Jeff Winchell

I’m a master’s student in computational biology at Carnegie Mellon University, with a background in machine learning, single-cell imaging, and biological data science. My research interests center around representation learning, interpretable models, and developing methods that help us understand complex biological systems at scale.

At NYSCF, I worked on projects in bioimage analysis, high-content screening, and generative modeling, with a particular focus on making high-dimensional data more explainable and biologically meaningful. I’m especially drawn to problems that involve uncovering structured latent spaces, modeling cell state dynamics, and building tools that interface between ML and real-world biology.

Long-term, I hope to contribute to method development that bridges theoretical insights in machine learning with practical advances in systems biology, imaging, and health. I’m also passionate about reproducibility and open-source tools in computational science.

In my spare time, I like running, traveling, watching movies, and playing classical guitar.