I’m Ming Lin — an undergraduate student at Stony Brook University majoring in Computer Science and Applied Mathematics & Statistics. I enjoy working where systems engineering, data, and machine learning intersect. My interests include machine learning, distributed systems, computer vision, and large-scale data processing.
I’m currently an undergraduate researcher working with Professor Jun Wang on developing a data analysis GUI to support large-scale microarray processing and biomarker distribution analysis on tissue samples.
- Optimized image processing pipelines using OpenCV and scikit-learn, reducing processing time from 20+ hours to under 1 hour.
- Enhanced detection accuracy with a novel machine learning–based method, reducing error rates from 5–20% to under 1% across 10 datasets.
Outside of research, I’ve contributed to open-source projects like etcd (a CNCF project, 50k+⭐) and pear-desktop (29k⭐).
My personal work spans from full-stack web apps and backend services using FastAPI, Celery, and Redis, to data visualization and AI-based search tools. I enjoy creating applications that solve my own and others' problems.
I have a strong foundation in Python, TypeScript, and various cloud and DevOps technologies, with a proven ability to optimize complex systems and deliver robust software solutions. I enjoy tackling challenging problems, whether it's reducing a 20-hour data processing pipeline to under an hour or architecting a microservices-based video platform to handle high traffic.