HanYi Chen
- (+886) 975763930 (Taiwan)
- Email: hanych923@gmail.com
- Github: chanhanyi0923
- Website: http://www.hanyichen.info/
Education
Zhejiang University
- Bachelor of Computer Science, Zhejiang University
- Cumulative GPA: 3.67/4.00
- Major GPA: 3.73/4.00
- Hangzhou, Sep.2016 - July.2020
Publication
OD Morphing: balancing simplicity with faithfulness for OD bundling.
- Vancouver, Oct.2019
- IEEE Visualization Conference (VIS) 2019
A visualization technique, OD Morphing, that enhances OD bundling to be more geographically faithful with actual paths, and provides user interaction for balancing simplicity for OD patterns with faith-fulness for real paths.
Awards
The 42nd ACM International Collegiate Programming Contest (Asia Regional)
- Silver Medal Award
- Xian, Oct.2017
Experiences
Software Engineer, Microsoft
Microsoft Maps and Geospatial
Taipei, Feb.2021 - Now
- 40 ms latency of BingGC service are decreased by migrating BingGC components from monoliths to microservices.
- Reduced the demand for data labeling of queries from 40% to less than 1%, by implementing auto labeling algorithm.
- Contribute to BingGC global expansion, including Spanish, Arabic, Chineses language markets.
- Help interns to achieve great performance.
Software Engineer Intern, Microsoft
Microsoft Maps and Geospatial
Taipei, Jul.2019 - Sept.2020
- Implemented the traffic visualizer of Bing Maps service, and traffic logger of the backend pipeline.
- Improved the performance of an internal scraping tool, which can be up to 3 times faster than before.
- Fine-tuned the machine learning model of geocoder to increase the metrics of answer relevance by 0.5%.
- Developed the prototype of an emergency alert Android app using Bing Maps SDK, and also designed UI/UX of it.
Software Engineer Intern, ByteDance
Lark Suite
Hangzhou, Mar.2019 - Jun.2019
- Developed an analysis tool for Lark Suite, which can display the online service usage of 50,000 users.
- Designed an algorithm to render front-end flowcharts 10 times faster than before.
- Implemented a genetic algorithm to arrange a shift work schedule with complicated rules, which can manage up to 300 people in 20 seconds.
Skills
- C, C++, C# & .NET, Java, Go, Python, PHP, JavaScript, OpenGL