Celeste Fralick
Senior Principal Engineer and Chief Data Scientist, McAfee. Dr. Fralick is responsible for McAfee's technical analytic strategy that integrates into McAfee consumer and enterprise products as well as internal Business Intelligence. Dr. Fralick brings over 36 years of industry experience to McAfee. Prior to Intel's divestiture of McAfee, she was Chief Data Scientist in Intel's Internet of Things Group where she developed Machine Learning and Deep Learning analytics for over 8 different markets.. Dr. Fralick chairs McAfee's Analytic Center of Excellence, and was a technical leader in Intel's data science and biotech strategies, product qualification, and product life cycle programs. Active in various industry and academic boards, journal editorial staffs, and consortiums, her experience spans analytics, systems, IoT engineering, semiconductor process and product development, regulatory, medical device, and quality/reliability domains. She holds a Ph.D. in Biomedical Engineering from Arizona State University, concentrating on predictive analytics and neuroscience, and is currently authoring Springer's "Intelligent Analytics".
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The AI (R)evolution: Why Humans Will Always Have a Place in the SOC
In cybersecurity, the combination of men, women and machines can do what neither can do alone — form a complementary team capable of upholding order and fighting the forces of evil. The 20th century was uniquely fascinated with the idea of artificial intelligence (AI). From friendly and helpful humanoid machines ...
Analytics 101
From today’s smart home applications to autonomous vehicles of the future, the efficiency of automated decision-making is becoming widely embraced. Sci-fi concepts such as “machine learning” and “artificial intelligence” have been realized; however, it is important to understand that these terms are not interchangeable but evolve in complexity and knowledge ...
‘McAfee Labs Threats Report’ Offers Primer on Security Data Science, Analytics, Big Data, Machine Learning
Analytics, big data, automation, and machine learning are all terms we use when talking about the future of cybersecurity. As the volume of security data increases, data science will become an important weapon to disrupt adversaries. Too often, these terms are used as synonyms, but they refer to different parts ...
