Catherine D Schuman

Catherine Schuman

Catherine D Schuman

Liane Russell Early Career Fellow

Bio

Katie Schuman is a Liane Russell Early Career Fellow in Computational Data Analytics at Oak Ridge National Laboratory.  Katie received her doctorate in computer science from the University of Tennessee in 2015, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems.  She is continuing her study of models and algorithms for neuromorphic computing as part of her fellowship at ORNL.  Katie is also an adjunct assistant professor at the University of Tennessee, where she, along with four other professors at UT, leads a neuromorphic research team made up of 25 faculty members, graduate student researchers, and undergraduate student researchers. 

Publications

Catherine D. Schuman. “The Effect of Biologically-Inspired Mechanisms in Spiking Neural Networks for Neuromorphic Implementation." International Joint Conference on Neural Networks 2017, May 2017.

Aleksander Klibisz, Grant Bruer, James S. Plank, and Catherine D. Schuman. “Structure-based Fitness Prediction for the Variable-structure DANNA Neuromorphic Architecture." International Joint Conference on Neural Networks 2017, May 2017.

James S. Plank, Garrett S. Rose, Mark E. Dean, and Catherine D. Schuman. “A CAD System for Exploring Neuromorphic Computing with Emerging Technologies." Government Microcircuit Applications and Critical Technology Conference 2017, March 2017.

Catherine D. Schuman, Adam Disney, Susheela Singh, Grant Bruer, J. Parker Mitchell, Aleksander Klibisz, and James S. Plank. “Parallel Evolutionary Optimization for Neuromorphic Network Training," Machine Learning in High Performance Computing Environments Workshop, Supercomputing 2016, November 2016.

Thomas Potok, Catherine Schuman, Federico Spedalieri, Garrett Rose, Jeremy Liu, Ke-Thia Yao, Gangotree Chakma, Steven Young and Robert Patton. “A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers," Machine Learning in High Performance Computing Environments Workshop, Supercomputing 2016, November 2016.

Adam Disney, John Reynolds, Catherine D. Schuman, Aleksander Klibisz, Aaron Young, and James S. Plank. “DANNA: A Neuromorphic Software Ecosystem." Biologically-Inspired Cognitive Architectures 2016. Accepted. 

Catherine D. Schuman, James S. Plank, Adam Disney, and John Reynolds. “An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures." International Joint Conference on Neural Networks 2016. Accepted. 

Mark E. Dean, Jason Chan, Christopher Daffron, Adam Disney, John Reynolds, Garrett S. Rose, James S. Plank, J.Douglas Birdwell, and Catherine D. Schuman. “An Application Development Platform for Neuromorphic Computing." International Joint Conference on Neural Networks 2016. Accepted. 

Catherine D. Schuman, Adam Disney, and John Reynolds. “Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture," Machine Learning in High Performance Computing Environments Workshop, Supercomputing 2015, November 2015. 

Margaret Drouhard, Catherine D. Schuman, J. Douglas Birdwell, and Mark E. Dean. “Visual analytics for neuroscience-inspired dynamic architectures." Foundations of Computational Intelligence (FOCI), 2014 IEEE Symposium on. IEEE, 2014. 

Catherine D. Schuman, J. Douglas Birdwell, and Mark E. Dean. “Spatiotemporal Classification using Neuroscience-Inspired Dynamic Architectures," Procedia Computer Science, Volume 41, 2014. 

Mark E. Dean, Catherine D. Schuman, and J. Douglas Birdwell. “Dynamic Adaptive Neural Network Array." Unconventional Computation and Natural Computation, 2014. 

Catherine D. Schuman, J. Douglas Birdwell, Mark E. Dean.“Neuroscience-Inspired Dynamic Architectures," 2014 Annual Biomedical Science and Engineering Center Conference (BSEC), Oak Ridge National Laboratory, 2014. 

Catherine D. Schuman and J. Douglas Birdwell,“Dynamic Artificial Neural Networks with Affective Systems," PLOS ONE, Volume 8 (11), 2013. 

Catherine D. Schuman and J. Douglas Birdwell, “Variable-Structure Dynamic Artificial Neural Networks," Biologically Inspired Cognitive Architectures, Volume 6, 2013.