Members
How to join?
Membership is open to University of Melbourne academics leading a research group with interest in quantum technology, which ranges from quantum computing and quantum information to quantum many-body physics and condensed matter, but also includes quantum methods for life sciences, optimisation, and finance. While most members will be continuing academics, MIQT also accepts continuing (research contingent) and fixed-term academics, who are expected to be part of the university for the foreseeable future (at least 2-3 years), such as longterm/senior research fellows and awardees of larger ARC Grants.
You can apply for membership by contacting the current chair of the Executive Committee, as listed here.
Members
The following senior academics are members of MIQT:
| Name | Faculty: School/ Department | Section: Method | Keywords | Research Summary | |
|---|---|---|---|---|---|
| Adrian Pearce | FEIT: School of Computing and Information Systems | QComputing: Experiment | Quantum Computing; Quantum Machine Learning | adrianrp@unimelb.edu.au | |
| Alastair Stewart | MDHS: School of Biomedical Sciences | astew@unimelb.edu.au | |||
| Alex Wood | Science: School of Physics | QDiscovery: Experiment | Quantum Sensing; Quantum Optics | alexander.wood@unimelb.edu.au | Details |
| Andy Martin | Science: School of Physics | QDiscovery: Theory & Experiment | Quantum Optics; Quantum Sensing; Quantum Gases | martinam@unimelb.edu.au | Current research focuses on (i) properties of ultracold quantum gases; (ii) quench dynamics in quantum systems and (iii) in collaboration with Dr Alex Wood, quantum sensing with nitrogen-vacancy defects in diamond and the effects of physical rotation on quantum systems. Previous research has focused on (i) superconductivity, dephasing and charge fluctuations mesoscopic devices; (ii) interfaces and disorder in high temperature superconductors and (iii) the breakdown of the quantum Hall effect. |
| Ann Roberts | Science: School of Physics | QDiscovery: Theory & Experiment | Quantum Optics; Quantum Sensing | ann.roberts@unimelb.edu.au | My research is focussed on investigating light-matter interactions on the nanoscale. As a member of the ARC Centre of Excellence for Transformative Meta-Optical Systems I am interested in using nanostructures to generate, manipulate and detect light. This includes using defined nanostructures to control and direct the emission of light from quantum dots and other emitters and use metasurfaces to sense the classical (and potentially quantum) properties of light. |
| Carsten Murawski | FBE: Department of Finance | QComputing: Experiment | Quantum Computing | carstenm@unimelb.edu.au | Carsten Murawski is Professor of Finance at the University of Melbourne and Director of the Centre for Brain, Mind and Markets. He leads the Decision, Risk and Financial Sciences PhD program and the Melbourne–Bonn joint PhD. His research spans decision neuroscience, economics, theory, and consumer behavior, focusing on neurocognitive processes in decision-making, studied with experiments, neuroimaging, and translational applications in health and performance. |
| Chris Chantler | Science: School of Physics | QDiscovery: Theory & Experiment | Quantum Optics; Quantum Matter or Materials; Advanced Relativistic QM and QED, theory and experiment | chantler@unimelb.edu.au | X-ray Optics and Synchrotron Science, Advanced Relativistic Quantum Mechanics (RQM) and QED: 50% theory, 50% experiment, 50% atomic physics, 50% condensed matter science. We discover new processes in RQM with synchrotrons & labs, & test QED. We have led characteristic structure theory for 20 years. We have new theory on the imfp, and one of three theoretical databases of the US on the interaction of photons with matter. We developed several new experimental techniques, and several new theories. |
| David Jamieson | Science: School of Physics | QDiscovery: Experiment | Quantum Matter or Materials; Quantum Computing | d.jamieson@unimelb.edu.au | My research focus is experimental condensed matter physics, and my group specialises in the ion implantation of silicon for creating both donor spin qubits and ultrapure isotopically-enriched silicon-28. I have extensive experience in ion beam physics, quantum nanotechnology and materials science including silicon and diamond. My work on deterministic ion implantation for single atom doping is a key contributor to the development of silicon-based quantum computer devices in Australia as part of the Centre for Quantum Computation and Communication Technology, where I am a chief investigator. |
