- Designed and implemented an autonomous system for a differential drive robot in ROS/C++. Created a simulation of the autonomous system using ROS and Gazebo. Presented work in a live demo to executives using a real differential drive robot.
- Designed, simulated, and implemented control systems for electromechanical systems using a combination of classical, optimal and modern control theory techniques, such as PID and LQR/LQG
- BS and MS in Mechanical Engineering
- Software/Programming: C, C++, Python, MATLAB, Visual Studio, Git, ROS, Linux, TCP, UDP, REST APIs, CAN (J1939, CANOpen)
- Control Theory: Model Predictive Control (MPC), Optimal Control, Optimization, Classical Control, PID Control, Kalman Filtering, Particle Filtering
- Artificial Intelligence: Supervised Machine Learning, Deep Learning, Convolutional Neural Networks, Reinforcement Learning