Daniel Zou is a system software engineer focused on AI infrastructure and robot perception, currently building scalable platforms at NVIDIA after a decade of hands-on experience. He brings research rigor from UC Berkeley—coauthoring Computron and contributing to Alpa and NumS—into production systems that support thousands of on-call engineers and large-scale model serving. His background spans distributed numerical libraries, sparse-aware tensor scheduling, and on-call automation, reflecting a blend of systems-level engineering and applied machine learning. Notably, he has led robotics software teams and administered campus-scale GPU and web infrastructure, showing comfort across hardware, low-level systems, and applied CV pipelines.
11 years of coding experience
3 years of employment as a software developer
B.S., Electrical Engineering and Computer Sciences (EECS), B.S., Electrical Engineering and Computer Sciences (EECS) at University of California, Berkeley
Part-time graduate level coursework with a focus on robotics and ML., Part-time graduate level coursework with a focus on robotics and ML. at Stanford Center for Global and Online Education
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