Hello! I am a PhD student at Chapman University, learning how to build a better qubit.

My background in mathematics and computer science initially introduced me to the field of quantum computing via Grover’s algorithm. I did some preliminary undergraduate studies on what aspects of quantum mechanics give Grover’s algorithm its quantum advantage.

Today, my interests have developed more towards the hardware that implements the qubit. In particular, I want to learn more about continuous measurement (especially weak measurement) and the engineering aspects of qubit construction. I also have a strong interest in quantum information, as it is the concept of physical information and the effects of measurement which first piqued my interest in all things quantum.

My coursework at Chapman has given me knowledge in the mathematical foundations of statistical analysis, machine learning, and scientific computing. I also have gained practical experience applying these foundations using Python (with Numpy, Scikit-Learn, TensorFlow, SciPy, Matplotlib, Pandas, etc.) and R (TSA, Tidyverse, ggplot2, R shiny, etc.). Additionally, through my computer science background I have thorough knowledge of programming best practices, version control with Git, and database administration. I have experience in Python, Haskell, Java, Javascript, SQL, C, C++ and R (although I am most comfortable in Python, R, and C/C++).

In my spare time, I love to hike, cook, and rant about the Landauer cost whenever given the chance.

  • Machine Learning
  • Quantum Information
  • Continous Measurement and Weak Measurement
  • Category Theory
  • Quantum Algorithms and Quantum Supremacy
  • B.S. in Computer Science, 2020

    Chapman University

  • B.S. in Mathematics, 2020

    Chapman University