Vivek Kumar
Associate Director
Ahmedabad, Gujarat, India
Summary
👤
Senior🎓
Top SchoolVivek Kumar is an AI R&D leader with 10+ years of hands-on experience building ML and NLP solutions for healthcare revenue cycle management, now directing GenAI strategy as Associate Director at AGS Health. He has led teams of up to 14 engineers to productionize models that cut manual coding time by 45%, onboarded 20+ healthcare clients, and implemented MLOps on AWS to accelerate deployments by ~40%. A pragmatic engineer who began in Java and transitioned to Python/PyTorch, he combines deep technical skills (modeling, ONNX, Prefect, MLflow) with product sensibility to turn POCs into scalable products. Vivek contributes to scikit-learn documentation—improving clarity on core APIs—which reflects his emphasis on reproducibility and user-facing clarity. He mentors teams on scalable, interpretable, and governed ML, and is actively exploring explainable AI for clinical and regulated domains.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Engineering - BE, Computer Engineering, 7.71, Bachelor of Engineering - BE, Computer Engineering, 7.71 at Ahmedabad Institute Of TechnologyMaster of Technology - MTech, Information Technology, Master of Technology - MTech, Information Technology at Dharmsinh Desai University
English, Hindi, Gujarati
Stackoverflow
35,893reputation
3.4mreached
637answers
1question
ubuntu
top-5%
pandas
top-5%
neural-network
top-5%
keras
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numpy
top-5%
scikit-learn
top-1%
Github Skills (27)
python10
classification10
scikit10
machine-learning10
regression10
scikit-learn10
documentation10
ubuntu9
pandas9
numpy9
tensorflow9
neural-network9
deep-learning9
keras9
nlp9
Programming languages (6)
Github contributions (5)
scikit-learn/scikit-learn
Feb 2017 - Sep 2018
scikit-learn: machine learning in Python
Role in this project:
Technical Writer
Technical WriterContributions:6 commits, 3 PRs, 19 comments in 1 year 7 months
Contributions summary:Vivek primarily contributes to documentation, updating and clarifying existing content. Their commits focus on refining the documentation for scoring parameters in `LogisticRegressionCV`, the output shape of `predict_proba` in gradient boosting and adaboost classifiers, and explaining the meaning of internal variables in `KernelPCA`. Furthermore, the user corrected documentation on the support for sparse matrices in gradient boosting's fit method. These changes enhance the clarity and accuracy of the project documentation for end-users.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
vivekk-ezdi/scikit-learn
Feb 2017 - Sep 2018
scikit-learn: machine learning in Python
Contributions:3 PRs, 9 pushes, 2 branches in 1 year 7 months
pythondata-sciencelearn-machine-learningsklearnmachine-learning
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