Over the summer, I worked as a robotics intern at Navflex Inc., a startup working on autonomous forklifts for warehouse logistics. While there, I worked with a small team of roboticists in an agile environment as a Kalman Filtering expert to contribute source code in c++ for sensor fusion augmentation. Among these augmentations were the inclusion of odometry data as sensor fusion measurements, tuning of LIDAR measurement noise, and building foundations for error-state estimation. With these augmentations, the reliability and accuracy of the vehicle localization were drastically improved. 

While there, I especially enjoyed seeing the full pipeline of development from troubleshooting errors and finding the root cause, prototyping theoretical fixes on a whiteboard, to seeing the results of the changes after the final PR of the code changes. I found it incredibly satisfying to be able to see this whole pipeline from start to finish within a short span.

The summer after I started my Ph.D. I worked under Greg Trafton at the Navy Center for Applied Research in Artificial Intelligence (NCARAI) group at the Naval Research Laboratories (NRL). While at NRL I collaborated directly with a small group of multi-disciplinary colleagues to develop a theory for what factors contribute to social robot navigation. We then programmed a Boston Dynamic's Spot Robot to navigate through a narrow hallway utilizing these principles. 

For over two years I worked as a Navigation Engineer at Vectornav Technologies. Throughout my time there I acted as an external expert in navigation systems, providing customers and potential customers with detailed and digestible information about navigation systems. This frequently meant meeting with customers to discuss the details of advanced navigation topics such as Kalman Filters, Quaternion Attitude Representation, and advanced  GNSS/GPS from both a theoretical and applied perspective. While not actively engaged with customers, I would spend my time on a variety of projects that either cultivated or utilized both my technical and communication skills. Some example projects; Programming an embedded microcontroller in C to send and receive the requisite messages for RTK-GNSS; Georeferencing points in space given sensor inputs given real-world datum; developing documentation for different applications of our product (many of which can be found here)

My favorite part of working at Vectornav was the people I worked with. I would spend a significant amount of time working with people across every department and consistently every person I worked with was exceedingly knowledgeable and fun to work with!

In my senior year of my undergraduate studies, I worked as a Research Scientist at the Nathan Kline Institute for Psychiatric Research as part of Northeastern Universities co-op program. Throughout my time there I worked in the neuroimaging research group working on signal processing for simultaneous EEG and fMRI.

During my undergraduate studies I worked as a project manager for the Singapore Grand Prix with Faithful+Gould. While working I was solely responsible for managing the public lighting contract. The Singapore Grand Prix is one of the few Formula 1 races that take place at night, which means that decorative lights are put up to light public sidewalks and seating spaces. My job was to work with contractors and subcontractors to ensure that all lights were installed properly and deal with any discrepancies and issues that came up throughout this process.