S. Seth Long
Department of Natural Sciences and Mathematics
Lewis-Clark State College
Currently I am working on the Graph Neural Analyzer (GNA) for discovering correlations between the physical structure of the brain and the charactaristics of people, such as age or level of education.
Spring 2020 Classes:
CS253 Systems Programming
Research Interests:Computational Neuroscience, Artificial Intelligence, Machine Learning, Parallel Processing, Graph Theory
- Li, Shuai, Joe Mitchell, Deidrie J. Briggs, Jaime K. Young, Samuel S. Long, and Peter G. Fuerst. Morphological Diversity of the Rod Spherule: A Study of Serially Reconstructed Electron Micrographs. PloS one 11, no. 3 (2016): e0150024
- S. Li, M. Woodfin, S. Long, P. Fuerst. IPLaminator: an ImageJ plugin for automated binning and quantification of retinal lamination. BMC bioinformatics, 17(1), 1. January 2016.
- Samuel Seth Long, Graph-Based Neural Image Analysis and Classification Ph.D dissertation, Washington State University, 2014.
- G. Andrade, S. Long, H. Fleming, W. Li, and P. Fuerst. Dscam localization and function at the mouse cone synapse. Journal of
Comparative Neurology, 522(11):2609–2633, 2014.
- S. Long and L. Holder, Discovery of Discriminating Neural Regions for MRI Classification, Workshop on Expanding the Boundaries of Health Informatics Using AI (HIAI), Conference on Artificial Intelligence (AAAI), July 2013.
- S. Long and L. Holder, "Graph-Based MRI Brain Scan Classification and Correlation Discovery," IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), May 2012.
- S. Long and L. Holder, "Graph-Based Shape Analysis for MRI Classification," International Journal of Knowledge Discovery in Bioinformatics, 2(2):19-33, 2011.
- S. Long and L. Holder, "Graph Based Classification of MRI Data Based on the Ventricular System," Workshop on Biological Data Mining and its Applications in Healthcare (BioDM) at the IEEE International Conference on Data Mining (ICDM), December 2011.
- S. Long and L. Holder, "Using Graphs to Improve Activity Prediction in Smart Environments based on Motion Sensor Data," International Conference on Smart Homes and Health Telematics (ICOST), June 2011.