Hi, I'm Aaron Goidel


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About Me

Currently pursuing Computer Science and Linguistics at the University of Toronto, I am deeply involved in NLP research on cross-linguistic semantics. My dual roles as a Research Assistant and a TA for Theory of Computation showcase my commitment to both theoretical understanding and its practical applications.

I've worked with some fantastic organizations

  • At NASA, I contributed to launch software for the groundbreaking Artemis program.
  • While at MLabs, I developed tools and smart contracts for financial tech on the Cardano blockchain.
  • My media tenure with Highsnobiety offered a unique blend of tech and art where I helped build data collection pipelines and content management software.
  • With the NSA, I researched novel applications of machine learning for security applications and fortified Linux systems security.

Beyond my studies, I am a fervent tinkerer and reader, driven by a belief that software can shape a brighter, more informed future.

My academic passions lie in computational linguistics and the intricate world of languages and compilers. As the Technical Director of the Math and Computer Science Society, I mentor peers, bridging theoretical concepts with practical execution.

Outside academia, I've crafted production-grade software for diverse teams. My explorations in computer science span from designing languages and simulating physics to delving into blockchain. Off the screen, my love for culinary arts keeps me experimenting in the kitchen, while music is both a solace and a creative outlet.


Cookie - Dynamic Cookbook

Cookie - Dynamic Cookbook

Better cooking through ml and graph theory. Recipe customization, ingredient substitution, realtime custom interactive steps.



A ml-powered visual product reccomendation tool. Using cnn feature extraction and attention, find products that match the style of an image.

NeRF 3D Reconstruction

NeRF 3D Reconstruction

An video to AR 3D reconstruction pipeline using Neural Radiance Fields. A deep learning model predicts scene radiance for a volumetric renderer.

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