Research

I do research on machine learning and quantum information at University of Waterloo / Perimeter Institute for Theoretical Physics.

Research timeline

2024-2025 theory and simulation of machine learning for (quantum) error correction.

2021-2024 machine learning with quantum computers, e.g. connections between learning and entanglement (2404.07277), strange generalization behavior in quantum models (Quantum) with Maria Schuld at Xanadu, and how bandwidth affects quantum kernel models (TMLR).

2019-2021 near-term implementations of quantum algorithms at Fermilab, e.g. how to select better qubits on Google’s hardware (PRX Quantum), simulating noisy quantum field theory simulations on a lot of GPUs (IEEE, 2111.02396), cheap-but-efficient readout error mitigation (Phys. Rev. A), and quantum machine learning on Google’s Sycamore quantum computer (npj quantum).

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

2017-2018 design and fabrication of superconducting qubits.