I studied Technical Mathematics at the Vienna University of Technology. I also earned a Master's degree in Law and I finished the first ("non-clinical") part of Medical Studies at the University of Vienna. I earned my PhD in Applied Mathematics at the University of Vienna in 2007. My PhD advisor was Christian Schmeiser, my co-advisor was Peter Markowich. I spent several months at the University of Buenos Aires working with C. Lederman and at the ENS-Paris rue d'Ulm in the group of B. Perthame.
Before coming to UQ, I held post-doc positions at the Wolfgang Pauli Insitute (Vienna), University of Vienna and the Austrian Academy of Sciences (RICAM). In 2013 I won an Erwin Schrödinger Fellowship of the Austrian Science Fund (FWF). I was a post-doc researcher in the group of Alex Mogilner first at UC Davis, then at the Courant Institute of Math. Sciences (New York University).
I am a Senior Lecturer in Mathematical Data Science, at School of Mathematics and Physics, The University of Queensland. I obtained my BSc degree in Mathematics and Applied Mathematics, from Beijing Normal University in 2006. I obtained my MPhil and PhD degrees from City University of Hong Kong in 2008 and 2011 respectively, where I was working as a research fellow from Oct 2011 to Feb 2013. During Feb 2013 -- Aug 2014, I was working as a postdoctoral associate at Department of Statistical Science, Duke University. Before joining UQ in Jan 2022, I worked at Hong Kong Polytechnic University. My research interests cover statistical learning theory (kernel methods, stochastic gradient methods, support vector machine, pairwise learning, online learning, error analysis, sparsity analysis, and the implementation of algorithms), mathematical data science, and their applications to artificial intelligence, immunological bioinformatics, systems biology, and computational social science.
Emeritus Professor Phil Pollett has research interests in Markov process theory, and mathematical modelling in population biology, ecology, epidemiology, chemical kinetics and telecommunications.
He holds an honours degree in Applied Mathematics from the University of Adelaide and a PhD degree in Applied Probability from the University of Cambridge. He joined the then Department of Mathematics in 1987 as Senior Lecturer, having previously held positions at the University of Adelaide, Murdoch University and University College of Cardiff. He was promoted to Reader in 1993 and to Professor in 2004.
His research is recognized internationally for significant contributions to Markov process theory, and mathematical modelling. This research has been supported by 12 ARC Large/Discovery/Linkage grants. He is a Chief Investigator within the ARC Centre of Excellence for Mathematical and Statistics Frontiers (ACEMS), and was a Chief Investigator (2002-2014) within the ARC Centre of Excellence for Mathematics and Statistics of Complex Systems (MASCOS). In 1993, he was awarded the Moran Medal by the Australian Academy of Science for distinguished research in Applied Probability.
Phil Pollett has served on the editorial boards of the Journal of the Australian Mathematical Society, Methodology and Computing in Applied Probability, Stochastic Models, and The Annals of Applied Probability, and has served on the organizing committees of several major international conferences. He devised the Probability Web, recognized as the main Web resource for probabilists throughout the world, and one of the first academic web sites. He has a strong record of innovation in undergraduate teaching, and has guided the development of many postgraduate students and postdoctoral fellows through supervision and collaboration.
My research focus encompasses a broad range of methods – Bayesian Inference, statistical models, compartmental models, stochastic models, social network analysis, forecasting methods- and a broad interest in emerging pathogens –tuberculosis, influenza and hospital associated pathogens and emerging infectious diseases including SARS, Ebola and COVID-19. I have led research teams to complete international consultancies, modeling of tuberculosis control in our region, and international research collaborations in the area of tuberculosis, healthcare associated infections SARS and Ebola and COVID-19.
I have diverse cross-disciplinary skills, as an infectious diseases physician (FRACP) and mathematical modeler (PhD -QUT), epidemiologist, and biostatistician (MBios Uni Melb). Since 2003, I have worked on interleaving clinical research with mathematical modeling and simulation of infectious diseases transmission. In this time, I have developed the ability to communicate and collaborate across the disciplines of mathematics, biostatistics, epidemiology, public health and clinical infectious diseases. I lead a team of highly skilled mathematicians and biostatisticians, epidemiologists.
