Tuowen Zhao is a tech leader and ML-savvy systems engineer with 12 years of experience, currently directing execution model and programming-abstraction work for dataflow hardware at SambaNova in Palo Alto. He has driven cross-stack improvements in sparsity, low-precision inference, and mixture-of-experts execution—achieving multi-digit performance gains and novel programming abstractions used across compiler and runtime. As a hands-on lead he built pre-silicon verification, formal verification with Z3, and developer-facing tooling including an internal "coding copilot" powered by SambaNova on-prem inference. His open-source contributions include integrating SambaNova’s Llama3.1 models into the Continue AI code-assistant project, bridging cloud model providers and developer tooling. Trained as a PhD computer scientist, Tuowen blends deep research rigor with product-focused delivery and a knack for simplifying operator sets and memory abstractions that pay off at chip and system scale. Unexpectedly, his background spans both international trade and information engineering, which informs a pragmatic, cross-disciplinary approach to complex engineering tradeoffs.
12 years of coding experience
4 years of employment as a software developer
The University of Utah
Bachelor of Science - BS Information Engineering, Bachelor of Science - BS Information Engineering at Shanghai Jiao Tong University
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Role in this project:
ML Engineer
Contributions:1 PR in 6 months
Contributions summary:Tuowen primarily contributed to integrating SambaNova, a cloud platform, into the project's AI model provider options. This involved adding configurations, API integrations, and model definitions for SambaNova's Llama3.1 models within the codebase. Additionally, the user updated documentation and configurations related to model providers, ensuring accurate information and functionality for the supported AI platforms.
Contributions:94 commits, 77 pushes, 13 branches in 1 year
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