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• Statistical Consulting Network Monthly Meet-Up

  • Start
    25 Feb 2026
  •  
  • End
    23 Jun 2027
  •  
  • Schedule
    15 sessions
  • Location
    Online via Zoom

  Come along with your thinking cap, maybe a problem, and some lunch!

  The Statistical Consulting Network invites you to their monthly online meet-up, a virtual lunchtime meeting where statisticians help each other out with problems that they aren’t sure how to deal with.

  This virtual meeting is held on Zoom at lunchtime on the last Wednesday of each month, 12:00 pm - 1:00 pm (AEDT). They start each meet-up with announcements, or occasionally a special topic discussion, then discuss problems that attendees have brought along with them.

  Zoom link

  Password: 543284

  Calendar invite: ​​Stats Consulting Network meeting.ics

  2026 Dates

  • Wednesday 25 February
  • Wednesday 25 March
  • Wednesday 29 April
  • Wednesday 27 May
  • Wednesday 24 June
  • Wednesday 29 July
  • Wednesday 26 August
  • Wednesday 30 September
  • Wednesday 28 October
  • Wednesday 25 November

  12:00 pm – 1:00 pm AEDT Feb, March, Oct, Nov
  12:00 pm – 1:00 pm AEST April, May, June, July, August, September

  2027 Dates

  • Wednesday 24 February
  • Wednesday 24 March
  • Wednesday 28 April
  • Wednesday 26 May
  • Wednesday 23 June

  
  The Statistical Consulting Network also has a Slack workspace where members of the consulting network can communicate between meetings, or post problems or relevant materials they would like to discuss during a meeting.​​

  Slack Workspace link  

  Show details
• Data Science SIG Monthly Catch Up

  • Start
    11 Jun 2026
  •  
  • End
    10 Jun 2027
  •  
  • Schedule
    11 sessions
  • Location
    Online via Zoom

  The Data Science SIG's monthly catch up is a place to share any ideas, challenges, cool tech, or anything else data science-related.

  Each month we'll come with something new to discuss, but anyone is welcome to lead the discussion. Just let the DSSIG committee know!

  The monthly meeting catch ups will be held via Zoom on the 2nd Thursday of each month, 2:00 pm - 3:00 pm (AEDT).

  Zoom link

  2026 Dates

  • Thursday 11 June
  • Thursday 9 July 
  • Thursday 13 August 
  • Thursday 10 September 
  • Thursday 8 October 
  • Thursday 12 November

  2:00 pm - 3:00 pm AEDT Feb, March, Oct, Nov
  2:00 pm - 3:00 pm AEST April, May, June, July, August, September

  2027 Dates

  • Thursday 11 February
  • Thursday 11 March
  • Thursday 8 April
  • Thursday 13 May
  • Thursday 10 June

  
  

  Show details
• Data Science SIG Monthly Show and Tell

  • Start
    26 Oct 2026
  •  
  • End
    24 May 2027
  •  
  • Schedule
    6 sessions
  • Location
    Online via Zoom

  Join the SSA Data Science SIG for a Monthly Show and Tell. Each month we'll have a speaker talk us through a problem, project, or passion of theirs. These will be opportunities to learn and discuss data science and related skills, find out what people are getting up to.

  Title: Data Science Show and Tell

  Date: 4th Monday of each month

  Time: 12:30 pm - 1:30 pm AEDT

  Format: Online via Zoom

  If you have something to contribute to the monthly show and tell, get in touch with the DSSIG committee. If you're looking for general data science chat, come along to our monthly catch ups on the second Thursday of each month.

  Zoom link

  Upcoming Dates

  • 26 October 2026 - "Deep learning or Just Deep Thinking: When hand-crafted features beat neural networks, and when they don't", Stuart Szwec
  • 23 November 2026 - "What's in a name? Variable names, conventions, and how to do them well", Ben Harrap
  • 22 February 2027 - TBC
  • 22 March 2027 - TBC

  
  

  Show details
• SSA NSW Branch workshop: Julia for Statistics

  • When
    6 Nov 2026
  •  
    9:00 AM - 1:00 PM
  • Location
    UNSW Sydney
  • Spaces left
    27

  Register

  The New South Wales Branch of the Statistical Society of Australia invites you to a workshop on "Julia for Statistics" delivered by Mattias Villani, Stockholm University.

