Professor Bart Kosko, Ph.D., J.D. |
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Bio | |||||||||||||||||||
Dr. Bart Kosko is a Professor of Electrical and Computer Engineering in the University of Southern California's Viterbi School of Engineering | |||||||||||||||||||
and a Professor of Engineering and Law in USC's Gould School of Law. | |||||||||||||||||||
Dr. Kosko received bachelors degrees in Philosophy and in Economics from the University of Southern California, | |||||||||||||||||||
the masters degree in Applied Mathematics from the University of California at San Diego, the Ph.D. degree in Electrical Engineering | |||||||||||||||||||
from the University of California at Irvine, and the J.D. degree in law from Concord Law School. Dr. Kosko is an attorney licensed in California and federal court. | |||||||||||||||||||
Dr. Kosko received the 2022 Hebb Award for neural learning from the International Neural Network Society (INNS). | |||||||||||||||||||
Dr. Kosko is a Fellow of the IEEE for "contributions to neural and fuzzy systems," a Fellow of the International Neural Network Society (INNS), and a Fellow of the International Fuzzy Systems Association (IFSA). | |||||||||||||||||||
Dr. Kosko received the NAFIPS-2021 Best Paper Award
for the paper
''Uniform Mixture Convergence of Continuously Transformed Fuzzy Systems'' | from the 2021 Annual Conference of the North American Fuzzy Information Processing Society. | | Dr. Kosko received the NAFIPS-2020 Outstanding Paper Award
for the co-authored paper
| ''Random Fuzzy-Rule Foams for Explainable AI'' | from the 2020 Annual Conference of the North American Fuzzy Information Processing Society. | | He received the IJCNN-2017 Best Paper Award
for the co-authored paper
| ''Using Noise to Speed up Video Classification with Recurrent Backpropagation'' | from the 2017 IEEE-INNS Joint Conference on Neural Networks. | | | | Profiles IEEE Spectrum Profile | Wired Q & A - Fuzzy Logic | Wired Q & A - Noise | | | | |