I build systems that work
and models that learn.

My research sits at the intersection of machine learning and molecular biology, specifically how computational methods can extract signal from messy, large-scale biological data. I work in the Cui Lab at RIT, where the problems range from proteomics data engineering to understanding how the genome regulates itself.

Right now I'm focused on two things: building rigorous PTM extraction pipelines for post-translational modification data, fixing assumptions the field has accepted for years, and studying genomics and 3D chromatin organization through deep learning models. The thread connecting all of it is the same: biology generates enormous, noisy datasets, and good software and good models are what turn that noise into biology.