Shang Zhou
Incoming Quantitative Researcher Intern
San Diego, California, United States
Summary
🤩
Rockstar🎓
Top SchoolShang Zhou is a quantitative researcher and machine learning engineer with six years of experience bridging high-performance inference systems and LLM research. Currently an incoming Quantitative Researcher Intern at Jump Trading and a research lead on a multi‑institution benchmark of LLM performance, he has published practical algorithms (e.g., OSCA mixed‑allocation for inference) that cut compute by orders of magnitude while improving accuracy. His contributions to PaddlePaddle include TensorRT integration, dynamic-shape inference demos, and operator versioning that improved framework stability for production-grade deployment. A former Codeforces problem setter ranked among the Top 100 contributors, he combines deep theoretical insight with hands‑on systems engineering and a knack for designing rigorous evaluation methodologies. Based in San Diego, he’s completing a PhD in Computer Science at UCSD and frequently leverages competitive programming and open-source work to stress-test and scale ML systems.
5 years of coding experience
1 year of employment as a software developer
University of California, San Diego
Github Skills (10)
tensorrt10
paddlepaddle10
machine-learning10
c-language10
deep-learning10
cprogramming-language10
efficientnet9
nlp7
github-ci3
githubaction-workflow3
Programming languages (2)
Github contributions (5)
PaddlePaddle/Paddle-Inference-Demo
Dec 2020 - Jul 2022
Role in this project:
ML Engineer
ML EngineerContributions:32 reviews, 56 commits, 32 PRs in 1 year 7 months
Contributions summary:Shang primarily contributed to the `paddlepaddle/paddle-inference-demo` repository by implementing and testing an Ernie-Varlen demo. This included modifying the `ernie_varlen_test.cc` file to incorporate the Ernie model and integrating it within the Paddle Inference framework. The changes involved setting up TensorRT and dynamic shapes for efficient inference. The user also made minor comment updates and merged changes from the master branch.
PaddlePaddle/Paddle
Sep 2020 - Jun 2022
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Role in this project:Backend Developer
Backend DeveloperContributions:422 reviews, 89 commits, 274 PRs in 1 year 10 months
Contributions summary:Shang contributed to the PaddlePaddle framework by implementing version checks for operators, ensuring compatibility and managing operator versions. They introduced new comparators and a registrar to handle version compatibility checks for different passes within the framework. Furthermore, the user optimized error reporting and added test cases for TensorRT integration. These changes focused on improving the framework's stability and extending its capabilities for optimized inference.
pytorchpythonparalleldeep-learningpaddlepaddle
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