I am currently the Professor of Infectious Diseases Epidemiology at the University of Queensland Centre for Clinical Research, working with the ODeSI program. I continue clinical work as a physician for the TB control unit at the Torres Strait and Cape York Health Service. My collaborators across Australia include as a chief investigator on two Centres for Research Excellence in forecasting and in tuberculosis. I work with researchers in major national (Monash University, Australian National University, Curtin University and the Doherty Institute, UWA, UQ) and international universities (Imperial College, LSHTM, Harvard, Stanford, Oxford, Mahidol).
COVID-19 work to date includes providing modelling and advice for: the commonwealth Government, Victorian State Government, OzSage Indigenous working group, and leading the AUS-CMI Australian Covid-19 modelling initiative group, the Global Fund against Malaria TB and AIDS, and the World Health Organization in conjunction with countries in the Asia Pacific Regions.
My major methodlogical areas of research in active development are (1) forecasting (2) scenario analysis for decision support (3) disease dynamic insights through data analysis including Bayesian inference and machine learning.
Veronika Kuchta received her Diploma degree in Mathematics at the Heidelberg University in Germany in 2010. She reseived her PhD in applied cryptography at the University of Surrey, United Kingdom in 2016. She worked as a postdoc at the Universite libre de Bruxelles in Belgium from 2016-2018. From 2018 till 2020 she has been a Research Fellow at Monash University in Melbourne, Australia. FromDecember 2020 to July 2022 she was employed by The University of Queensland, School of Mathematics and Physics as a lecturer in mathematical cryptography. From November 2022 she is Assistant Professor at Florida Atlantic University (Boca Raton, USA), department of mathematical sciences. Her research interst focus on the different areas of mathematical cryptography, post-quantum cryptography and its applications to the real-world.
Kazutoshi Yamazaki is a senior lecturer at the School of Mathematics and Physics, the University of Queensland. Before joining UQ in April 2022, he was an assistant professor at Osaka University and an associate professor at Kansai University. He is an applied probabilist with contributions in the field of insurance and financial mathematics and operations research. He has organised various conferences including the Probability Theory and Stochastic Processes session at the 65th AustMS 2021 annual meeting. He is also one of the organisers of Mathematics of Risk 2022, a MATRIX event to be held in December 2022. Kazutoshi obtained his PhD in Operations Research and Financial Engineering from Princeton University in 2009.
I am a teaching focussed academic in the School of Mathematics and Physics. I have a PhD in applied statistics and love mathematical programming in R, python and Matlab.
I am particularly interested in understanding the ways in which first year university students seek help outside of their shceduled classes and the role that university first year learning centres can play in helping students succeed.
Adrian grew up in Perth and double majored in Pure Mathematics and Applied Mathematics at the University of Western Australia. Soonafter, he ventured to Canberra to undertake a PhD, focussing on analytic number theory: an enchanting area where one perplexingly uses calculus and analysis to study discrete structures such as the set of prime numbers.
After this, he worked as a derivatives trader at Optiver APAC for five years and stayed on there as Head of Academic Partnerships. He currently straddles both industry and academia and believes they both have much to offer mathematicians.
Adrian is available (and invariably keen) to supervise honours, masters and PhD projects in analytic number theory.
Jerzy Filar is Emeritus Professor of Applied Mathematics. Jerzy is a broadly trained applied mathematician with research interests spanning a spectrum of both theoretical and applied topics in Operations Research, Stochastic Modelling, Optimisation, Game Theory and Environmental Modelling. Professor Filar co-authored, or authored, five books or monographs and approximately 100 refereed research papers. He has a record of research grants/contracts with agencies and research institutes such as NSF, ARC, US EPA, World Resources Institute, DSTO, FRDC and the Sir Keith and Sir Ross Smith Foundation. He is editor-in-chief of Springer’s Environmental Modelling and Assessment and served on editorial boards of several other journals. He has supervised or co-supervised 29 PhD students. Jerzy's Erdos Number is 3.
Professor Joseph Grotowski completed his Bachelor of Science with Honours in Mathematics at the Australian National University in 1985. He then moved to New York for postgraduate studies in Mathematics, and completed an MS in 1987 and a PhD in 1990 at the Courant Institute, NYU.
He held a number of positions in Germany, and completed his Habilitation at the Friedrich-Alexander Universitaet Erlangen-Nuernberg in 2001. He took up a position as an Associate Professor at the City College of New York of the City University of New York in 2003, and returned to Australia to take up a position as a Senior Lecturer at UQ in 2005. He was promoted to Associate Professor from 2010, and Full Professor from 2013.
His main research area is geometric and nonlinear partial differential equations.
