Andrew is the Director of Data Science at HiddenLayer, responsible for researching and design of adversarial ML detection mechanisms. He has nearly a decade of experience in the cyber-security industry working for Cylance, Sophos, and Elastic, where he trained and deployed machine learning solutions to detect malware and emerging threats. Andrew has previously worked with computer vision and machine learning for neuroscience research, as well as applying ML/AI in the fields of speaker recognition, vehicle fault prediction, and financial modeling. Andrew holds a Ph.D. in computer engineering and machine learning from the University of Tennessee, Knoxville, with his dissertation focusing on Conditional Computation in Deep and Recurrent Neural Networks. As a two-time BlackHat speaker, most recently on Deep Learning on Disassembly, Andrew is passionate about sharing knowledge with the cyber-security community. His interests include attacking machine learning systems to better understand how to develop defensive countermeasures, and plays a mean guitar. He resides in Portland, Oregon, with his wife, dog, and two cats.
HiddenLayer, a Gartner recognized AI Application Security company, is a provider of security solutions for machine learning algorithms, models and the data that power them. With a first-of-its-kind, noninvasive software approach to observing and securing ML, HiddenLayer is helping to protect the world’s most valuable technologies.
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