Emperor is a quad-copter drone-based oceanographic instrument used to measure conductivity, temperature, and depth in the upper coastal ocean (CTD). These measurements are essential for oceanographic research, where the current measurement methods such as the shipboard sampling method produces accurate and reliable results, at the cost of being very expensive and time-consuming.

CubeSats is the number one way for innovation in space research. This can be attributed to their significantly lower costs relative to conventional satellites and greater accessibility to space via a rideshare program. The main constraint, however, is the low average power generation due to their small size, meaning they have limited surface area on their external walls for solar cell assembly. Our solution aims to tackle that problem by introducing an origami-inspired solar deployment method which utilizes shape memory alloys as actuators.

The National Oceanic Atmospheric Administration (NOAA) tasks our team to develop whale safe fishing gear to prevent whale entanglements due to the fishing lines. The entanglements entail losing parts of the whales' bodies and eventually, their deaths. With the unusual amount of whale entanglements due to in 2016, the fishery faces strict regulations that impact the fishermen's livelihood. Keeping in mind of the necessity to create cost-effective devices, our team focuses on two different aspects of the solution: prevention and fail-safe.

GreeNN is an optical neural network designed with the goal of reducing the carbon footprint of image classification. Increasing the complexity of computations for image classification in traditional silicon based hardware is associated with a significant energy cost. The team’s solution implements the most computationally intensive task of image classification in free space optics with high energy efficiency. The setup encodes an image onto a green laser beam using a digital micromirror device and performs a convolution calculation on a spatial light modulator.