| David Simpson | Science: School of Physics | QSensing: Experiment | Quantum Sensing; Quantum Biology | simd@unimelb.edu.au | My current research is focused on diamond-based quantum sensors for biomedical and precision magnetometry applications. I am focused on developing of high-resolution imaging techniques to visualise the electrical and magnetic properties of biological systems. These advances are being pursued in start-up companies I have co-founded Chromos Laboratories, FeBI Technologies and Phasor Quantum. |
| Elisabetta Barberio | Science: School of Physics | QSensing: Experiment | Quantum Sensing; Using Quantum Sensing for Experimental Particle Physics | barberio@unimelb.edu.au | We will use quantum sensing with superconducting bolometers to search for low-mass dark matter. Transition-edge sensors at cryogenic temperatures detect tiny energy deposits and phonons with sub-eV precision. Modular targets like superfluid helium and polar crystals enable exploration of interactions beyond conventional detectors, demonstrating the power of quantum-enhanced measurement for fundamental physics. |
| Farhad Farokhi | FEIT: Department of Electrical and Electronic Engineering | QComputing: Theory | Quantum Information; Quantum Communication; Quantum Control | farhad.farokhi@unimelb.edu.au | Farhad's research focuses on the interplay between information and physics across classical and quantum systems with applications to control, estimation, security, and privacy. |
| Gawain McColl | MDHS: Florey Department of Neuroscience and Mental Health | gawain.mccoll@florey.edu.au | |||
| Harry Quiney | Science: School of Physics | QDiscovery: Theory | Quantum Matter or Materials; Quantum Optics; Quantum Computing | quiney@unimelb.edu.au | I study the formulation and computational implementation of relativistic theories of quantum electrodynamics, and their applications to atomic and molecular physics and quantum chemistry. |
| Jan de Gier | Science: School of Mathematics and Statistics | QDiscovery: Theory | Solvable Lattice Models | jdgier@unimelb.edu.au | I study solvable lattice models—an area of mathematical physics and statistical mechanics rich in connections to pure and applied mathematics. This field uses tools from algebra (e.g., Yang–Baxter equation, Hecke algebras, quantum groups) and analysis (e.g., complex analysis, elliptic curves), often revealing unexpected links between diverse research areas. |
| Jeff McCallum | Science: School of Physics | QDiscovery: Experiment | Quantum Matter or Materials; Quantum Computing; Ion Implantation for Quantum Computing Device Fabrication | jeffreym@unimelb.edu.au | Prof McCallum's group specialises in solid state physics with a strong focus on materials science, interface nd defect physics and quantum applications in materials like silicon. He is an expert in ion implantation of silicon and semiconductor physics and is a key contributor to Australia's silicon quantum computing effort. |
| Kate Smith-Miles | Science: School of Mathematics and Statistics | QComputing: Experiment | Quantum Optimisation; Quantum Computing; Quantum Machine Learning | smith-miles@unimelb.edu.au | We are exploring the competitiveness of quantum optimisation algorithms such as Quantum Annealing and QAOA, considering combinatorial optimisation problems such as Travelling Salesman Problem and MAXCUT. We use Instance Space Analysis - a methodology developed by my group for "stress testing" algorithms - to better understand quantum circuit design performance, algorithm performance, and parameter choices, for various kinds of instances of a problem. This is critical to understanding potential quantum advantage. |
| Ken Crozier | FEIT: Department of Electrical and Electronic Engineering | QDiscovery: Experiment | Quantum Optics; Nano- and Meta-Optics | kenneth.crozier@unimelb.edu.au | Kenneth Crozier is Professor of Physics and Electronic Engineering and Deputy Director of the ARC Centre of Excellence in Transformative meta-optical systems (TMOS) at the University of Melbourne. His research interests are in nano- and micro-optics, with an emphasis on optical metasurfaces, optical nanotweezers, and photodetectors based on nanomaterials. |
| Kim-Anh Le Cao | Science: School of Mathematics and Statistics | QComputing: Theory & Experiment | Quantum Computing; Quantum Biology | kimanh.lecao@unimelb.edu.au | Our lab focuses on the development of computational methods, their applications in areas informed by biology, and the training of the new generation of computational biologists and data analysts. Our area of expertise is in the integration of biological ‘omics data (transcriptomics, proteomics, metabolomics etc., as well as microbiome, metagenomics, single cell transcriptomics and multi-omics) with multivariate and dimension reduction methodologies, selection of features of biomarkers in large biological data sets and R software development. |
