I am a graduate student at the University of Miami working in the lab of Dr. Odelia Schwartz since the Fall of 2018. My main research interests are computational neuroscience, vision, sparse coding, and machine learning. My work is supported by a National Science Foundation (NSF) Graduate Research Fellowship.
I recieved a B.S. in computer science with a minor in mathematics from the University of Central Florida. During my time at UCF I worked with Dr. Kenneth Stanley on an neural network called a Real-Time Autoencoder-Augmented Hebbian Network (RAAHN) which addresses control tasks. In 2016 I worked with Dr. R. Paul Wiegand of the Institute for Simulation and Training at UCF on brain-inspired image compression. During the summer of 2017 I worked at the Princeton Neuroscience Institute in the lab of Dr. Jonathan Pillow on hierarchical and non-negative sparse coding.
Joshua Bowren arXiv.(2022) Inference via Sparse Coding in a Hierarchical Vision Model
Joshua Bowren, Luis Sanchez-Giraldo, Odelia Schwartz; Inference via sparse coding in a hierarchical vision model. Journal of Vision 2022;22(2):19. doi: https://doi.org/10.1167/jov.22.2.19.(2016) Fully Autonomous Real-Time Autoencoder-Augmented Hebbian Learning through the Collection of Novel Experiences
Joshua A. Bowren, Justin, K. Pugh, and Kenneth O. Stanley In: Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV). Cambridge, MA: MIT Press, 2016. 8 pages.