John Seymour is a Ph.D. student at UMBC researching machine learning for malware classification. He's mostly interested in avoiding and helping others avoid some of the major pitfalls in machine learning, especially in dataset preparation (seriously, do people still use malware datasets from 1998?) In 2014, he completed his Master’s thesis on the subject of quantum computation applied to malware analysis (later presented at DEFCON23). He currently works at ZeroFOX, Inc. as a Data Scientist.

Appearing at:

• An Introduction to Malware Classification

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