| Liz Hinde | Science: School of Physics | QDiscovery: Experiment | Quantum Optics; Quantum Sensing; Quantum Biology | elizabeth.hinde@unimelb.edu.au | We are a cellular biophysics lab developing advanced fluorescence microscopy methods, including quantum-enhanced fluorescence spectroscopy, to quantitatively probe nuclear architecture in living cells. Our research applies these technologies to study chromatin organization, transcription factor dynamics, and the biophysics of DNA repair, enabling nanoscale insights into fundamental nuclear processes. |
| Lloyd Hollenberg | Science: School of Physics | QDiscovery: Theory | Quantum Computing; Quantum Information; Chem/Optimisation/Bio/ML | lloydch@unimelb.edu.au | Quantum User Interface (QUI): qui.research.unimelb.edu.au |
| Lucas Hackl | Science: School of Physics | QDiscovery: Theory | Quantum Information; Quantum Computing; Condensed Matter, Relativistic Quantum Information | lucas.hackl@unimelb.edu.au | The Mathematical Quantum Information (MQI) Group aims to understand fundamental aspects in a wide range of physical systems, including many-body systems, relativistic systems and spacetime, through the lens of quantum information and mathematical physics. This includes the Mathematics of Gaussian states, Variational Methods, Entanglement Production, Entanglement and Typicality, Quantum Field Theory in Curved Spacetime, Black Hole Information Paradox, Extended Pauli Principle and more. |
| Marcus Giansiracusa | Science: School of Chemistry | QDiscovery: Theory & Experiment | Quantum Matter or Materials | marcus.giansiracusa@unimelb.edu.au | The chemical design and optimisation of new molecular qubits followed by characterisation of coherence times using electron paramagnetic resonance spectroscopy |
| Mario Kieburg | Science: School of Mathematics and Statistics | QDiscovery: Theory | Quantum Information; Random Matrix Theory | m.kieburg@unimelb.edu.au | My research is on Random Matrix Theory which has a vast of applications ranging beyond Physics and Mathematics such as Telecommunications systems and Time Series Analysis. The mathematical tools I am using are Harmonic Analysis and Group & Representation Theory, Orthogonal functions and polynomials, Supersymmetry & Graded Algebras. Those I apply to physical problems in Quantum Chaos, Quantum field theory, Quantum Information Theory. |
| Marta Garrido | MDHS: School of Psychological Sciences | marta.garrido@unimelb.edu.au | |||
| Martin Sevior | Science: School of Physics | QComputing | Quantum Computing; Quantum Machine Learning; Noise in Quantum Computers | martines@unimelb.edu.au | Martin's research is in the field of Experimental Particle Physics and Quantum Computing. He undertakes research into Quantum Machine Learning, Quantum Error correction, simulations of Quantum Computers, and noise in Quantum Computers. |
| Michael Menden | MDHS: Department of Biochemistry and Pharmacology | QDiscovery: Experiment | Quantum Biology; Quantum Medicine | michael.menden@unimelb.edu.au | The Menden Lab develops advanced artificial intelligence and biostatistical methods to improve precision medicine. Our work integrates high-throughput drug screening, multi-omics, and clinical data to predict drug responses, discover biomarkers, and guide patient stratification. We apply generative AI and digital twins to simulate disease progression and treatment outcomes, with applications spanning oncology, neurodegenerative, respiratory, and other complex diseases. |
| Muhammad Usman | Science: School of Physics | QDiscovery: Theory | Quantum Computing; Quantum Machine Learning; Quantum Software Engineering | muhammad.usman@unimelb.edu.au | My work is focused on quantum algorithms and quantum software engineering. We work on a range of topics including quantum compiler design, quantum error correction, quantum machine learning, quantum optimisation, quantum biotechnology, and quantum control. We also develop classical machine learning models which can help quantum systems. |
| Nitin Yadav | FBE: Department of Finance | QComputing: Experiment | Quantum Computing | nitin.yadav@unimelb.edu.au | Nitin Yadav is a Senior Lecturer in computational finance. He studies the complexity of decision-making, applying computer science and AI techniques to decision making. His research also covers automated planning, service composition, and intelligent agent systems. |
