Wendy Kan is a Machine Learning Engineer with 14 years of experience applying data science and software engineering to high-impact problems, currently fighting abuse at Google using ML. She has deep experience building production ML systems across ads quality, multi-modal models, and scalable data infrastructure from her time leading data analytics at Kaggle. Her background spans biomedical and research software—from microscopy and neuro-experiment pipelines to biotech web apps—bringing rigorous experimentation and domain sensitivity to applied ML. Wendy combines hands-on engineering (Python, BigQuery, Airflow, cloud orchestration) with a track record of designing evaluation and metric systems that enable fair, reproducible model comparisons. Based in San Francisco, she pairs a PhD in Biomedical Engineering with cross-disciplinary product experience, often turning messy scientific data into deployable predictive solutions.
14 years of coding experience
11 years of employment as a software developer
Ph.D., Biomedical Engineering, Ph.D., Biomedical Engineering at The University of Texas at Austin
BS, Electrical Engineering, BS, Electrical Engineering at National Tsing Hua University
Contributions:72 pushes, 1 branch in 3 years 5 months
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