Jonathan Wapman
Software Engineer at Waymo
United States
Summary
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Rockstar🎓
Top SchoolJonathan Wapman is a software engineer with nine years of experience specializing in motion planning and high-throughput GPU compute for autonomous systems, currently building trajectory generation and low-latency systems at Waymo. He brings deep GPU and parallel-computing expertise from graduate research at UC Davis and multiple NVIDIA architecture internships, where he modeled novel dataflow and load-balancing approaches for graph analytics and sparse linear algebra. An active contributor to the Gunrock CUDA graph analytics project, he implemented multi-device CUDA context management and expanded input-format support, reflecting a practical blend of systems-level optimization and open-source impact. His background spans robotics, control, and spacecraft-relevant research (JPL, LLNL), giving him a rare cross-domain perspective on real-time autonomy, graph analytics, and AI-driven perception.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS, Electrical and Electronics Engineering, Bachelor of Science - BS, Electrical and Electronics Engineering at University of California, DavisLivermore High School
English, Spanish, German
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
cuda10
graphdb10
graph10
graph-algorithms10
c-language10
graph-analysis10
parallel-computing10
cprogramming-language10
gpu10
algorithm9
cmake7
Programming languages (7)
Github contributions (5)
gunrock/gunrock
Jan 2019 - May 2022
Programmable CUDA/C++ GPU Graph Analytics
Role in this project:
Back-end Developer
Back-end DeveloperContributions:9 reviews, 164 commits, 9 PRs in 3 years 4 months
Contributions summary:Jonathan's contributions focus on modifying and enhancing the Gunrock library, primarily related to graph analytics on GPUs. They updated CUDA context management, including support for multiple devices and streams. Additionally, the user implemented the ability to read SMTX files, expanding the input format capabilities for the library. Furthermore, the user fixed namespace collisions within the CUDA codebase, improving code clarity.
graph-primitivescxxgraph-algorithmsgraph-analyticsgpu-acceleration
jdwapman/gunrock
Jan 2019 - Apr 2019
High-Performance Graph Primitives on GPUs
Contributions:108 pushes, 16 branches in 3 months
cudagraph-primitivesgpu-programminggpu-accelerationgpu
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