IEEE Awards

IEEE Frank Rosenblatt Award

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The IEEE Frank Rosenblatt Award is a Technical Field Award sponsored by the IEEE Computational Intelligence Society.

The award, established in 2004, is named in honor of Frank Rosenblatt, who is regarded as one of the founders of neural networks. Basing his research on study of fly vision, he developed the single-layer input layer and an output layer of neural cells. Frequent presentation of a pattern or patterns resulted in changes in the input to output connections, facilitating future recognition of these patterns, or memory. His work influenced and anticipated many modern neural network approaches.

This award will be presented for outstanding contributions to the advancement of the design, practice, techniques or theory in biologically and linguistically motivated computational paradigms including but not limited to neural networks, connectionist systems, evolutionary computation, fuzzy systems, and hybrid intelligent systems in which these paradigms are contained.

This award may be presented to an individual, multiple recipients, or a team of not more than three members. This award is administered by the Technical Field Awards Council of the IEEE Awards Board. Prize items include a bronze medal, certificate and honorarium.

 

Congratulate the 2022 IEEE Frank Rosenblatt Award recipient:

PJW2017 Florence

PAUL JOHN WERBOS

For development of backpropagation and fundamental contributions to reinforcement learning and time series analysis

Among the first researchers to realize the power of bio-inspired learning techniques to train neural networks in real time, Paul John Werbos’ development of backpropagation algorithms provided the backbone of reinforcement and deep learning methods for solving today’s complex tasks. Backpropagation allows training of neural network data online and in real time by using gradients computed backward through the layers of the neural network. His leadership of the Adaptive and Intelligent Systems group at the U.S. National Science Foundation enhanced the ability of countless researchers to contribute to prediction and control of systems ranging from nanorobots to the electric power grid. His work has made possible many advances in areas including electric vehicles and speech, face, and handwriting recognition applications.

An IEEE Fellow, Werbos is program director (retired) with the National Science Foundation, Arlington, Virginia, USA.