Winston Li is a founder and data science leader with nine years of experience building privacy-first consumer analytics and advanced ML solutions. As founder of Arima he created the Synthetic Society, a cloud platform that generates 1:1 synthetic populations from 10,000+ attributes to enable privacy-by-design insights for data-driven teams. Previously a Director of Data Science at PwC Canada and Omnicom, he led cross-disciplinary teams delivering predictive analytics, deep learning, and research on trustworthy AI in collaboration with partners like the University of Oxford. He also contributes to open-source anomaly detection work, implementing advanced outlier models in the pyod library, reflecting a hands-on blend of research and production engineering. Based in Toronto, Winston combines product-focused entrepreneurship with enterprise delivery and a demonstrated interest in making AI auditable and privacy-preserving.
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
Role in this project:
Data Scientist
Contributions:10 commits, 7 PRs, 4 comments in 1 year 9 months
Contributions summary:Winston implemented several outlier detection models within the pyod library, specifically SOS, LOCI, MO_GAAL, and COPOD. These implementations involved writing Python code, integrating with existing libraries, and potentially optimizing performance. The contributions demonstrate expertise in various outlier detection algorithms and their application. Furthermore, the user added and revised related examples and tests for the implemented models.
Contributions:9 commits, 8 pushes, 1 branch in 1 year 8 months
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