Kun Lei
软件工程师 at 微软(中国)有限公司
Suzhou City, Jiangsu, China
Summary
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Top SchoolKun Lei is a software engineer with 8 years of experience, currently working on the front-end product for MSN Money at Microsoft in Suzhou. He has a strong background in image algorithms and full-stack AI projects, having led a technical team developing vision algorithms before an engineering stint at eBay. At Microsoft since January 2021, he combines front-end product work with practical ML/vision experience evidenced by contributions to a YOLOv3-based AI projects repo. Trained in software engineering at Xiamen University, he brings hands-on implementation skills from model training to front-end delivery. Colleagues would describe him as a pragmatic coder who values clear documentation and reproducible AI workflows, as shown by his emphasis on READMEs and project organization.
7 years of coding experience
学士, 软件工程, 学士, 软件工程 at 厦门大学
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
object-detection10
keras10
python10
yolov410
documentation9
machine-learning8
Programming languages (5)
Github contributions (5)
leikunx/AI_projects
Apr 2019 - Dec 2019
I am a full-stack engineer for AI projects, glad to share my experience. pratices make the top engineer.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:147 commits, 144 pushes, 1 branch in 7 months
Contributions summary:Kun primarily modified the `README.md` files, suggesting a focus on documentation and project overview. They also committed code changes within the `yolo3` directory, specifically modifying the `model.py` file, indicating work related to the YOLOv3 object detection model implemented in Keras. Furthermore, they changed some code in `_04_train_fish.ipynb` and added many code file in project 002, indicating that the user is responsible for implement the project, including training the model with the dataset.
pythonchinese-simplifieddeep-learningfull-stackmachine-learning
xkunlei/resume
May 2022 - Feb 2023
Contributions:17 pushes, 1 branch in 9 months
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