He served as Head of the Mathematics Discipline from 1 January 2010 until 30 April 2014. From 1 May 2014 he has been Head of the School of Mathematics and Physics. As Head of School, he is responsible for ensuring that the School delivers a high standard of research and teaching, as well as engagement with the broader community, across our disciplines of mathematics, physics and statistics. He is also responsible for providing and fostering strategic leadership within the School, as well as for financial management of the School’s budget and management of the School’s resources.
He is a former Board Member of the Australian Mathematical Sciences Institute, and serves on the advisory Board of the MATRIX Research Insitute. He has been active in CSIRO Mathematicians in Schools for a number of years.
I am a Senior Lecturer in Logic in the School of Historical and Philosophical Inquiry at the University of Queensland, Australia. From 2022-2025, my work was supported by the Discovery Early Career Researcher Award DE220100544 (383,975 AUD in funds) given by the Australian Research Council. I serve on the editorial boards of Archive for Mathematical Logic and Journal of Multiple-Valued Logic and Soft Computing. According to the Mathematics Genealogy Project, I am one of the many academic descendants of G. H. Hardy through the path G. H. Hardy - R. Rado - K. Gravett - John N. Crossley - John L. Bell - G. Priest - Z. Weber - me. Jointly with John Crossley and John Stillwell, I have written a book entitled What is Mathematical Logic? (2ed.) to be published by Oxford University Press.
Director of Research of School of Mathematics and Physics
School of Mathematics and Physics
Faculty of Science
Availability:
Available for supervision
Cecilia is an associate professor in the School of Mathematics and Physics at the University of Queensland. After completing undergraduate studies at Universidad de Guanajuato / CIMAT and PhD at the University of Maryland, College Park, she held research fellowships from the Pacific Institute for the Mathematical Sciences (PIMS) and the Australian Research Council (ARC). She has also held a Promoting Women Fellowship by UQ.
Cecilia is an expert in the field of random dynamical systems (RDS). Along with collaborators, she has developed a framework for the study of transport in RDS, relying on the so-called Lyapunov–Oseledets spectrum. Her key contributions include the development of tools and algorithms to (i) approximate coherent structures and Lyapunov exponents, (ii) establish limit laws and quantify fluctuations, (iii) develop a thermodynamic formalism and (iv) optimise mixing. Her work also includes significant advances on data assimilation, metastable and dynamical systems.
Cecilia has received significant research funding from the Australian Research Council, including a 2016 Discovery Early Career Researcher Award (DECRA) a 2018 ARC DP and a 2022 ARC DP as lead CI. She has led or co-led competitive applications for conference funding (20-60 participants), including a 2023 MATRIX Workshop, co-funded by the MATRIX-Simons Collaborative Fund, an Australian Mathematical Sciences Institute (AMSI) funded Mathsfest Workshop (ANU, 2016), a Banff International Research Station Workshop (Canada, 2015) and a BIRS-CMO Workshop (Mexico, 2018).
Cecilia has delivered over a hundred invited lectures, seminars and colloquia in almost twenty countries, including invited/keynote addresses at the ANZIAM 2023 annual conference, 2014 International Workshop Set Oriented Numerics (U Canterbury, NZ), 2017 Workshop Ergodic Theory, Algorithms & Rigorous Computations (U Warwick, UK), 2017 EMALCA (Latin-American & Caribbean Math School, Mexico) and participation at invitation-only workshops at AIM (USA), BIRS (Canada), Bernoulli Center (Switzerland), CMO (Mexico), CIRM (France), Centro De Giorgi (Italy), Lorentz Center (Netherlands) and MATRIX (Australia).
Cecilia's service roles include: MATRIX Scientific Committee (2019-), Australian Mathematical Society council (2018-2021) and Queensland representative at the ANZIAM Executive Committee (2019-2021).
Key research areas: Intellectual and developmental disability; Inclusive mathematics education; Down syndrome; Mathematics learning difficulties; Quality of life.
Dr Rhonda Faragher AO is a Professor in Inclusive Education. She has internationally recognised expertise in the mathematics education of learners with Down syndrome. In her research and teaching, she works to improve the educational outcomes of students who have difficulties learning mathematics, for whatever reason, including through educational disadvantage. Beyond mathematics education, she has expertise in inclusive education in a range of contexts, including secondary classrooms.
