Physics Projects
Liquid Helium Dip Probe
J. C. Seamus Davis Group, 2014
I designed a versatile dip probe for use in a standard 68L liquid helium storage dewar. Components were build by the Cornell machine shop based on my CAD model. I fit the probe with superconducting wire to provide electrical signals to experiments mounted on the modular stage.
Image: (Left) CAD model featuring the vacuum can contents, (Middle) Probe with completed wiring, (Right) Testing probe in LN2 dewar.
CS129: Applied Machine Learning, 2021
Detecting Defects with Deep Learning
My project team and I applied the Faster R-CNN object detector algorithm to detect defects in simulated electron microscope images of molecular graphene. The neural network spots carbon atoms that are not part of the hexagonal lattice structure (left image). We then utilized the deep learning inpainting algorithm to remove the defect from the image and replace it with the ideal pattern (right image).