Kazuaki Ishizaki
Senior Technical Staff Member at The Apache Software Foundation
Tokyo, Japan
Summary
🤩
Rockstar🎓
Top SchoolKazuaki Ishizaki is a Senior Technical Staff Member at IBM and an ACM Distinguished member with over two decades of compiler-focused research and 11 years of industry experience driving performance in large-scale data and deep learning systems. A Java JIT specialist by training (Ph.D., Waseda University), he has spent 25+ years on JVM compilation and modernized inference pipelines to accelerate PyTorch and TensorFlow on hardware accelerators. He contributes to flagship open-source projects—Apache Spark and Arrow committer, and documentation/bug fixes in TensorFlow and PyTorch—bringing a rare blend of low-level code generation, runtime optimization, and practical docs hygiene. His work on Spark SQL code generation and Parquet filter integration demonstrates measurable query-performance improvements, while earlier efforts exploited SIMD and s390 instructions for enterprise workloads. Based in Tokyo, he combines deep academic rigor with hands-on engineering that bridges compilers, managed runtimes, and GPU/accelerator deployment.
11 years of coding experience
18 years of employment as a software developer
Ph.D, Information and computer science, Ph.D, Information and computer science at Waseda University
Japanese, English
Github Skills (37)
spark-sql10
c-language10
testing10
bash10
cicd10
java10
scala10
apache-arrow10
javas10
j10
automation10
tensorflow10
japa10
performance-optimization10
automations10
Programming languages (19)
Github contributions (5)
apache/spark
Nov 2016 - Jan 2021
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:36 reviews, 21 commits, 205 PRs in 4 years 2 months
Contributions summary:Kazuaki primarily contributed to the Apache Spark codebase, focusing on performance optimization. Their work involved implementing and optimizing features related to filtering queries, specifically optimizing the "where in clause filter queries" in Spark SQL. They also worked on using Parquet-mr filter2 API to further improve the performance of queries with filters, including implementing support for custom filters. Additionally, the user contributed to addressing memory usage issues in the generated code and other general code improvements.
analyticspythondata-processingsqlapache
apache/arrow
Dec 2019 - Jan 2023
Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics
Role in this project:Technical Writer
Technical WriterContributions:102 reviews, 67 commits, 80 PRs in 3 years 1 month
Contributions summary:Kazuaki's commits primarily focused on fixing typos, broken links, and adding missing periods in the project's documentation. They addressed issues across various documentation sections, including code examples, developer guides, and format specifications. The contributions improve the readability and accuracy of the project documentation, which is crucial for user understanding and project maintainability. The changes are consistent across multiple file types.
memorymulti-languagetoolboxacceleratedarrow
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