Tufts CubeSat is a student-led team dedicated to building a 1U CubeSat (a small cube-shaped satellite) with a Machine Learning payload that will be responsible detecting and identifying space debris as it orbits Earth. My current role on the team is Computational Co-Lead.

My Responsibilities

Overseeing the Payload subteam. The plan for our CubeSat launch is to do space debris detection and classification using image processing and computer vision. Therefore, computer vision software and algorithms towards that end comprise a majority of the current interaction of this subteam.
Overseeing software work for Attitude Determination Control Systems (ADCS). ADCS involves mathematics, control theory, programming, sensor integration, and hardware integration.
Overseeing Command and Data Handling (CDH) operations. This subteam is responsible for programming and executing tasks and commands with the Onboard Computer, data handling and storage of processed sensor data, implementing software to interpret commands received from the ground station, and more.

SPACE RACCOON

The name for our satellite is an admittedly complicated acronym that took months to dream up:

Sensor Payload for Acute Classification and Evaluation of Residual Astronomical Components and Colliding Objects in Orbit Neighborhoods (SPACE RACCOON)

Our CubeSat Launch

We plan to launch our satellite through NASA's CubeSat Launch Initiative (CLSI). However, this is a competitive program, and we were required to write large report with nearly 100 pages discussing our plans for the satellite and how our mission aligns with NASA's core objectives. We are currently waiting to hear back about acceptance. If we don't get it this year, we'll simply take what we learned and reapply.