Working in the Balloon Research and Development Lab developing algorithm for ideal balloon predictions, scientific instruments, and writing code to be used on future missions.

Developed comprehensive lesson plans and assignments to instruct students in circuit design, soldering, and the interpretation of specification sheets. Guided students through practical exercises, enabling them to create functional PCBs by the end of the semester. In a separate lab, students were instructed through the creation of simple neural network architectures, layer types, activation functions, and common optimization techniques enabling students to recreate the work done in the paper “Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning” by Stanford researchers.

Conducted research on two different projects, An Open Source droplet digital polymerase chain reaction (ddPCR) Machine, and Handwritten Sheet Music digitization.Open Source ddPCR:Designed optics system to focus laser onto a flowing sample while collecting the scattered light. Several custom fittings were modeled in Fusion 360 and 3D printed with the Cura slicer. Developed a signal filtration, amplification, and digitization circuit. Developed a high-sample rate C++ GUI allowing users to create new trials, monitor results in real-time, and export the data. Developed a peak detection and classification algorithm using a custom TensorFlow deep learning convolutional neural network model in combination with generic peak detection algorithms.Handwritten Sheet Music Digitization:This project uses a YOLOv8 convolutional neural network to detect both staff lines before detecting music notes within each measure. The form is then reconstructed using coordinate info of each note within their measure to dictate pitch and timing.