Wang Bojun
Software Engineer at UESTC
Chengdu City, Sichuan, China
Summary
🤩
RockstarWang Bojun is a software engineer based in Chengdu with four years of experience bridging materials science research and production-grade machine learning systems. Holding a PhD in Materials Science and Engineering from UESTC, he applies rigorous experimental thinking to core ML framework development, notably contributing Phi kernel implementations and operator migrations in the widely used PaddlePaddle project. His work spans performance-sensitive areas such as grid sampler migration, average accumulates operator implementation, activation-function testing, and TensorRT group norm plugins—highlighting a focus on optimization and deployment. Comfortable in both research and engineering contexts, he brings domain expertise and meticulous testing practices to make deep learning runtimes more reliable and efficient.
4 years of coding experience
Github Skills (10)
paddlepaddle10
machine-learning10
deep-learning10
python10
neural-network9
tensorrt9
distributed-training8
efficientnet8
cprogramming-language7
c-language7
Programming languages (2)
Github contributions (5)
PaddlePaddle/Paddle
Jul 2022 - Jan 2023
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:
ML Engineer
ML EngineerContributions:99 reviews, 20 commits, 89 PRs in 5 months
Contributions summary:Wang's contributions primarily involve migrating and implementing operations within the PaddlePaddle deep learning framework, focusing on Phi kernel implementations. This is evidenced by code changes related to grid sampler migration and implementing the average accumulates operator, indicating a focus on core framework functionality. Further commits include the migration and addition of YAML/unit tests for the softplus activation function and work related to a TRT group norm plugin, demonstrating work on model optimization and deployment.
pytorchpythonparalleldeep-learningpaddlepaddle
wwbitejotunn/PaddleNLP
Nov 2022 - Nov 2023
👑 Easy-to-use and powerful NLP library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis and 🖼 Diffusion AICG system etc.
Contributions:40 pushes, 14 branches in 1 year
extractionbertnlp-tasksdiffusionsentiment-analysis
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