Short answers, pulled from the story.
Paul Werbos is best known for his 1974 doctoral dissertation, which was the first work to formally describe training artificial neural networks through backpropagation of errors. He is also recognized as a pioneer of recurrent neural networks.
Paul John Werbos was born on the 4th of September, 1947.
Werbos received the IEEE Neural Network Pioneer Award in 1995. The award recognized his discovery of backpropagation and his development of other basic neural network learning frameworks, including Adaptive Dynamic Programming.
Adaptive Dynamic Programming is one of the basic neural network learning frameworks developed by Paul Werbos. It was cited alongside backpropagation when the IEEE awarded him the Neural Network Pioneer Award in 1995.
Paul Werbos was one of the original three two-year Presidents of the International Neural Network Society, known as INNS. He was among the founding leaders of the organization.
Beyond machine learning, Paul Werbos wrote on quantum mechanics and other areas of physics. He also pursued questions about consciousness, the foundations of physics, and human potential, and served as a program director at the National Science Foundation until 2015.