I'm currently a Postdoctoral Research Associate at Duke University, where I use computational modeling and statistical analyses to better understand the brain. My research deals with neural coding in sensory systems, and particularly how multiple types of sensory information can be integrated together to make decisions. Neural data, like many other types of data, is complex and ambiguous and benefits from both common machine learning techniques and completely novel statistical analyses. Feel free to look around the site to see how I've been using these techniques to answer scientific questions.
PhD in Neurobiology, 2014 - 2020
Auditory and visual localization under uncertainty
B.S. Mechanical engineering, 2009 - 2014
Minor: Mechatronics, GPA:3.86
Machine learning is a powerful tool for neuroscience. Often, we can use tools like regression to get a better understanding how neurons relate to perception and behavior. Here is a short demo of the neural problems that can be solved with non-linear regression. 