Dr Faragher is the Director of the Down Syndrome Research Program within the School of Education. She is an appointed Board member to the Academy on Education, Teaching and Research of IASSIDD - the International Association for the Scientific Study of Intellectual and Developmental Disability, Chair of the Down syndrome Special Interest Research Group of IASSIDD, Vice-President of Down Syndrome International and an Independent Director of Down Syndrome Australia. She is Co-Editor in Chief of the Journal of Policy and Practice in Intellectual Disabilities.
Dr Faragher is a Senior Fellow of the Higher Education Academy, a Fellow of IASSIDD and has received a number of awards for her work including the 2020 UQ Award for Excellence in Community, Diversity and Inclusion, the 2016 ACU Vice-Chancellor's Medal for Staff Excellence, a Commonwealth of Australia Endeavour Executive Award and the 2011 Mathematics Education Research Group of Australasia Research Award. In 2023, she was appointed an Officer of the Order of Australia.
Recent books / chapters
Faragher, R. (2023). A practical guide to educating learners with Down syndrome. Supporting lifelong learning. Routledge.
Faragher, R. M. (2023). Individual student characteristics, abilities and personal qualities and the teacher’s role in improving mathematics learning outcomes. In A. Manizade, N. Buchholtz, & K. Beswick (Eds.), The evolution of research on teaching mathematics. International perspectives in the digital era. (pp. 227-253). Springer Nature. https://doi.org/https://link.springer.com/book/10.1007/978-3-031-31193-2
Faragher, R., Robertson, P., & Bird, G. (2020). International guidelines for the education of learners with Down syndrome. DSi.
Siemon, D., Warren, E., Beswick, K., Faragher, R., Miller, J., Horne, M., Jazby, D., & Breed, M. (2020). Teaching mathematics: foundations to middle years. 3rd ed. Oxford University Press.
Brown, R. I., & Faragher, R. (Eds.). (2018). Quality of life and intellectual disability. Knowledge application to other social and educational challenges. (Revised ed.). Nova.
Recent articles
Faragher, R., & Lloyd, J. (Early View). Continuing conceptualising QOL through application to the lives of young adults with Down syndrome. Journal of Policy and Practice in Intellectual Disabilities. https://doi.org/10.1111/jppi.12479
Vassos, M., Faragher, R., Nankervis, K., Breedt, R., Boyle, F., Smith, S., & Kelly, J. (2023). The ethical, legal, and social implications of genomics and disability: Findings from a scoping review and their humanrights implications. Advances in Neurodevelopmental Disorders. https://doi.org/10.1007/s41252-023-00362-1
Yanes, T., Vaishnavi, N., Wallingford, C., Faragher, R., Nankervis, K., Jacobs, C., Vassos, M., Boyle, F., Carroll, A., Smith, S., & McInerney-Leo, A. (2023). Australasian genetic counselors’ attitudes toward disability and prenatal testing: Findings from a cross-sectional survey. Journal of Genetic Counseling, 1-12. https://doi.org/http://doi.org/10.1002/jgc4.1788
Wanjagua, R., Hepburn, S., Faragher, R., John, S. T., Gayathri, K., Gitonga, M., Meshy, C. F., Miranda, L., & Sindano, D. (2022). Key learnings from COVID‐19 to sustain quality of life for families of individuals with IDD. Journal of Policy and Practice in Intellectual Disabilities, 19(1), 72–85. https://doi.org/10.1111/jppi.12415
Faragher, R., Chen, M., Miranda, L., Poon, K., Rumiati, Chang, F., & Chen, H. (2021). Inclusive Education in Asia: Insights From Some Country Case Studies. Journal of Policy and Practice in Intellectual Disabilities, 18(1), 23–35. https://doi.org/10.1111/jppi.12369
Faragher, R.M. & Clarke, B. A. (2020). Inclusive practices in the teaching of mathematics : some findings from research including children with Down syndrome. Mathematics Education Research Journal, 32(1), 121–146. https://doi.org/10.1007/s13394-019-00294-x
Faragher, R,M. (2019). The New 'Functional Mathematics' for Learners with Down Syndrome : Numeracy for a Digital World. International Journal of Disability, Development, and Education, 66(2), 206–217. https://doi.org/10.1080/1034912X.2019.1571172
Dirk Kroese's research interests are in: Monte Carlo methods, rare-event simulation, the cross-entropy method, applied probability, and randomised optimisation.
