- Developing machine learning agents that transform how large batteries in the grid buy and sell energy.

- Developed embodied deep reinforcement learning agents that learned to optimally adapt to environmental changes in a simulated patch foraging environment.- Responsible for machine learning training, environment design, and explainability/interpretability analyses.

- Led multi-disciplinary human behavioral and neuroimaging experiments on perception, embodiment, and decision making.- Programmed wireless displays, simultaneous EEG and motion capture data collection pipeline, andtime-series statistical analyses using MATLAB and R.

- Led human motion tracking experiments, and implemented statistical analyses of time series data.