Yuhao Yang
Sunnyvale, California United States
Summary
🤩
Rockstar🎓
Top SchoolYuhao Yang is an experienced software engineer with 11 years focused on scalable ML and distributed systems, based in Sunnyvale, California. He has made substantial open-source contributions to heavyweight projects like Apache Spark and Ray, improving MLlib algorithms, performance tests, and real-world model examples such as a DCGAN tutorial. His work spans algorithm design, performance tuning, test and build integration, and technical writing—evidenced by adding LDA benchmarks, MaxAbsScaler and FPGrowth features, and fixing race conditions in Ray’s tune library. Comfortable in back-end and ML engineering roles, he blends deep academic training from Zhejiang University with pragmatic engineering that moves research-grade code toward production readiness. Less obvious: he combines careful benchmarking mindset with documentation improvements, ensuring new features are both performant and usable by other engineers.
11 years of coding experience
Bachelor of Engineering (BEng), Computer Science, Bachelor of Engineering (BEng), Computer Science at Zhejiang University
Github Skills (23)
algorithm10
algorithms10
apache-spark10
pytorch10
python10
data-science10
machine-learning10
data-structure10
lda10
ml10
scala10
performance-testing10
deep-learning10
data-structures10
ray10
Programming languages (5)
Github contributions (5)
databricks/spark-perf
May 2015 - Aug 2015
Performance tests for Apache Spark
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 1 PR, 9 comments in 2 months
Contributions summary:Yuhao implemented and extended performance tests for Apache Spark's Machine Learning library (MLlib). They introduced and refined tests for Latent Dirichlet Allocation (LDA), including both the standard and online optimization methods. The contributions involved modifying existing test frameworks and data generation to benchmark the performance of different LDA implementations within Spark. Additionally, the user incorporated changes related to build processes to incorporate these new tests.
performance-testsspark-mlapachesparkperformance
apache/spark
Jul 2015 - Dec 2017
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:11 commits, 152 PRs, 790 comments in 2 years 4 months
Contributions summary:Yuhao primarily contributed to the Apache Spark MLlib library, focusing on improvements and additions related to machine learning and data processing functionalities. They worked on various aspects of the library, including optimization, bug fixes, and the implementation of new features such as the MaxAbsScaler and FPGrowth model. Their contributions often involved algorithm design, performance tuning, and code refactoring within the context of ML algorithms. They added documentation, tests, and compatibility fixes.
analyticspythondata-processingsqlapache
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