Praetorian Hires Machine Learning Expert to Advance Technology for Software Vulnerability Identification

Jeff Olson, expert in deep learning and artificial intelligence, joins Praetorian to lead development of state-of-the-art machine learning techniques used for continuous software vulnerability identification.

AUSTIN, Texas – June 12, 2018 – Praetorian, a leading provider of enterprise cybersecurity solutions, today announced the appointment of Jeff Olson as Director of Machine Learning. Olson, who spent the last 10 years applying deep learning to automated high-frequency trading, will lead machine learning research and development within Praetorian’s product engineering team and report to VP of Engineering Chad Walters.

An expert in deep learning and artificial intelligence with a comprehensive background in mathematics, physics, and computer science, Olson has written custom neural network libraries and training algorithms from scratch prior to the release of Google TensorFlow and other widely available computational frameworks for building machine learning models.

“I’m very excited to join the Praetorian team,” said Olson. “With Praetorian’s deep expertise in cybersecurity, I believe there is an excellent opportunity here to leverage state-of-the-art machine learning techniques to make significant advances in the field of automated detection of security vulnerabilities.”

Olson is now responsible for the advancement of machine learning algorithms and techniques used by Chariot, Praetorian’s security-as-a-service platform. Using multiple analysis methods for vulnerability identification, the platform’s technology is designed to meet the evolving needs of agile development teams. Its technology identifies software vulnerabilities introduced by incremental code movement with direct support for continuous integration and continuous delivery (CI/CD) pipelines.

With mass adoption in cloud and container technologies, today’s leading development teams are shipping code at unprecedented speed. The new pace in which code is being pushed to production is causing security teams to reexamine how they integrate security verification into the software development lifecycle.

“We believe that machine learning aided vulnerability identification operating within CI/CD pipelines is required to meet the evolving needs of agile development teams operating at the speed of DevOps,” said Nathan Sportsman, CEO at Praetorian. “The technology we are developing is positioned to transform the way in which software vulnerabilities are identified and eradicated.”

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