William Grisaitis

I was a lead engineer and co-author on published research applying deep learning to neuroscience. With other researchers, I developed a deep learning approach to "map" neurons in images of fruit fly brain tissue.

My responsibilities include all aspects of the project:
* deep learning - training and evaluating neural networks. Developing support code for automating and repeating this work.
* data engineering - storing large image data, developing access layers
* sys admin - maintaining a cluster of GPU machines. Deploying code with Docker and Mesos. General Linux/Ubuntu sysadmin.
* miscellaneous - data visualization, Jupyter, visualizing results, etc.

In this work, I produced predictive regressions of energy prices in wholesale markets, where electricity is bought and sold in a futures market. My results are currently (Oct 2018) being used for financial trading by a hedge fund in North Carolina, USA.

I worked with domain experts to develop a predictive linear model that successfully explains about 20% of all price movement in the market. Beyond statistical modeling and analysis, I also prepared all data needed for the project, starting from the ground up. This included data about the market itself as well as other data relevant to the problem, such as weather data.