About

Hello! I am a data scientist with a background in experimental psychology and neuroscience, which means I've spent a lot of time thinking about how people behave, how systems respond, and how to make sense of messy, complex data. These days, I bring that same curiosity and analytical mindset to machine learning and applied AI. My path from academia to tech has taught me to balance scientific rigor with practical problem solving, and I'm especially interested in building models that are interpretable, ethical, and actually useful in the real world.

I'm energized by working across a wide range of challenges—from anomaly detection and time-series modeling to reinforcement learning and explainability tools. I enjoy diving into new domains, translating data into insights, and sharing what I learn along the way. This site is where I collect and share my work: projects that interest me, blog posts that reflect my thinking, and the occasional experiment in code or concept.

I received my undergraduate education at Florida State University (Go 'Noles!) and my master's degree in experimental psychology from Old Dominion University (Go Monarchs!). I studied at Wake Forest University for my PhD in computational and systems neuroscience (Go Deacs!), and completed my formal education with a postdoctoral fellowship at The Salk Institute for Biological Studies (Yay vaccines!). I currently live in Seattle, WA with my partner and two dogs, and when I'm not trying to solve puzzles with data, I enjoy volunteering at the Ballard Food Bank, gardening, bread-making, hiking, and exploring the many many beautiful parks in Seattle. Thanks for stopping by—feel free to explore, or even get in touch!