that research into production: from analytics-driven single-page apps to contributions in core open-source projects like scikit-learn and CPython. Notably, he enhanced scikit-learn’s semi-supervised learning module by adding arbitrary kernel support and stability fixes, and improved Python’s datetime test coverage, reflecting a pragmatic attention to quality and reproducibility. Based in Cottbus, Germany, he blends deep academic training with startup execution and consultancy, often tackling hard problems in networked systems and ML at scale. A detail that sets him apart: his open-source work spans both algorithmic innovation and the test/QA engineering that makes those algorithms reliable in the wild.
15 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Machine Learning on Networks, Doctor of Philosophy (Ph.D.) Machine Learning on Networks at Max Planck SocietyIndian Institute of Technology KanpurMS Computer Science, MS Computer Science at EPFL
English, Hindi
Stackoverflow
34,198reputation
2.9mreached
558answers
20questions
meteor
top-5%
jquery
top-5%
label
top-5%
r
top-5%
javascript
top-1%
html
top-1%
Github Skills (37)
datetime10
javascript10
python10
scikit10
testing10
machine-learning10
datetimes10
angularjs-directive10
semi-supervised-learning10
iframe10
svg10
angularjs10
scikit-learn10
html10
test-automation10
Programming languages (18)
Github contributions (5)
scikit-learn/scikit-learn
Sep 2016 - Oct 2018
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:9 commits, 7 PRs, 97 comments in 2 years 1 month
Contributions summary:Utkarsh contributed significantly to the semi-supervised learning module within scikit-learn, enhancing its functionality. They added the capability to use arbitrary kernel functions, alongside the existing options. The user also fixed a critical bug related to alpha deprecation and convergence warnings, while also increasing the `max_iter` parameter for the `LabelPropagation` algorithm. The work also included improvements to the documentation and test suites, indicating a focus on the quality and usability of the semi-supervised learning models.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
python/cpython
May 2017 - Sep 2017
The Python programming language
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:10 PRs, 37 comments in 4 months
Contributions summary:Utkarsh primarily contributed to enhancing the testing framework and ensuring the reliability of the `datetime` module within the Python standard library. Their work involved fixing existing tests, adding new test cases, and modifying the test setup to improve test coverage and execution. These commits focus on addressing specific issues, such as ensuring tests run correctly across different implementations and updating documentation to reflect code changes.
python-programmingprogramming-languagepythonpython-programming-language
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.