Yue Zhao (https://www.andrew.cmu.edu/user/yuezhao2/ ) is a Ph.D. candidate at Carnegie Mellon University. He is an expert on anomaly detection (a.k.a outlier detection) algorithms, systems, and its applications in security, healthcare, and finance, with more than 7-year professional experience and 30+ papers (in JMLR, TKDE, VLDB, NeurIPS, etc). He is a winner of the 2022 Norton Labs Graduate Fellowship. His works lay the foundation of anomaly detection, and his Python Outlier Detection (PyOD https://github.com/yzhao062/pyod ) library has been downloaded by more than 10 million times and used at Amazon, IBM, Morgan Stanley, and Tesla.

In this talk, Yue will give an overview of anomaly detection–a widely used machine learning technique to identify deviant samples from the general data distribution. He will also present how to use the Python Outlier Detection library PyOD.

Note: The Zoom link will be sent in the confirmation email after registration.

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