Research

My overarching research vision is to develop novel approaches for optimization using non-classical computing. To this end, I take a two-pronged approach in research: algorithmic theorization and analysis/testing. Combined, I hope to build a more nuanced comprehension of the field and have a wider reach with my work.

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McMahon Lab

Due to the computational difficulty with computing minimums for certain problems like vehicle routing problems with time windows (VRPTWs), it can be viable to approach these problems using non-traditional means such at the coherent Ising machine (CIM), a physical solver. Our goal is to benchmark the CIM and compare it to traditional solvers like CPLEX and Gurobi, particularly for large instances where traditional solvers struggle.

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Institute for Creative Technologies

Humans tend to leverage various heuristics in their optimization of dependent choices. We apply various neural networks along with older statistical models like logistical regression to capture this behaviour using cognitive biases such as loss aversion and anchoring.

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Past Summer Research

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Space Systems Design Studio

Cislunar Explorers

My work at Space Systems Design Studio (SSDS) involved working with Cislunar Explorer's satellite and ground station to make sure that the two were correctly performing their tasks. My efforts were initially devoted towards hardware, and thus I focused heavily on making sure our individual ground station components were working and testing the uplinking and downlinking processes between our model satellite (flatsat) and our ground station. Over time, I began moving more into software, initially working with registration key manipulation to fix our encryption scheme for downlinking and eventually moving onto the optical navigation subteam, where I worked on dynamic position estimation and testing for our satellite using unscented Kalman filters.

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