Kai Jiang
CEO at Nuovo Film Inc.
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top SchoolKai Jiang is a CEO and seasoned technology leader with 11 years of hands-on software and data engineering experience and a broader career spanning management consulting and supply chain architecture. Based in Oakland, he blends executive strategy with deep technical contributions to high-profile open-source projects like Servo, Apache Beam, and Apache Spark, focusing on backend refactors, security-hardening, and ML/parallel-processing APIs. His background includes senior strategic roles at Atmel and consulting at McKinsey, plus supply chain leadership at Xilinx and Stanford, giving him a rare combination of operational rigor and engineering fluency. He holds a PhD in Operations Management from Stanford, which informs his systematic approach to scalable systems and data-driven product decisions. Notably, his open-source work touches core browser engine internals and distributed data processing libraries, demonstrating an ability to improve both performance and security at the infrastructure level. He is entrepreneurial, technically curious, and adept at translating complex research-grade ideas into production-ready software and business outcomes.
11 years of coding experience
2 years of employment as a software developer
Tsinghua UniversityPhD Operations Management, PhD Operations Management at Stanford University
Stackoverflow
364reputation
22kreached
3answers
4questions
Github Skills (33)
apache-spark10
data-pipelines10
servo10
python10
data-science10
big-data10
machine-learning10
pyspark10
browser10
webengine10
ml10
rust10
webassembly10
data-pipeline10
apache-beam10
Programming languages (9)
Github contributions (5)
apache/beam
Jan 2017 - Mar 2020
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 reviews, 44 commits, 47 PRs in 3 years 2 months
Contributions summary:Kai contributed to Apache Beam by adding side input functionality to Combine, GroupedValues, and PerKey transforms. They refactored existing code to use AutoValue, reducing boilerplate in BoundedReadFromUnboundedSource. The user also refactored EmptyOnDeserializationThreadLocal to util, along with using ThreadLocal for Marshaller/Unmarshaller in JAXBCoder and added variance population and variance sample built-in aggregation functions.
golangpythonstreaming-databeambatch
apache/spark
Sep 2015 - Jun 2018
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:20 PRs, 150 comments in 2 years 9 months
Contributions summary:Kai primarily contributed to the Apache Spark MLlib project, implementing and improving machine learning algorithms. Their work included the development of a Python API for AFTSurvivalRegression, changes to the range of quantile probabilities, and the implementation of Python APIs for RandomForest and GBT-related parameters. The user also added support for model save/load functionality in PySpark for FPGrowth, RandomForestClassifier, RandomForestRegressor, and implemented the PySpark API for GeneralizedLinearRegression.
analyticspythondata-processingsqlapache
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