| Rajkumar Buyya | FEIT: School of Computing and Information Systems | QComputing | Quantum Computing; Quantum Communication; Quantum Cloud Computing | rbuyya@unimelb.edu.au | Recent advances in quantum hardware are enabling new applications, but quantum software engineering faces challenges due to diverse languages and platforms. Our iQuantum Initiative addresses these by exploring core research issues and building tools to support (1) rapid app development and deployment, and (2) modeling and simulation of quantum environments to advance the quantum computing paradigm. |
| Richard Sandberg | FEIT: Department of Mechanical Engineering | QComputing: Experiment | Quantum Computing; Quantum Machine Learning; Quantum Computational Fluid Dynamics | richard.sandberg@unimelb.edu.au | Computational Fluid Dynamics (CFD) remains constrained by classical computing resources, despite the availability of Exa-scale supercomputers. We are looking into options of how to leverage QC for CFD, or how to use quantum concepts to accelerate CFD on classical computers. |
| Rob Evans | FEIT: Department of Electrical and Electronic Engineering | QComputing: Theory | Quantum Information; Quantum Sensing | robinje@unimelb.edu.au | Rob Evans is an Emeritus Professor at Department of Electrical and Electronic Engineering at The University of Melbourne. He was previously a Laureate Professor and the Director of the Victoria Research Laboratory of National ICT Australia (NICTA). He is a Fellow of the Australian Academy of Science, Fellow of the Australian Academy of Technological Sciences and Engineering, Fellow of the Institution of Engineers Australia, and Fellow of the Institute of Electrical and Electronic Engineering. |
| Sarah Erfani | FEIT: School of Computing and Information Systems | QComputing: Experiment | Quantum Machine Learning; Quantum Computing | sarah.erfani@unimelb.edu.au | I am interested in quantum machine learning, understanding model robustness and reliability under adversarial threats and natural changes. |
| Stephan Rachel | Science: School of Physics | QDiscovery: Theory | Quantum Matter or Materials; Quantum Computing | stephan.rachel@unimelb.edu.au | The quantum matter group of Stephan Rachel specializes in (1) topological quantum computing, (2) quantum simulations on IBMQ and (3) quantum materials more broadly. Prominent examples of quantum simulations on the IBM Quantum Computers includes our work on Discrete Time-Crystals. Our interest in quantum materials ranges from semiconductors and superconductors to quantum magnets. |
| Steven Prawer | Science: School of Physics | QMaterial: Experiment | Quantum Matter or Materials; Quantum Sensing; Diamonds | s.prawer@unimelb.edu.au | Our work is focused on the use of diamond and related materials for practical quantum applications. We have developed a sophisticated tool kit for the fabrication of diamond materials and devices using semiconductor fabrication processes such as plasma processing, ion beam implantation and doping, and laser sculpting. Target products are integrated chips for optical quantum computing, nanofluidic devices for quantum sensing and ultralong lasting diamond based batteries |
| Tansu Alpcan | FEIT: Department of Electrical and Electronic Engineering | QComputing: Experiment | Quantum Machine Learning; Quantum Computing | tansu.alpcan@unimelb.edu.au | We focus on adversarial QML, cybersecurity applications, hybrid and split QML, and engineering applications. In collaboration with CSIRO/Data61. |
| Thomas Quella | Science: School of Mathematics and Statistics | QDiscovery: Theory | Quantum Matter or Materials; Quantum Information; Quantum Computing | thomas.quella@unimelb.edu.au | The research group of Thomas Quella studies the mathematical foundations of equilibrium and non-equilibrium quantum matter, with a particular emphasis on the investigation of exactly solvable models, non-trivial topological features and the interplay of (generalised) symmetry and entanglement. The insights are then used in more applied contexts such as quantum computing or the efficient simulation of quantum systems. |
| Tracy Nero | MDHS: Department of Biochemistry and Pharmacology | tracy.nero@unimelb.edu.au | |||
| Udaya Parampalli | FEIT: School of Computing and Information Systems | QComputing: Theory & Experiment | Quantum Computing; Quantum Optimisation; Quantum Information | udaya@unimelb.edu.au | Udaya’s group researchers in Quantum error correction, Quantum Machine Learning and Quantum programming languages. He leads research on Quantum computing at the School of Computing and Information Systems at the University of Melbourne.. We have conducted research applying AI algorithms to quantum circuit design, as well as incorporating intuitions and heuristics from classical AI research into quantum machine learning (QML) model design. |