Giang Truong
Senior Software Engineer at NVIDIA
Western Australia
Summary
🤩
Rockstar🎓
Top SchoolGiang Truong is a Senior Software Engineer with 11 years of experience specializing in GPU-accelerated data processing and perception for autonomous driving at NVIDIA. He holds a PhD in Computer Science and has strong research roots in deep learning for robust estimation, 3D scene understanding, registration and localization. An active open-source contributor, Giang has improved high-profile projects like NVIDIA's Spark RAPIDS and cuDF—implementing SQL string functions, statistics aggregations, and performance fixes that enhance GPU DataFrame and Spark acceleration. He blends deep research experience with production-grade backend engineering, having applied ML to medical imaging during a research fellowship and to real-world perception systems at NVIDIA. Based in Western Australia, he pairs technical rigor with a quirky personal touch as a self-described computer and food enthusiast.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Engineering - BE, Electrical and Electronics Engineering, Excellent, Bachelor of Engineering - BE, Electrical and Electronics Engineering, Excellent at Ho Chi Minh University of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Edith Cowan University
Github Skills (21)
algorithm10
algorithms10
apache-spark10
c-language10
data-structure10
java10
javas10
rapids10
aggregations10
cuda10
data-structures10
datastructures-algorithms10
cprogramming-language10
gpu-acceleration10
data-engineering9
Programming languages (5)
Github contributions (5)
rapidsai/cudf
Feb 2021 - Jan 2023
cuDF - GPU DataFrame Library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:4520 reviews, 141 commits, 232 PRs in 1 year 11 months
Contributions summary:Giang primarily focused on enhancing the cuDF library, making significant contributions to the functionality and efficiency of its data structures and operations. Their work included implementing and optimizing core features, such as the `HISTOGRAM` and `MERGE_HISTOGRAM` aggregations, as well as improvements to existing APIs such as `cudf::contains` and `lists::distinct`. They also addressed memory issues and code inefficiencies within the ORC writer, focusing on performance improvements and bug fixes in the core library's functionality.
cudadataframe-librarydata-analysiscppcudf
NVIDIA/spark-rapids
Aug 2021 - Jan 2023
Spark RAPIDS plugin - accelerate Apache Spark with GPUs
Role in this project:Back-end Developer
Back-end DeveloperContributions:373 reviews, 14 commits, 86 PRs in 1 year 5 months
Contributions summary:Giang implemented several features and made improvements related to string manipulation functions within the Spark RAPIDS plugin. This included adding support for the `repeat` SQL function and implementing relevant code. They also worked on extending the plugin to support `stddev` and `variance` aggregations, as well as the `str_to_map` function. These contributions directly enhance the plugin's capabilities for GPU-accelerated data processing within Apache Spark.
gpu-accelerationgpuapachebig-dataspark
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