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Dr Joanne De Faveri is a Senior Research Fellow in Statistics with QAAFI at The University of Queensland. Dr De Faveri’s research is based on developing new improved statistical and hybrid (integrated statistical / machine learning) methods to deliver significant genetic gains for plant breeding and pre-breeding programs. Her primary interests lie in spatio-temporal modelling of longitudinal data and the integration of high throughput phenotyping (HTP) (from sensors, hyperspectral, aerial images), genomic and environmental information for improved variety predictions.

Prior to joining UQ Dr De Faveri worked with CSIRO as part of SAGI-North, the Statistics for the Australian Grains Industry project, where she researched and applied statistical methods to grains research projects, in particular focussing on methods for High Throughput Phenomics. She also has over 20 years’ experience as a Biometrician with the Department of Agriculture & Fisheries (DAF), researching and applying statistical methods and training staff across a wide range of agricultural research projects in field crops, horticulture, beef, dairy, fisheries, aquaculture, and in particular, horticulture breeding programs.

Dr De Faveri has been invited to speak at National and International conferences on statistical methods for incorporating HTP data in variety trials and has developed national and international collaborations with colleagues at CSIRO, University of Queensland, University of Adelaide, Dept Agriculture & Fisheries, Wageningen University and CIMMYT.

Radislav (Slava) Vaisman is a faculty member in the School of Mathematics and Physics at the University of Queensland. Radislav earned his Ph.D. in Information System Engineering from the Technion, Israel Institute of Technology in 2014. Radislav’s research interests lie at the intersection of applied probability, statistics, and computer science. Such a multidisciplinary combination allows him to handle both theoretical and real-life problems, in the fields of machine learning, optimization, safety, and system reliability research, and more. He has published in top-ranking journals such as Statistics and Computing, INFORMS, Journal on Computing, Structural Safety, and IEEE Transactions on Reliability. The Stochastic Enumeration algorithm, which was introduced and analyzed by Radislav Vaisman, had led to the efficient solution of several problems that were out of reach of state of the art methods. In addition, he is an author of 3 books with three of the most prestigious publishers in the field, Wiley, Springer, and CRC Press. Radislav serves on the editorial board of the Stochastic Models journal.

I completed my PhD, supervised by Dr. Jan Engelstaedter, investigating host shift dynamics of parasites within a host clade. In this project I am was interested in understanding the long-term dynamics and consequences of host-shift dynamics, while taking into account the evolutionary relationships between host species. I was interested in identifying predictable patterns in the distribution of pathogens using statistical and mathematical modeling.

Currently, I am a postdoctoral researcher working at the University of Queensland under Dr. Christine Beveridge. I will be creating computational models of plant hormone signalling in order to make predictions on the phenotypic outcomes of plant species.

Dr Forbes has an extensive background in applying optimisation methods to industrial problems. He spent over 20 years working in industry before returning to academia in 2010. Dr Forbes now focuses on building Mixed Integer Programming models for industrial applications and specialised techniques for solving difficult Mixed Integer Programming models.

Dr Forbes has experience in many application areas including

• vehicle routing;
• supply chain optimisation;
• mine planning;
• public transport vehicle and crew scheduling and rostering (buses, trains and planes);
• hospital staff scheduling and rostering, including operation scheduling and room allocation;
• power generation and planning;
• network design (communications, electricity, gas, water);
• maintenance scheduling.

Dr Archie Chapman is an Associate Professor in Computer Science in the School of Electrical Engineering and Computer Science.

Archie develops and applies principled artificial intelligence, game theory, optimisation and machine learning methods to solve large-scale and dynamic allocation, scheduling and queuing problems. His recent research has focused on applications of these techniques to problems in future power systems, such as integrating large amounts of renewable power generation and using batteries and flexible loads to provide power network and system services, while making best use of legacy network and generation infrastructure.

Prior to joining UQ, Archie was Research Fellow in Smart Grids at the University of Sydney (2011-2019), and a postdoc fellow at the University of Southampton (2009-2010), where he completed his PhD.

Nan Ye's research interest spans machine learning, statistics and optimization. He has published papers on topics including sequential decision making under uncertainty, weakly supervised learning, probabilistic graphical models, statistical learning theory, in venues such as NeurIPS, ICML, ICLR, UAI, JAIR, JMLR. He received an IJCAI-JAIR Best Paper Prize in 2022, and a UAI Best Student Paper Award in 2014.

He is a Lecturer in Statistics and Data Science in the School of Mathematics and Physics in University of Queensland. He previously held postdoc positions at QUT and UC Berkeley from 2015 to 2018, and at NUS from 2013 to 2014. He obtained his PhD in Computer Science from NUS, and completed double first-class honors in Computer Science and Applied Mathematics, also from NUS.

Please visit his personal webpage for more information: https://yenan.github.io/.

Dr Evgenii Nekhoroshev is a Postdoctoral Research Fellow at the School of Chemical Engineering and a member of the Pyrometallurgy Innovation Centre led by Prof. Evgueni Jak.

