Yinchen Ni is a graduate student researcher and software engineer with four years of experience building scalable AI and big-data tooling, blending an academic background in electronic and computer engineering with practical cloud-native skills. At UM‑SJTU he teaches and researches topics from integrated-circuit CAD to big-data methods while contributing recitation materials on GitHub, and he previously improved CI/CD, Docker/K8s deployments, and distributed TensorFlow/PyTorch workflows at Intel. Proficient in C/C++, Python, CUDA, Spark and PyTorch, he focuses on developing robust, production-ready pipelines and recommendation examples that bridge research and real-world impact. Known as a quick starter with a curious mindset, he pairs strong coding fundamentals with hands-on experience in containerization, orchestration and nightly testing to accelerate reproducible ML and data engineering workflows.
4 years of coding experience
Master's degree, Computer Science, Master's degree, Computer Science at Shanghai Jiao Tong University
Contributions:15 commits, 4 PRs, 27 pushes in 3 months
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