In my role as an Instructional Aide, I assist in answering student questions during lectures and hold several office hours each week for EECS 280, the largest course in the College of Engineering with over 1200 students per semester.

At the NeuRRo lab, I work on medical robotics research. My current project is working on and optimizing the computer hardware and software that controls a robot meant to aid in rehabilitating muscle function in stroke patients' arms.

I worked in the Scaled Environment for Robotics Algorithms (SERA) Lab at Ford Research and Advanced Engineering. In this role, I helped set up a network of several computers that were capable of talking to one another and processing data from model autonomous vehicles in real-time. For my primary project, I developed a monitoring system based on several overhead cameras. My software processed the feeds from several cameras at once and stitched the data from each one together, creating a live map of the entire lab environment. Using this information, I was able to determine how compatible novel perception, control, and planning algorithms were with one another.Finally, I also worked on testing novel perception algorithms on model autonomous vehicles in the lab.

I developed a diagnostic tool designed to identify the root cause of errors in Symbotic's proprietary robotic warehousing system. Each system was comprised of a smart structure coupled with hundreds of warehousing robots. The complexity of this system meant that errors were often extremely difficult to identify. My software combed through hundreds of log files and used machine learning to isolate the cause of these errors. At the end of my internship, this software was successfully deployed to customer sites.

I developed a Python-based command-line interface for DEP's Meshworks CAD software. I collaborated with a global team split between Bangalore, India, and Troy, MI.