Brian is a veteran of defense intelligence and operations communities with a combination of data science, analytics algorithm development, robust signal processing, and software engineering experience. He values staying involved with the implementation details of adaptive computing technologies to advance the state of the art of human machine intelligence (HMI).
His research and development focus is on the third wave of machine intelligence (3MI) to implement Saffron's complementary learning vision; which increases system autonomy by creating a true partnership of human and machine. By integrating both traditional statistical learning methods from the second wave of machine intelligence (2MI) and instance learning methods from cognitive memory-based computing, it is possible to make high impact decisions faster with more relevant data.
Dr. Womack received his Ph.D. from Duke in robust signal processing and his M.S. from Texas A&M in adaptive control systems. Brian enjoys martial arts, SCUBA, camping, hiking, canoeing, archery, and volunteering.
Webcast: Creating data labels to adapt to contextual change February 20, 2018
Today, traditional artificial intelligence (AI) and machine learning (ML) largely depend upon data scientists to formulate labels associated with feature vectors that take into account model attributes such as entity, action, or relationship. A key challenge...