Dirk Kroese is a professor of Mathematics and Statistics at the School of Mathematics and Physics of the University of Queensland. He has held teaching and research positions at The University of Texas at Austin, Princeton University, the University of Twente, the University of Melbourne, and the University of Adelaide. His research interests include Monte Carlo methods, adaptive importance sampling, randomized optimization, and rare-event simulation. He has over 120 peer-reviewed publications, including six monographs:
Rubinstein, R.Y., Kroese, D.P. (2004). The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning, Springer, New York.
Rubinstein, R. Y. , Kroese, D. P. (2007). Simulation and the Monte Carlo Method, 2nd edition, John Wiley & Sons.
Kroese, D.P., Taimre, T., and Botev, Z.I. (2011). Handbook of Monte Carlo Methods, Wiley Series in Probability and Statistics, John Wiley & Sons, New York.
Kroese, D.P. and Chan, J.C.C. (2014). Statistical Modeling and Computation, Springer, New York.
Rubinstein, R. Y. , Kroese, D. P. (2017). Simulation and the Monte Carlo Method, 3rd edition, John Wiley & Sons.
Kroese, D.P., Botev, Z.I., Taimre, T and Vaisman, R. (2019) Data Science and Machine Learning: Mathematical and Statistical Methods, Chapman & Hill/CRC.
Kroese, D.P. and Botev, Z.I. (2023). An Advanced Course in Probability and Stochastic Processes, Chapman & Hill/CRC.
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 am a research fellow in the School of Mathematics and Physics at the University of Queensland, Australia, where I work with Professor Geoffrey J. McLachlan on semi-supervised learning, specifically investigating missingness mechanisms and mixture modelling. I earned my PhD in 2022 from the Queensland University of Technology (QUT), under the joint supervision of biostatistician Professor You-Gan Wang, applied mathematician Professor Kevin Burrage, and computer scientist Professor Yu-Chu Tian.
Following my doctoral studies, I was appointed as an Associate Lecturer at QUT, where I coordinated the course Longitudinal Data Modelling. I later joined the Australian Catholic University as a Research Fellow, collaborating with Professor Herbert Marsh on large-scale social data modelling.
My research focuses on machine learning and statistical modelling, with a particular emphasis on robust statistical methods and predictive analytics. I have published more than 80 peer-reviewed papers in leading journals such as Pattern Recognition and several IEEE Transactions journals. My work has been cited over 1,450 times, and my current h-index is 21 (Google Scholar).
I serve as an Academic Editor for PLOS ONE and have guest-edited special issues for journals such as Safety Science and Environmental Modelling & Assessment. As a peer reviewer, I have contributed to over 50 prestigious journals, including The New England Journal of Medicine and IEEE Transactions on Pattern Analysis and Machine Intelligence, and I have also acted as a grant referee for the German Academic Exchange Service.
I have served on program committees for major conferences such as the International Conference on Artificial Intelligence in Education and the Australasian Data Science and Machine Learning Conference. I maintain active international collaborations with researchers from institutions including the University of Oxford, the University of Munich, Michigan State University, and Xi’an Jiaotong University.
In 2021, I was honored with the Chinese Government Award for Outstanding Self-Financed Students Abroad, recognizing me as one of the top 500 overseas Chinese scholars globally.
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;
Affiliate of Centre for Biodiversity and Conservation Science
Centre for Biodiversity and Conservation Science
Faculty of Science
Senior Lecturer
Mathematics
Faculty of Science
Availability:
Available for supervision
Media expert
Dr. Matthew Holden is an applied mathematician using modelling to improve environmental outcomes. Mathematical tools unify his research across several diverse topics in biodiversity conservation, theoretical ecology, fisheries, and other branches of natural resource management. He is especially interested in how we improve the well-being of human populations at least cost to biodiversity.
Dr. Holden currently serves as the Vice President of the Resource Modeling Association, an international society of economists, mathematicians, and envrionmental scientists unified via their passion for modelling and other quantitative methods to solve the world's hardest natural resource management problems. He also is the Deputy Director of Research for the Centre for Biodiversity and Conservation Science (CBCS), and is also affiliated with the Centre for Marine Science (CMS).
Dr. Holden was awarded his Ph.D. in Applied Mathematics at Cornell University, where he used dynamical systems, optimal control, and statistical theory to recommend policies to improve the management of invasive species, agricultural pests, and fisheries. He received his bachelor’s degree from the University of California, Davis, where he won the University Medal, working on the effect of habitat fragmentation on the persistence of endangered species.
