TENNLab - Neuromorphic Architectures, Learning, Applications
We are a group of faculty, post-docs, graduate students and undergraduates researching a new paradigm of computing, inspired by the human brain. Our research encompasses nearly every facet of the area, including current and emergent hardware implementations, theoretical models, programming techniques and applications. (Read More)
Publications
Recent Publications
- Non-Traditional Input Encoding Schemes for Spiking Neuromorphic Systems: IJCNN: The International Joint Conference on Neural Networks July, 2019.
- Intelligent Reservoir Generation for Liquid State Machines using Evolutionary Optimization: IJCNN: The International Joint Conference on Neural Networks July, 2019.
- Spike-based primitives for graph algorithms: Published on arXiv. March, 2019.
- The TENNLab Suite of LIDAR-Based Control Applications for Recurrent, Spiking, Neuromorphic Systems: 44th Annual GOMACTech Conference March, 2019.
- Adapting Spiking Networks to Neuromorphic Hardware Subject to Process Variability: 44th Annual GOMACTech Conference March, 2019.
All Publications
Team
Dr. Nathaniel Cady
Dr. Md Sakib Hasan
Dr. Roger Horn
Parker Mitchell
Dr. Andy Sarles
Musabbir Adnan
Jonathan Ambrose
Sherif Amer
Hongyu An
Sam Brown
Gangotree Chakma
Mihaela Dimovska
Adam Foshie
Brent Hurst
John Murray
Maryam Parsa
Michael Peek
John Reynolds
Sagarvarma Sayyaparaju
Nick Skuda
Ryan Weiss
Grace Zhao
Kody Bloodworth
Michael Goin
Ankush Patel
Charlie Rizzo
Syd Shelby
Julia Steed
Alec Yen
Samantha Zimmerman