Projects
Quantum Computing
Quantum-Randomness Generative Art
Using true quantum randomness sourced from Quantum Inspire's Tuna-series processors, this project drives generative visual art through actual quantum measurement outcomes rather than pseudorandom seeding. Early work has focused on executing Bell state circuits as a randomness source and building the pipeline connecting hardware output to visual generation.
Barren Plateau Research
A study sweeping gradient variance across qubit counts and circuit depths in variational quantum circuits, run via statevector simulation in Google Colab. The results showed a clean exponential decay in gradient magnitude, with qubit count as the dominant factor in plateau severity. Findings were compiled into a full research paper.
Variational Quantum Classifier
An ongoing build using Qiskit, applying a ZZFeatureMap and RealAmplitudes ansatz to a two-moons classification task. Current work is focused on refining optimizer performance.
AI
AI Interpretability Tools
Exploratory work on understanding how complex learned systems, whether neural networks or otherwise, arrive at their outputs. Ongoing focus on building tools and methods to make model behavior more transparent and legible.
Writing
Modern Day Extremist
A forthcoming book examining extremist ideology in the 21st century, currently in development.