Jian Li is a fifth-year Ph.D. candidate at the University of Chinese Academy of Sciences specializing in scalable, theoretically grounded machine learning, with five peer-reviewed papers at NeurIPS, IJCAI and AAAI and multiple arXiv preprints. He focuses on efficient large-scale ML, kernel methods, semi-supervised learning, interpretability, and building optimization tools that bridge theory and application. With seven years of engineering experience and a background in game development, he combines practical software chops with rigorous research instincts. Jian is also an active open-source contributor and an Apache Hadoop committer, having improved Router reliability and asynchronous RPC performance for a project used broadly in big-data ecosystems. Colleagues describe him as perpetually in “apprentice” mode—continually learning while delivering robust, scalable systems.
7 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Machine Learning, a fifth-year Ph.D. student, Doctor of Philosophy - PhD, Machine Learning, a fifth-year Ph.D. student at University of Chinese Academy of Sciences
Bachelor's degree, Software Engineering (English), Bachelor's degree, Software Engineering (English) at Northeastern University (CN)
Contributions:136 reviews, 90 PRs, 26 pushes in 2 years 8 months
Contributions summary:Jian primarily contributed to the Apache Hadoop project by addressing critical issues and implementing improvements within the Router component. These changes involve bug fixes related to failover scenarios, specifically resolving `NoNamenodesAvailableException` issues and addressing quorum problems. The user also introduced enhancements for the asynchronous RPC protocol, enhancing the overall performance and reliability of the Router. The commits also include fairness policy improvements and testing.
Contributions:14 PRs, 169 pushes, 36 branches in 2 years 6 months
apachebig-datasparkhadoopjava
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