Chen Yang

My work spans machine learning, software development, and applied statistics. I'm drawn to problems where probabilistic modeling and data-driven decisions meet the real world, whether that's building machine learning systems at scale or pursuing quantitative research in markets.

I'm a CS + Applied Statistics dual-degree student at Purdue, where I concentrate in machine learning and gravitate toward the probabilistic and statistical side of both majors. I spent the spring at Rolls-Royce building a PyTorch generative model for synthetic multivariate sensor data, using a transformer-based masked diffusion architecture with distribution-derived column embeddings. At AbbVie I build a containerized R Shiny analytics app that oncology researchers use to explore RNA-seq differential-expression results and run pathway enrichment against MSigDB. This August I attended Jane Street's INSIGHT program on the Trading & Research track.