He graduated with a Master in Chemistry (chemical thermodynamics) from Lomonosov's Moscow State University, Deparment of Chemistry in 2012. His Master's Thesis was "Thermodynamic optimization of the NaOH-Al(OH)3-Na2SiO3-H2O system for applications in Bayer's process of bauxite treatment" as part of a bigger project initiated in collaboration with Rusal company aimed at utilisation/valorisation of red mud residues accumulated during the production of aluminium oxide from bauxite ores.

In 2019, he completed a PhD in Metallurgical Engineering at Ecole Polytechnique of Montreal, Canada within The Centre For Research in Computational Thermodynamics (CRCT), where he acquired expertise in FactSage software, multicomponent database development, and was included in the list of official collaborators of FactSage. His PhD thesis was "Thermodynamic optimization of the Na2O-K2O-Al2O3-CaO-MgO-B2O3-SiO2 system" sponsored by Glass Consortium including Corning and SCHOTT glass producers. The purpose of the database he developed was to assist the industry in designing new glasses with special properties: chemically hardened glasses (smartphones), technical glasses with high thermal and chemical resilience (boron-containing glasses), chemically inert glasses, etc.

Short after receiving his PhD, Dr Evgenii Nekhoroshev accepted a position at The University of Queensland as part of the Pyrometallurgy Innovation Centre's team where he has an official title of Theme Leader in Thermodynamic Computations, combining his broad expertise in metallurgy, chemical engineering, applied mathematics, and programming.

Dr Evgenii Nekhoroshev has always been passionate about formalisation and automation of big research tasks. He started working on developing an automated solver for thermodynamic optimisation during his PhD thesis which was improved and finalised using the ideas of Prof. Evgueni Jak about real-time derivative matrix optimization and sensitivity analysis applicable to large multicomponent systems. His contribution to the Centre allowed to make transition to a continuous optimization approach when experimental and modelling streams of work in the Centre are efficiently combined together. It allows to include the most recent experimental datasets into a self-consistent database update with minimal time delays.

I am an applied and computational topologist; my research is motivated and inspired by real life problems. My main focus is on understanding how shape influences behaviour, which is a common theme arising in the study of many natural systems. I have done my bachelor and master in Pisa (Italy), and my PhD and first postdoc in Oxford (UK). I then moved to Melbourne for my second postdoc, before starting my position at UQ.

Gloria is a Lecturer in Chemical Engineering and an Advance Queensland Industry Research Fellow at UQ’s School of Chemical Engineering. She applies multiscale simulation techniques, combining molecular simulations with macroscopic physics-based modelling, to address energy and environmental challenges. Working at the interface of applied mathematics and engineering, she develops predictive models to understand complex system behaviour and computational methods to enhance simulation tools across chemical engineering applications.

Her expertise spans membrane science, nanocomposites, transport phenomena, and chemical kinetics, with a focus on adsorption, diffusion, and permeation in nanocomposites, as well as reaction engineering of complex chemical systems. She integrates Bayesian statistics, physical modelling, computational chemistry, and experimental validation to optimize carbon capture technologies for climate change mitigation and advance the development of sustainable chemical processes.

I am an Associate Professor in the School of Languages and Cultures at UQ (since 2017), having formerly been an assistant professor at the Centre for Applied English Studies (CAES), University of Hong Kong (since 2014). I hold an MA TESOL from the University of London and an M.Phil/Ph.D in applied linguistics from the University of Cambridge.

My areas of research and supervisory expertise include corpus linguistics and the use of corpora for language learning (known as 'data-driven learning'), as well as English for General and Specific Academic Purposes. I have published 60+ papers in leading journals including Language Learning, Corpus Linguistics and Linguistic Theory, Studies in Second Language Acquisition, Journal of English for Academic Purposes, English for Specific Purposes, and Computer-Assisted Language Learning, ReCALL, System, Journal of Second Language Writing, IRAL and the International Journal of Learner Corpus Research. I have featured in Stanford's Top 2% Scientists lists for 2023 and 2024.

I am currently Editor in Chief of the Australian Review of Applied Linguistics, have served as Associate Editor for the Q1 Journal of English for Academic Purposes, sit on the editorial boards of JSLW, IRAL, System, Applied Corpus Linguistics, Research Syntheses in Applied Linguistics, Research Methods in Applied Linguistics, and the book series Studies in Corpus Linguistics.

