Subraman
Scientific Research at Self-employed
Norcross, Georgia, United States
Summary
👤
Senior🎓
Top SchoolSubraman is a research-driven ML engineer and educator with over 8 years of professional experience and a PhD in Electrical and Computer Engineering from McMaster University. Based in Norcross, Georgia, he focuses on big data and data science research, bringing hands-on expertise in Python, Spark, Hadoop ecosystem tools, streaming platforms like Kafka and Storm, and a wide range of databases. He has a long history of self-directed scientific research and undergraduate/graduate teaching dating back to the late 1990s, blending academic rigor with practical system-building. An active open-source contributor, he improved MLflow usability and model-registry functionality, demonstrating attention to developer experience and production ML workflows. His background spans both computer science and electrical engineering foundations, enabling cross-disciplinary approaches to problems in systems, security, and distributed computing. Colleagues value his ability to translate complex research into teachable material and usable tooling for real-world ML lifecycles.
8 years of coding experience
Doctor of Philosophy (PhD), Electrical and Computer Engineering, Doctor of Philosophy (PhD), Electrical and Computer Engineering at McMaster UniversityB.Sc.Eng.(Hons), Computer Science and Engineering, B.Sc.Eng.(Hons), Computer Science and Engineering at University of MoratuwaToronto Metropolitan University
Github Skills (7)
machine-learning10
mlflow10
model-management10
python10
api8
apidoc8
documentation7
Programming languages (2)
Github contributions (5)
mlflow/mlflow
Apr 2022 - Sep 2022
Open source platform for the machine learning lifecycle
Role in this project:
ML Engineer
ML EngineerContributions:44 reviews, 9 commits, 15 PRs in 5 months
Contributions summary:Subraman's contributions primarily focused on improving and expanding the MLflow platform. They fixed typos, corrected imports, and enhanced documentation. The user added examples for the `create_experiment` and `start_run` features, incorporating tags. Additionally, they made changes related to the model registry, including supporting stage parameters in the `set_model_version_tag` feature. These changes suggest a focus on improving usability and functionality for ML model management within the MLflow ecosystem.
pythonlifecyclemlmachine-learningincremental-learning
subramaniam02/mlflow
Apr 2022 - Feb 2023
Open source platform for the machine learning lifecycle
Contributions:13 PRs, 117 pushes, 14 branches in 10 months
pythonlifecyclemlmachine-learningmachine-learning-lifecycle
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.