Nan Zhu - Software Engineer at NVIDIA

Nan Zhu

Software Engineer at NVIDIA

Seattle, Washington, United States

Join Prog.AI to see contacts

Summary

🤩

Rockstar

🎓

Top School

Nan Zhu is a seasoned software engineer and distributed systems expert with 14 years building high-performance data infrastructure and ML tooling, now based in Seattle. He has driven production-scale improvements at companies like Uber, Pinterest, Microsoft and NVIDIA, focusing on Spark services, XGBoost JVM integrations, and AI research infrastructure. An active open-source committer, Nan has made substantive backend and performance contributions to flagship projects including Apache Spark, Apache Iceberg, XGBoost and MXNet—work that spans executor/resource management, table/schema evolution, and JVM API design. He combines deep academic training (PhD-level research) with hands-on platform leadership, having led teams and technical efforts to boost performance by multiple folds in large-scale environments. Notably, he helped make XGBoost more portable on the JVM and improved Spark internals for stability and profiling, reflecting a talent for both low-level fixes and system-wide architecture.

13 years of coding experience

15 years of employment as a software developer

Master Computer Science, Master Computer Science at Shanghai Jiao Tong University

Bachelor's degree Electrical Electronics and Communications Engineering, Bachelor's degree Electrical Electronics and Communications Engineering at Nanjing Institute of Technology

Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at McGill University

English

Github Skills (37)

apache-spark10

c-language10

mxnet10

distributed-systems10

travis-ci10

apache10

nodemanager10

java10

cicd10

scala10

javas10

deep-learning10

performance-optimization10

tab-management10

params10

Programming languages (11)

JavaC++ShellRustScalaGoHTMLJupyter Notebook

Github contributions (5)

Azure/azure-event-hubs-spark

Nov 2016 - Sep 2017

Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs

Role in this project:

DevOps Engineer & Test Automation Engineer

Contributions:174 commits, 170 PRs, 182 pushes in 10 months

Contributions summary:Nan primarily contributed to the project by adding and configuring Travis CI for automated testing. They also focused on applying code style guidelines using Scalastyle. Further contributions included fixing flaky tests and addressing configuration issues related to maximum event rates. The user's work improved the project's testing infrastructure and build process.

event-hubsstreammicrosoftreal-timebigdata

dmlc/xgboost

Dec 2015 - Nov 2020

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Role in this project:

Back-end Developer

Contributions:14 reviews, 203 commits, 465 PRs in 5 years

Contributions summary:Nan's commits re-structured the Java API, added a Scala API, and consolidated the Java/Scala API names within the `xgboost` project. This involved modifying the `JavaBoosterImpl.java` to handle the new APIs. Furthermore, the user added style checks for Java and Scala code to maintain code quality. Additional commits also involved renaming files and packages.

xgboostpythonflinkdaskdataflow

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.

Request Free Trial