Xiande Cao
Principal Deep Learning Compute Engineer at NVIDIA
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolXiande Cao is a Principal Deep Learning Compute Engineer in San Jose with a decade of experience building GPU-accelerated AI systems and production-grade deep learning stacks at NVIDIA. He blends a strong academic foundation (PhD in Electrical Engineering) with hands-on engineering and management, having progressed from R&D and principal engineering roles at Cadence to leading deep learning software teams. Xiande collaborates actively with the open-source community on deep learning and graph neural networks, optimizing workloads across the NVIDIA software stack and large-scale GPU platforms. He’s known for translating research-grade models into efficient, deployable compute kernels and system-level optimizations that materially improve performance and scalability. Beyond technical leadership, his background in mentoring and Toastmasters indicates strong communication skills that help bridge research, engineering, and community adoption.
10 years of coding experience
5 years of employment as a software developer
MS Electric Engineering, MS Electric Engineering at Beihang UniversityPhD Electric Engineering, PhD Electric Engineering at University of KentuckyBachelor of Science (BS) Mechanic Engineering & Electric Engineering, Bachelor of Science (BS) Mechanic Engineering & Electric Engineering at Hefei University of Technology
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (96)
dep10
dataflow10
python10
mxnet10
deep-learning10
graph-convolutional-networks10
portable10
javascript10
scheduler10
llmops10
neural-network10
golang10
transformer10
gpt10
julia10
Programming languages (6)
Github contributions (5)
TristonC/dgl
Nov 2021 - Sep 2024
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Contributions:38 pushes, 18 branches in 2 years 10 months
pytorchpythondeep-learningmachine-learninggraph
TristonC/incubator-mxnet
May 2020 - May 2022
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Contributions:49 pushes, 30 branches in 1 year 11 months
pythonschedulerdataflowmutationorchestration
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