Currently I am a PhD student studying machine learning involving quantum systems at the Institute for Quantum Computing and Perimeter Institute for Theoretical Physics. I am supervised by Achim Kempf (Physics of Information Lab).

Since 2021 I have studied theory for machine learning with quantum computers. Most recently, I looked at connections between learning and entanglement (2404.07277). At Xanadu I interned with Maria Schuld to characterize strange generalization behavior in quantum models (Quantum), and separately looked at how bandwidth affects quantum kernel models (TMLR).

In 2019-2021 I was a visiting researcher at Fermilab where I worked on near-term implementations of quantum circuits. I demonstrated how to use better qubits using Google’s hardware (PRX Quantum), studied noise in quantum field theory simulations using a lot of GPUs (IEEE, 2111.02396), studied efficient readout error mitigation (Phys. Rev. A), and implemented a quantum machine learning model on Google’s Sycamore quantum computer (npj quantum).

During 2018-2019 I was on the original team of UWaterloo students who prototyped/developed the software library that eventually became TensorFlow Quantum (2003.02989, press).

During 2017-2018 I worked on design and fabrication of superconducting qubits.