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 inefficiency of certain problems including vehicle routing problems with time windows (VRPTWs) or image classification, it can be viable to approach these problems using non-traditional means such at the coherent Ising machine (CIM) or other physical solvers. Our goal is to benchmark unconventional computing algorithms against traditional frameworks, showcasing increased energy efficiency in these domains.

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Computational Imaging Lab

By combining ideas from machine learning, signal processing, optics, computer vision and physics, better imaging systems can be constructed via the co-design of optics, algorithms, and high-level tasks. To this end, I have worked on the creation of synthetic datasets for realistic physical biases in hardware imagers, along with performing model evaluation for various computational imaging tasks such as image classification with optical hardware.

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Helbling Lab

Aquatic environments are challenging to monitor, motivating millimeter-scale bio-inspired robotic swimmers that use fin-based propulsion to maneuver through confined natural and engineered waterways (e.g., streams, lakes, pipes) while enabling studies of fish-locomotion hydrodynamics. To contribute to this body of research, I introduced tracking software and developed control algorithms for millimeter-scale robotic swimmers dubbed DanioBot.

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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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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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