Our People

Professor of Data Science at the University of Adelaide, studying how information moves over social networks using mathematical models, coupled with data science techniques. Research interests: computational social science, human dynamics, online social networks, as well as data assimilation and the mathematics of weather and climate.

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Lecturer in Data Science and Statistics at the University of Adelaide, with chief interests in Data Assimilation (DA), the mathematical and statistical question of how to combine an uncertain model forecast with data, and numerical multiscale methods. A key focus on projective integration that accelerates simulation of stiff systems and patch dynamics. Interested in coherent structure DA, projected DA, non-gaussian problems and surrogate DA.

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Professor at the University of Adelaide within the School of Computer and Mathematical Sciences, and (interim) Director of the Teletraffic Research Centre (TRC). Made a Fellow of the IEEE in 2019, and a Fellow of the ACM in 2018. Interested in measurement/estimation, modelling and control of networks, in particular traffic, topology, performance analysis, routing and security.

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Research activities are mainly in the fields of Applied Mathematics, Statistics and Psychology. Completed PhD in the area of Mathematical Psychology, looking at two broad areas: (1) Effective wastewater sampling techniques for measuring illicit drug consumption extent; (2) Application of cognitive models in a clinical context. Published first author papers in both fields with both cross-disciplinary and cross-institutional teams. Also interested in statistical applications across all fields and currently researching in the forensic science space. Dr. Melissa Humphries was recently awarded a place on the prestigious Science & Technology Australia (STA) Policy Committee for the Science, Engineering, Technology and Maths (STEM) sector. The Committee serves to drive progress in STEM sector policy in areas such as diversity, equity and inclusion.

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Started his career as a veterinarian. After 12 years, went back to university to study maths and achieved a PhD in statistics. Lecturer in statistics at the University of Adelaide and an applied statistician with expertise in biostatistics, bioinformatics, and network analysis.

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Lecturer at the University of Adelaide within the School of Computer and Mathematical Sciences. Previously, worked as a postdoctoral fellow in the Queensland University of Technology (QUT) Centre for Data Science, and a research associate in the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) at QUT. Research: working with imperfect data and models to better monitor the environment with a focus on developing hybrid approaches of statistical methodology and machine learning.

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Lecturer at the University of Adelaide, creating survey weights and thinking about non-representative data, multilevel modelling, poststratification, causal inference, Bayesian inference and all manner of other related fields to making inference from the social sciences.

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Senior Lecturer in Applied Mathematics at the University of Adelaide, where research bridges the fields of data science and stochastic modelling. Strongly believes that most data can be better understood through the lens of a generative or mechanistic model. Particular expertise in mathematical epidemiology and has developed new methods for fitting epidemic models to outbreak data to inform planning and decision making. Currently interested in how new generative AI techniques (diffusions, normalising flows) can be leveraged to create fast and flexible models for complex datasets.

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Professor of Statistical Machine Learning in the School of Computer and Mathematical Sciences. Previously an Associate Professor at the Department of Statistics, University of Oxford, a Fellow of Mansfield College, and a Faculty Fellow of the Alan Turing Institute. Conducts research at the interface between machine learning and statistical methodology. Research interests include: statistical machine learning, reproducing kernel Hilbert spaces, nonparametric and large-scale hypothesis testing, measures of association and multivariate interaction, trade-offs between computational and statistical efficiency, information theory.

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Particle astrophysicist, using searches in astrophysics and particle physics experiments to find and test new theories of what the universe is made of and how it came to be. This includes: Co-leading the GAMBIT collaboration – a team who perform detailed statistical fits of new physics models including new models of dark matter – and will soon include cosmological models and models that explain neutrino masses, co-leading the Dark Machines initiative, searches for new particles at the Large Hadron Collider (LHC), working to improve theoretical models of the new signals searched for at the LHC, and working in the Australian Cherenkov Telescope Array consortium.

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Senior Lecturer at the School of Agriculture, Food and Wine. Expertise in nonparametric inference and applied statistics in academic research and consulting in human nutrition, food sensory, soil and plant sciences, including design and analysis of experiments and observational studies. Interested in collaborations on three themes: (1) research on robust statistical methods, in particular the theory of rank methods, (2) research in food sensometrics, outside the consumer research and (3) applied statistics research in application to agriculture and food data.

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Professor of Practice in the School of Computer and Mathematical Sciences, and Director of Industry Engagement in the ADSC. Obtained his PhD in pure and discrete mathematics with a minor in business from the University of Wisconsin – Madison. Successful career at senior executive level in finance and risk management in Australia and internationally. Following some senior roles in New York, was a member of the Management Board of ANZ Banking Group and Group Chief Risk Officer from 1999-2004. Since 2008 Dr Lawrence has run an international consulting business providing strategic advisory services to financial institutions and regulators regarding a wide range of risk management and governance matters.

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