Cindy Wei
Hi, I'm Cindy Wei, a passionate software engineer specializing in computer graphics and game technology. I'm currently pursuing my M.S.E.
About
Hi, I’m Cindy Wei, a passionate software engineer specializing in computer graphics and game technology. I’m currently pursuing my M.S.E. and B.A.S. degrees at the University of Pennsylvania, where I’ve had the opportunity to work on exciting projects ranging from procedural terrain generation to real-time log visualization. I enjoy tackling complex problems through innovative solutions and continuously growing my skills in software development.
In addition to my academic work, I’ve gained valuable hands-on experience interning with renowned companies like Woven by Toyota, TSMC, and Stanford University. I love collaborating with diverse teams and applying my expertise in languages like C++, Python, and JavaScript to create efficient and impactful software. Outside of coding, I am also involved in extracurriculars like Penn Spark and the Pennsori Acapella Group, balancing my technical and creative interests.
- 2 years' experience
- Joined July 2025
Languages
- KoreanIntermediate
- EnglishAdvanced
Industry experience
- Software & Internet
- Gaming
- Manufacturing
- Life Sciences
- Education
More experts in Philadelphia, United States
Work experience· 4 roles
Ported a large analytics web app to a cross-platform Electron desktop (Linux/macOS/Windows) with secure IPC bridges. Integrated a native log to MCAP transformer by spawning Linux binaries, streaming progress, and auto-loading results. Built real-time log visualization using a Python WebSocket server and Electron client subscribing and rendering live MCAP log data. Added CLI ingestion for MCAP and JSON layout files with dynamic layout application and persistence.
Improved the FNO model for defect detection in AMRS-DB by generating and comparing reference images. Applied training methods and model adjustments to enhance performance for N5 VG/VD and M0 layer processes. Reduced gauge error to 12% for non-defect and 10% for defect cases, with better L1 edge error detection.
Developed image-processing algorithms using OpenCV for droplet manipulation in biological automation. Enhanced the precision of data analysis by creating robust detection pipelines for automated workflows. Analyzed and tracked moving objects across sequential images, improving object detection accuracy by 25%.
Education
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