Hao Gong
Co-director Of NVIDIA AI Technology Center (NVAITC) Japan
Chiyoda, Japan
Summary
🤩
Rockstar🎓
Top SchoolHao Gong is a machine learning and systems architect with nine years of experience, now co-directing NVIDIA AI Technology Center (NVAITC) Japan after serving as a Senior Solutions Architect for deep learning. He blends academic rigor from a Doctor of Science in life and environmental sciences with hands-on engineering in industrial ML: meta-learning, multimodal pre-training, user-behavior pre-training, recommender systems, and geo-modeling for automotive and remote sensing. Hao has practical backend experience optimizing performance on GPU and OpenCL projects—contributing benchmarks and kernel-level improvements to notable repos like cuDF and pyopencl—which reflects a focus on production scalability. Comfortable managing cross-cultural, multitask programs, he pairs consulting and project leadership with deep technical delivery to move research into deployable platforms. An intriguing strength is his cross-domain fluency: applying life-sciences-rooted research instincts to spatial and user-centric ML challenges in industry.
9 years of coding experience
Doctor of Science Graduate School of Life and Environmental Sciences, Doctor of Science Graduate School of Life and Environmental Sciences at University of Tsukuba
Chinese, English, Japanese, Shanghainese
Github Skills (18)
algorithm10
opencl10
algorithms10
benchmark10
c-language10
python10
dataframes10
cudf10
dataframe10
parallel-processing10
parallel-computing10
gpu10
cuda10
cprogramming-language10
testing9
Programming languages (3)
Github contributions (5)
rapidsai/cudf
Jun 2019 - Aug 2021
cuDF - GPU DataFrame Library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:44 reviews, 38 commits, 8 PRs in 2 years 2 months
Contributions summary:Hao's primary contribution focused on adding a join benchmark to the cuDF library. This involved implementing and refining code related to generating input tables for join operations, specifically within the context of GPU-accelerated DataFrame processing. The commits reveal the addition of benchmarking infrastructure and improvements to error checking. The changes showcase a focus on optimizing performance, particularly in the area of join operations.
cudadataframe-librarydata-analysiscppcudf
inducer/pyopencl
Nov 2017 - Feb 2018
OpenCL integration for Python, plus shiny features
Role in this project:Backend Developer
Backend DeveloperContributions:14 commits in 3 months
Contributions summary:Hao primarily contributed to the `pyopencl` repository by implementing and refining features related to OpenCL algorithms. Their work includes adding and modifying test cases, fixing list builder bugs, improving variable naming, enhancing documentation, and making the codebase compatible with Python 2. A significant portion of the commits focuses on the `ListOfListsBuilder` class, showcasing their involvement in performance optimization and OpenCL kernel modifications.
amdarraypythonreductionopencl
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