Gerald Penn (computer scientist)
Gerald Penn | |
|---|---|
 Penn at IZ-Colloquium (Berlin, May 2012) | |
| Alma mater | |
| Known for | Application of neural network in acoustic model |
| Awards |
|
| Scientific career | |
| Fields | |
| Institutions | University of Toronto |
| Thesis | The Algebraic Structure of Attributed Type Signatures (2000) |
| Doctoral advisor | Frank Pfenning |
| Website | http://www.cs.toronto.edu/~gpenn/ |
Gerald Penn is an American computer scientist specializing in mathematical linguistics and speech processing.[1] He is a Professor of Computer Science at the University of Toronto,[2] a senior member of IEEE and AAAI,[3] and a past chair of Association for Mathematics of Language.[4]
Education[edit]
Penn earned a B.Sc. in mathematics from the University of Chicago in 1991. He then attained a M.Sc. in philosophy in 1993 and Ph.D. in computer science in 2000, both from Carnegie Mellon University.[5] His Ph.D. thesis was nominated by Carnegie Mellon School of Computer Science for the ACM Doctoral Dissertation Award.[6]
Career[edit]
Penn is a past recipient of the Ontario Early Researcher Award. His joint work with Geoffrey Hinton and Hui Jiang on signal processing with neural networks revolutionized acoustic modelling for speech recognition systems, and received the Best Paper Award from IEEE Signal Processing Society. He has led numerous research projects, including those funded by Avaya, Bell Canada, CAE, the Connaught Fund, Microsoft, NSERC, the German Ministry for Training and Research, SMART Technologies, the U.S. Army and the U.S. Office of the Director of National Intelligence.[3]
References[edit]
- ^ "Gerald Penn". scholar.google.com. Retrieved 2022-01-05.
- ^ "Gerald Penn". www.cs.toronto.edu. Retrieved 2022-01-05.
- ^ a b "Gerald Penn". tcairem.utoronto.ca. Retrieved 2022-12-23.
- ^ "SIGMOL". wwwhomes.uni-bielefeld.de. Retrieved 2022-01-05.
- ^ "Gerald Penn Profile | University of Toronto". Retrieved 2024-01-20.
- ^ "Frank Pfenning / Students and Co-authors". www.cs.cmu.edu. Retrieved 2023-02-28.
