I'm a PhD candidate in Chemical Engineering at UC Davis, working on control theory, data science, and machine learning for energy and industrial systems. Read more

I started in process engineering, then found myself drawn to the control and data side of these systems: how you model them, monitor them, and let machine learning take on the parts first-principles models can't. Along the way I've touched refineries, HVAC systems, and CO2 heat pumps, working through process design, controls, and data problems in each of them. At Energy Recovery, that pulled me from a data internship into full ownership of an R&D control systems project, building simulation models, monitoring tools, and cloud platforms used across engineering and business teams. I'm doing something similar now at SpaceXAI (formerly xAI), applying that same background to help build AI models that reason like a domain expert. I also publish research on control theory and fault detection when the timeline allows. Whatever hat a project actually needs, I'm usually glad to put it on.