About me

I am currently a machine intelligence engineer with Embedded Intelligence, a start-up in the DC area, where I work on adversarial machine learning (GARD, RED) and signal restoration.

Generally speaking, I do research in the areas of artificial intelligence, cognition, and neuroscience. During my post-doctoral fellowship 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.

I am also passionate about open science, broadly defined, am a trained Carpentries instructor, and remain involved with the graduate data science group I helped found at Emory.

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.