• Characterized the human perception of the benefits from state-of-the-art exoskeletons• Designed, implemented, and debugged a Transformers-based deep learning controller that estimates gait phase and task on a Raspberry Pi-controlled exoskeleton• Collaborated with a startup company (Dephy, Inc.) to implement this controller on hardware• Successfully tracked the state of a data-driven human gait model and applied adaptive biomimetic torques• Implemented sensor fusion and multimodal signal processing using on-board device sensors • Improved on state-of-the-art phase estimation error by 100%• Controller is the first to estimate phase and task continuously in an outside practical environment

• Led the mechanical redesign of the fleet of Small Size League soccer robots for the annual competition • Redesigned robot’s drivetrain system for precision CNC manufacturing• Improved the robot’s ability to capture the ball by designing a dampening system for shock absorption• Integrated existing dribbler, chipper, and kicker systems to increase space efficiency by 30%

• Participated in the development of SculptPrint software, a CAM application that utilizes voxels to represent models and generate tool-paths as opposed to traditional CNC machine parametric methods • Created CAD models of mechanisms for manufacturing using SculptPrint • Implemented a design of experiments (DoE) to systematically test essential toolpath planning operations • Developed a Python application to automate the tool path generation process within SculptPrint