I bring industry and academic experience in working on quantum error mitigation, quantum error correction, and quantum control theory to enable quantum computing demonstrations on hardware. I am currently investigating the feasibility of combining error mitigation and error correction techniques with quantum algorithms at the University of Queensland. My team's recent focus spans quantum kernel methods, quantum Hamiltonian simulations for chemistry and optimization, and analysis of quantum channels and their impact on quantum learning. While my group is a theoretical physics research group, we focus on hardware-aware algorithms design and have close partnerships with superconducting qubit experimental platforms at UQ and IBM, with supporting classical computational compute capability at Pawsey Sentonix through NCMAS. I co-lead the quantum computing workstream with Prof. Sally Shrapnel for the Queensland Digital Health Center; I work closely with Prof. Eleanor Rieffel quantum algorithms aligned with the work of the newly established Queensland Decarbonization Alliance and I lead the Asia Pacific Hub of IBM Quantum's Industry Working Group for Healthcare and Lifesciences. Prior to this, I worked on execution of dynamic circuits for error mitigation and quantum error correction applications at IBM Quantum (US) for three years. My work resulted in 3 patents and being recognised as one of IBM Research’s Top Technical Contributors in 2023 globally. I have also designed classical algorithms for noise filtering and prediction for trapped ions at the Quantum Control Laboratory in the University of Sydney, winning ARC EQUS inaugural Director’s Medal in Australia in 2019. QDA is hiring a postdoc position in Quantum Algorithms (https://lnkd.in/e9jZQUEt) and funning two Ph.D positions: Robust Quantum Algorithms for Decarbonisation Applications (https://lnkd.in/gQ3S6bjY) & Distributed Quantum-Enhanced Algorithms (https://lnkd.in/gV7z4EQj)

Damon Thomas is a senior lecturer in literacy education. His current research interests include theories of writing, writing development, pedagogy, and assessment, systemic functional linguistics, argumentation, standardised assessment, and classical rhetoric. Damon's research has made important contributions in the following areas:

• Understanding the complexities of student writing development
• Exploring writing instruction in situ
• Unpacking and critiquing the results of Australia's only large-scale test: the National Assessment Program - Literacy and Numeracy.

Damon completed his PhD at the University of Tasmania (UTAS) in 2015. He began lecturing at UTAS in 2014 and was promoted to senior lecturer in 2019. He took up a senior lecturer position at the University of Queensland (UQ) in 2021. Before starting his academic career, Damon taught as a primary school teacher in Tasmania after completing a Bachelor of Education degree with First Class Honours.

Damon was part of a team of Chief Investigators from the University of Tasmania, Deakin University, and La Trobe University that secured a successful ARC Linkage Project in 2015 in partnership with Anglicare Tasmania (LP150100558). The project investigated conditions that improved learning and wellbeing outcomes in regional, low-SES schools in Tasmania and Victoria. Damon oversaw the literacy component across school sites and conducted in-depth case studies in Tasmanian primary and high schools.

Damon is currently a Chief Investigator on an ARC Discovery Project investigating talk for learning in early years mathematics classrooms. Damon's main role is to employ several linguistic frameworks to understand the complexities of student dialogue and features of productive talk.

Damon is a member of several professional organisations including the Australian Systemic Functional Linguistics Association (ASFLA), the Primary English Teaching Association of Australia (PETAA), and the Australian Literacy Educators' Association (ALEA). Damon also translates literacy research for practising teachers via his blog: Read Write Think Learn

Dr Peter Baker is an Honorary Associate Professor at the Queensland Alliance for Agriculture and Food Innovation

From 2021-2023, Peter was an Honorary Senior Lecturer at the School of Public Health, University of Queensland. For twelve years until the end of 2020, he was a Senior Lecturer in Biostatistics at the School of Public Health and a senior statistical collaborator, advisor and consultant to several research projects in the Faculty of Medicine, School of Public Health.

With fourty years experience as a statistical consultant and researcher, Peter has a passion for biometrics in agricultural research and biostatistics applied to public health and medical research. He also champions reproducible research and reporting and to this end has developed R and Make software to aid the workflow of data analysts in any field. As a statistical consultant and collaborator, he has contributed to many agricultural, genetic, public health and medical research projects. His contribution has ranged from advice on standard statistical approaches to the application of novel methods to improve statistical analysis or the development of new statistical methodology to fill a gap in the knowledge.

Peter's current research interests:

• efficient statistical computing using R, Make, Git and related software for the workflow of data analysis,
• reproducible research and reporting using R, Markdown, Quarto and Sweave,
• tailoring R functions and developing bespoke packages for specific statistical analyses, and
• applied statistlcal research in novel methods for epidemiological and medial research, including
  • graphical models for multivariate data in epidemiology,
  • statistical methods for modelling trajectories of alcohol consumption in youths,
  • propensity score analysis to adjust for selection bias in observational studies, and
  • Bayesian methods for epidemiological and medical MCMC studies.

Dr Baker is an Accredited Statistician (ASTAT) with the Statistical Society of Australia (see SSAI_Accreditation)

Chris O’Donnell obtained his PhD from the University of Sydney. He is an Associate Editor of the Journal of Productivity Analysis, an Associate Editor of Empirical Economics, and a Distinguished Fellow of the Australian Agricultural and Resource Economics Society. His current research is focused on economic and statistical methods for measuring and explaining productivity and efficiency change. He has authored or co-authored three books on this topic. His work has been published in leading economics and econometrics journals, including the American Journal of Agricultural Economics, the Journal of Econometrics, the Journal of Applied Econometrics, Econometric Reviews and the European Journal of Operational Research. He has provided in-house training and/or been a consultant for organisations including the World Bank, the Asian Productivity Organisation, the International Rice Research Institute, the Australian Energy Regulator, the New South Wales Independent Pricing and Regulatory Tribunal, and the Australian Independent Hospital Pricing Authority.