18 y/o research intern at IQC, invested in QML

"Step by Step, Ferociously"


  • Working on a mentorship project integrating Nvidia GPU compability into TensorFlow Quantum
  • Learning as a freshman at the University of Waterloo for computer engineering
  • New (June 20, 2022): Was selected as a member of The Masason Foundation

Where I've worked

Institute for Quantum Computing - Research Intern

  • Researched a method to effectively realize Bose Hubbard Hamiltonian dynamics through Rydberg atom arrays.
  • Built infrastructure to run 100+ theoretical simulations under various experimental conditions and constraints.
  • Developed a python package for efficiently calculating sparse matrix exponentials.

Zapata Computing - Quantum AI Intern

  • Researched more efficient training methods for quantum generative models.
  • Developed Orquestra codebase to enable effortless development of QGANs (quantum generative adversarial networks).

What I've done

April 2022 - Authored article on quantum graph neural networks [article]

  • Wrote a deep dive into classical graph neural networks, graph convolutions & attention-based graph learning, and QML applied to high energy physics [article]

Feb 2022 - Top 5 QHack 2022 Project [github]

  • Improved a hybrid quantum graph neural network that was used to solve the particle trajectory reconstruction problem [link]

Dec 2021 - Authored closing chapter in the Qiskit QML course [link] [blog]

  • As part of the Qiskit Advocate Mentorship Program, authored the chapter on QGANs for the newly released quantum machine learning course by IBM's Qiskit team [link]

June 2021 - Built a project applying quantum generative adverserial networks to learn sequential data [link]

  • Under the guidance of a research scientist from AWS Braket, built a hybrid quantum-classical version of the Wasserstein generative adversarial network. [link]
  • Evaluated learnability of conditional QGANs for sequential data prediction [link]
  • Investigated heuristics for optimal training of QGANs [link]

Feb 2021 - Quantum portfolio optimization project with QHack 2021 [link]

  • Used quantum generative adversarial networks for portfolio optimisation
  • We built an exploratory project applying qGANs and VQE to solve the mean-variance portfolio problem. This placed our team in the 95th percentile of participants in the QHack quantum machine learning hackathon winning over $4000 in AWS credits.

Apr 2021 - Authored an overview of quantum generative adversarial networks [link]

  • Explained QGANs for quantum computing enthusiasts.
  • Derived the cost function and other mathematical properties stated in the original paper

Feb 2021 - Generalized QAOA to solve the Max-Cut problem [link]

  • Built a general quantum approximate optimization algorithm for solving weighted cases of the Max-Cut problem

Mar 2021 - Developed an AI SMS-based text engine in a project partnered with UN Women [link]

  • An alternative search engine that we’ve developed & trialed, allowing rural South Africans with a mobile phone to be able to send internet search queries & receive back summarized results all through SMS
  • Placed top 3 in challenge out of 150+ teams — project built as part of a TKS challenge w/ United Nations.

Dec 2020 - Challenge project for Instacart [link]

  • Addressed customer experience holdbacks by providing an easy-to-implement solution filling data gaps in the Instacart to retailer to CGP pipeline.
  • Won first place in consulting challenge out of 30+ teams.