PhD Dissertation: Secure by Design

Designing process control systems so that cyberattacks can be isolated and identified by construction, not just detected after the fact.

MS Thesis: Learning to Adapt

A machine learning and model-based framework for detecting, estimating, and correcting multiple simultaneous sensor faults in real time.

HVAC Energy Forecasting

Built time-series forecasting models to optimize HVAC scheduling on UC Davis campus buildings based on occupancy data, projecting a 15% reduction in weekly energy costs. Class project with a small team.

Rocket Landing Prediction

Built a data-driven framework to predict successful rocket landings using feature engineering and supervised learning, achieving 94% cross-validation accuracy.

MIMO Chemical Process Control

Modeled a multi-input, multi-output chemical process in Python and designed an LQR controller to stabilize the system.

Autonomous Vehicle MPC

Built a nonlinear model predictive control framework for autonomous vehicle motion planning, handling lane following and obstacle avoidance.

Production of Phenol

Undergraduate capstone project: end-to-end plant design for phenol production, covering process synthesis, mass and energy balances, equipment design, plant layout and site selection, Aspen Plus simulation, cost estimation, and safety and effluent treatment considerations.