About me

I’m an Electrical and Computer Engineering PhD student at the University of Georgia’s Multispectral Imagery Lab researching computer vision models for image and spectral data inside and outside the visible domain. I like to incorporate statistical analyses of the effects of methodological decision-making and hyperparameter selection as I feel that the current literature is often lacking in this type of analysis. While it does take up quite a bit of GPU runtime, you might as well throw what you can at the wall and see if there’s a pattern to what sticks. I blame the movie Moneyball for my bachelor’s degree in statistics, as it as the first movie I watched alone in theaters (and Nate Silver’s defunct FiveThirtyEight blog); likewise, I watched The Big Short on an airplane once or twice and now I also have a bachelor’s degree in finance. Why am I into machine learning for computer vision? The carykh YouTube channel got me interested in machine learning content, and the computer vision-related stuff stuck out to me the most. I also completed the coursework necessary to fulfill a graduate-level geographic information sciences certificate; honestly, I did it because I’ve loved staring at maps since I could read, I’ve always thoroughly enjoyed data visualization, and my graduate curriculum required a ton of electives that could be anything provided you provided justification. Outside of my current research, I’m particularly interested in remote sensing, as it sits at the intersection of geographic information sciences, machine learning, and multispectral and hyperspectral imaging.