Nathan Tsao
Applied Machine Learning Engineer with experience in generative AI, reinforcement learning, and scalable machine learning. Seeking full-time ML Engineer positions.
About Me
I received my MS from UT Austin in 2025, and BS from UIUC in 2022. During my Master's studies, I developed machine learning algorithms for scalable electrical network modeling and human activity recognition using batteryless sensors as a graduate research assistant. I was also recently a research intern at NASA Ames Research Center (Summer 2025). Interested in deep learning, generative AI, and humanoid robots.
Featured Projects
Causal Diffusion Guidance
Working towards diffusion models capable of causal counterfactual reasoning.
Traffic Following Autonomous Aircraft
Internship project at NASA Ames exploring autonomous air traffic control
Human Activity Recognition with Batteryless Sensors
Developed a low-energy and fast-inference human activity recognition algorithm for batteryless sensors.
Neural Port-Hamiltonian Differential Algebraic Equations
Developed compositional learning algorithms for coupled dynamical systems.