IEEE Frank Rosenblatt Award
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 2023 IEEE Frank Rosenblatt Award recipient:
Polycarpou pioneered the development of neural network-based fault monitoring and event detection. Its wide use in today’s monitoring and control systems makes reliable operation in diverse applications possible
The IEEE Computational Intelligence Society is most pleased to announce that Marios Polycarpou has been selected as the recipient of the prestigious 2023 IEEE Frank Rosenblatt Technical Field Award. Professor Polycarpou was selected "for pioneering contributions to the theory and application of neural networks and learning systems in monitoring and control." Professor Polycarpou will receive the award at the 2023 International Joint Conference on Neural Networks (IJCNN 2023), which will be held in Queensland, Australia, from 18-23 June 2023.
Marios Polycarpou’s research on intelligent monitoring and control has had a long-lasting impact in numerous application domains, including water distribution networks, robotic systems, smart buildings, automation in healthcare devices, smart electric grids, and transportation. His work in neural networks-based adaptive control methods has transformed the field and opened new ways for designing neural control schemes with learning capabilities for uncertain dynamical systems. He also initiated an entirely new approach to using a learning systems methodology in fault diagnosis. First developed in 1994, his approach is now important to the Internet of Things and cyber-physical systems, where faults can heavily—and subtly—affect application performance.
An IEEE Fellow, Polycarpou is a professor of electrical and computer engineering and director of the KIOS Center of Excellence, at the University of Cyprus, Nicosia, Cyprus.