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.
Congratulations to Bernadette Bouchon-Meunier
Recipient of the 2024 IEEE Frank Rosenblatt Technical Field Award
She is an IEEE Life Fellow, an International Fuzzy Systems Association fellow, an Honorary Member of the European Association for Fuzzy Logic and Technology (EUSFLAT) and a fellow of the Asia-Pacific Artificial Intelligence Association (AAIA). She was appointed as Distinguished Lecturer of the IEEE CIS for the period 2014-2016. She received the 2012 IEEE Computational Intelligence Society Meritorious Service Award, the 2017 EUSFLAT Scientific Excellence Award, the 2018 IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award, the 2019 Outstanding Volunteer Award of the IEEE France Section and the IEEE 2024 Frank Rosenblatt award.
Her present research interests include approximate and similarity-based reasoning, as well as the application of fuzzy logic and machine learning techniques to decision-making, data mining, risk forecasting, information retrieval, user modelling, sensorial and emotional information processing, management of information quality and eXplainable Artificial Intelligence.
Read full bio here.