Summary
Qingfu Wan is an Associate Software Engineer III with 11 years of hands-on experience building low-latency data pipelines, quantitative systems, and AI/ML infrastructure across finance and tech. He has blended C++ system engineering and Python-driven data science—shipping ETL, backtesting CAPI, and real-time alpha simulation at WeQuant, and developing GenAI/RAG pipelines on Azure at Microsoft. His academic background in computer vision and deep learning (NYU, JHU research, and Microsoft Research Asia) informs practical work on pose estimation and large-scale model training. Now in Global Risk at JPMorgan Chase, he applies this cross-domain expertise to production Python systems for risk analytics. An active coder with a GitHub and Google Scholar presence, he uniquely bridges research-grade algorithms and production engineering for high-throughput, mission-critical workflows.
11 years of coding experience
5 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at New York University
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Fudan University
Chinese, English