From the bench to the model.

I came to science from an unusual direction. I spent my early twenties in Charlotte playing music and working day jobs, including running the lessons studio at a Guitar Center. When the pandemic ended both the band and the work, I moved back to Winston-Salem and had to figure out what I actually wanted to do.

Trying to answer that honestly led me into psychology, and then into neuroscience. I worked through Robert Sapolsky’s Stanford lectures, and it clicked. I was not only interested in biology, I was good at understanding it. That was the turning point. I went back to school for biotechnology and committed to it.

I earned an Associate of Applied Science in Biotechnology from Forsyth Technical Community College (GPA 3.51), with coursework from aseptic technique and cell culture through recombinant DNA. Alongside it I taught myself the AI and data stack, with certifications in machine learning (IBM), genomic data science (Johns Hopkins), and prompt engineering (Vanderbilt). In 2025 I did data and AI work for the Piedmont Triad Regenerative Medicine Engine at WFIRM, and I now take on freelance data and AI projects.

What keeps me here is the overlap between the two fields. The perceptron, the unit behind every neural network, was modeled on the biological neuron. I work on both sides of that line: data and AI tools for real biology problems, and, on my own time, experiments with neural networks that behave a little more like the biological ones.

I am not where I want to be yet, but I know where I am going. My next step is a bachelor’s degree to deepen the biology side of the work, with the long-term aim of applying machine learning and data engineering to hard problems, most of them in regenerative medicine, cell therapy, and bioinformatics. If you are hiring, looking to collaborate, or have a noisy problem worth solving, get in touch.