Understanding the Importance of Securing the ML Code with ML


Cyberthreats are becoming smarter and more complex as the threat players have access to newer, AI driven, cloud enhanced technologies. Having the ability to forecast cyberattacks before they happen depends on the same AI capabilities. How can we outsmart the cyberthreats? The answer is by augmenting traditional Cybersecurity with the help of Machine Learning and Deep Leaning technologies. This session will be focused on defining the threat players, types of security threats and defensive techniques, and will culminate with a practical example on how Generative Adversarial Networks can help build proactive, resilient, and robust cybersecurity solutions.


Dr. John Almasan is a hands-on, accomplished technology executive with 20+ years of experience in leading global tech teams and building large-scale data, analytics, and cloud platforms at Bank of America, American Express, and Nationwide Insurance. He has deep expertise in multi-cloud big data engineering, machine learning, and data science. His focus is on enabling the acceleration of AI adoption, as well as employee cross-training. As an adjunct professor at several universities and a member of the Arizona State University’s Board of Advisors, John is actively involved in preparing our next generations to meet the future skillset needs and demand. John holds two master’s degree in Engineering and Statistics and a Doctor of Business Administration, is credited with 15+ patents, and has been the recipient of several awards.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

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