I currently spearhead the development of a high-speed motion control system for an autonomous racecar participating in the Indy Autonomous Challenge, designed to operate at velocities up to 180 mph. More about our team's endeavors can be found on our Team Website (https://autonomousracing.dev/).Key Contributions:- Advanced Localization Techniques: Engineered and deployed an Extended Kalman Filter localization pipeline that integrates GNSS, IMU, and Wheel Odometry. This robust system facilitates smooth localization across 15 degrees of freedom (DOF), utilizing C++ and ROS2.- Collision Avoidance System: Developed a collision avoidance planner that computes dynamically feasible trajectories for overtaking maneuvers. The planner takes into account the varying longitudinal and lateral friction limits of the tire, as well as a long horizon prediction of opponent motion, and is efficiently implemented in C++.- Real-Time Control Systems: Designed and tested a real-time capable Nonlinear Model Predictive Control (NMPC) system. This system efficiently generates stable steering angle requests at a frequency of 100Hz, leveraging Sequential Quadratic Programming (SQP) and written in C++.

● Performed data preparation, investigation, and analysis of 10-15 million transactions per month for the Defense Health Agency (DHA). Produced reports for a dataset totaling over 1 billion records spread over five data sources● Cleaned and normalized data from 5 different data sources to create a comprehensive set of financial transactions for seven different DHA components using Visual Studio and SSIS Packages

● Created a decision analysis matrix by creating and testing alternative system models for Boeing’s platform infrastructure● Developed a simulation model involving dynamic and sensory features of a vehicle. Utilized Java, C++, MATLAB, and Python to do propagation calculations, irradiance and gain approximations, and multithreading of Monte Carlo data sets