Download pdf version of this CV here
Education
2019–2023
Doctor of Philosophy (PhD), Monash University, Melbourne
thesis
Computing Divergences between High Dimensional Graphical Models
supervisors
Geoff Webb, Daniel Schmidt, Nico Piatkowski
2015–2018
Bachelor of Informatics and Computation Advanced (Honours), Monash University, Melbourne, GPA 3.9/4.0, Graduated with First Class Honours.
thesis
Generating Concept Drift by Shuffling Instances.
majors
Computer Science, Probability & Statistics
Experience
2023–present
Research Associate, Fraunhofer IAIS, Sankt Augustin, Germany
Researching quantum optimisation, both in self-directed research and in applied projects delivered jointly with industry partners.
Researching quantum optimisation, both in self-directed research and in applied projects delivered jointly with industry partners.
- Proposed and developed a framework for incorporating inequality constraints into QUBO formulations without needing additional variables or parameter tuning. To appear at IEEE QCE 2026.
- Proposed and studied how the competing objectives of a multi-objective problem can be scaled and combined so that the resulting QUBO preserves the intended trade-off. Published at IEEE QCE 2025.
- Formulated power-system redispatch as a multi-objective QUBO and evaluated it on quantum annealing hardware, in a joint project with a professional-services firm and a German energy utility company. Published at IEEE DSAA 2025.
- Contributed to a hybrid quantum-classical method for multi-agent pathfinding. Published at ICML 2025.
2016–2017
Undergraduate Research Assistant, Monash University, Melbourne
Researched how to measure and visualise concept drift in both streaming and static data. Built a system to incrementally measure changes to the probability distributions of a data set over time, along with a companion web application.
Researched how to measure and visualise concept drift in both streaming and static data. Built a system to incrementally measure changes to the probability distributions of a data set over time, along with a companion web application.
2017
Quality Assurance Intern, Carsales, Melbourne
Created automated tests for the backend APIs being developed during migration to a microservice architecture. Liaised between multiple teams to ensure sufficient test coverage.
Created automated tests for the backend APIs being developed during migration to a microservice architecture. Liaised between multiple teams to ensure sufficient test coverage.
Skills
quantum
QUBO formulation, multi-objective optimisation, quantum annealing (D-Wave Ocean), gate-model circuits (Qiskit), classical mixed-integer programming solvers
ML
probabilistic graphical models, divergence estimation, concept drift
languages
Python, Julia, Rust, C++, JavaScript, Guile Scheme
tools
GNU Emacs, Git, LaTeX, Guix, Linux
Featured Publications
Hardware-aware QUBO reformulation of constrained binary optimization via the Walsh-Fourier transform
Preprint, 2026. Accepted at IEEE QCE 2026
Standardization of multi-objective qubos
In 2025 IEEE international conference on quantum computing and engineering (QCE), 58–64, 2025.
Hybrid quantum-classical multi-agent pathfinding
In Proceedings of the 42nd international conference on machine learning, 19161–19171, 2025.
Computing divergences between discrete decomposable models
In Proceedings of the AAAI Conference on Artificial Intelligence, 37(10):12243–12251, 2023.
Other Publications
High-order Markov blanket discovery via a k-order relaxation of the faithfulness assumption
In Proceedings of the 42nd conference on uncertainty in artificial intelligence, 3338–3354, 2026.
Quantum adiabatic generation of human-like passwords
In 2025 IEEE international conference on quantum computing and engineering (QCE), 1516–1524, 2025.
Multi-objective quantum power system redispatch
In 2025 IEEE 12th international conference on data science and advanced analytics (DSAA), 1–12, 2025.
Computing marginal and conditional divergences between decomposable models with applications in quantum computing and earth observation
In Knowledge and Information Systems, 66(12):7527–7556, 2024.
Computing Marginal and Conditional Divergences between Decomposable Models with Applications
In 2023 IEEE International Conference on Data Mining (ICDM), 239–248, 2023.