I am currently a machine intelligence engineer with Embedded Intelligence, a research and development group in the DC area, where we advance understanding of robust machine learning algorithms (GARD, RED).
Generally speaking, I work in the areas of machine learning, artificial intelligence, cognition, and neuroscience. As a post-doctoral researcher at Emory University in Atlanta, Georgia, I worked with Astrid Prinz in the Biology department, on brain-inspired algorithms for continual machine learning, as part of a DARPA program. For more on this research, please see this section of my GitHub profile page: https://github.com/NickleDave#visual-search-and-visual-attention. In the area of applied machine learning, my work has focused mainly on automated annotation of birdsong and other vocalizations. For related libraries and tools I develop and maintain, please see: https://github.com/NickleDave#data-science-tools-for-birdsong-and-other-vocalizations. I began developing software tools for studying vocalizations during my graduate studies in Sam Sober’s lab at Emory University in Atlanta, Georgia. My dissertation work in the Sober lab showed that connections which are known to be important for learning motor skills in humans and other mammals are also found in regions of the songbird brain that are important for learning song. For the published paper and related works, please see my Google Scholar profile.
Sometimes when I get some free time I dance salsa and bachata. Merengue after 2:00 A.M. In a previous life I was a rock star and an underground cartoonist.