  Date: Friday 6 November 2026

  Times: 9:00 am - 1:00 pm AEDT

  Venue: UNSW Sydney (exact details TBC)

  Format: In person

  Abstract: Julia for Statistics

  Julia has emerged as an important language for statistical data analysis and machine learning. It is a high-level language that is easy to learn, but with a speed close to C/C++ from its just-in-time compilation. Despite its relatively young age, Julia already has an impressive set of libraries for statistics, and can be easily integrated with a workflow in R or Python. It is an excellent language for speeding up your statistical computations, and works well with AI coding.

  This half-day tutorial/workshop introduces the Julia programming language with a focus on statistical analysis, including likelihood and Bayesian inference using the Turing.jl probabilistic programming ecosystem in Julia. The tutorial/workshop will present different aspects of Julia and demo some code where participants can follow along on their own computers. Time will however not allow for much own work/exercises, so be prepared to experiment by yourself after the workshop.

  Key Learnings

  The following topics will be covered/introduced:

  • introduction to the Julia programming language and a bit of tooling
  • the package manager
  • managing data and plotting in Julia
  • statistical distributions
  • numerical optimization and automatic differentiation
  • working with R and Python in Julia
  • probabilistic programming with Turing.jl

  Prerequisites:

  • previous experience with at least basic programming in some language.
  • some statistical knowledge, including maximum likelihood estimation and Bayesian inference.

  Before the workshop:

  Participants are encouraged to install Julia and some statistical packages beforehand, to follow along on their own laptops. Installation instructions are available at the workshop web page: https://mattiasvillani.com/Julia4Stats 

  Presenter Bio: Mattias Villani

  
  

  Mattias Villani is Professor and chair of Statistics at Stockholm University, where he earned his PhD in Statistics in 2000 with a thesis on Bayesian cointegration under Daniel Thorburn. He was a senior lecturer at Stockholm University from 2003 to 2011 and, concurrently, a researcher and advisor at the Swedish central bank from 2004 to 2011, where he helped develop its two main models for macroeconomic forecasting and policy analysis. From 2011 to 2023 he was Professor of Statistics at Linköping University, where he built up the Statistics and Machine Learning division and broadened his applied work into neuroimaging, robotics and transportation, before returning to his alma mater in 2018. His research develops computationally efficient Bayesian methods for inference, prediction and decision making using flexible probabilistic models. He serves as associate editor for Bayesian Analysis and the CSDA Annals of Statistical Data Science, and is a keen programmer with a particular fondness for Julia.

  Cancellation Policy:

  Occasionally events have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.

  Cancellations received prior to two weeks before the event will be refunded, minus the Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20.

  From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au. 

  Show details
• SSA NSW Branch seminar: Time-Varying Parameter Distributional Regression with Dynamic Global-Local Shrinkage Process Priors

  • When
    6 Nov 2026
  •  
    4:30 PM
  • Location
    Room 4082, School of Mathematics and Statistics, UNSW
  • Spaces left
    37

  Register

  The New South Wales Branch of the Statistical Society of Australia invites you to a seminar titled "Time-Varying Parameter Distributional Regression with Dynamic Global-Local Shrinkage Process Priors" delivered by Mattias Villani, Stockholm University.

  Date: Friday 6 November 2026

  Time: 

  4:00 pm Snacks and light refreshments

  4:30 pm Seminar

  5:30 pm Dinner/Drinks at a nearby location

  Venue: Room 4082, School of Mathematics and Statistics, UNSW Sydney, Kensington NSW 2052

  Format: In person

  Abstract: Time-Varying Parameter Distributional Regression with Dynamic Global-Local Shrinkage Process Priors

  We consider regression models for exponential family distributions in which all distributional parameters are linked to covariates with time-varying regression coefficients. The coefficients follow dynamic global-local shrinkage process priors, which allow them to stay constant in some periods while moving rapidly or jumping in others. We develop a Gibbs sampling algorithm with three alternative updating steps for the coefficient trajectories. The samplers are based on Gaussian approximations and therefore target a perturbed posterior. Several strategies are proposed to improve sampling speed, robustness and accuracy. The degree of posterior perturbation is assessed by comparing with exact posterior inference from particle Gibbs with ancestor sampling. The coefficient innovations are defined so that they adapt automatically to the model geometry, the link functions, and the scale and covariance of the covariates. The approach is illustrated with a time-varying seasonal Poisson regression for UK bike rental demand and a Beta regression for US layoff proportions, with time-varying effects on both the mean and the precision. The algorithms will be made available in an open-source Julia package.

  Presenter Bio: Mattias Villani, Stockholm University

  
  

  Mattias Villani is Professor of Statistics at Stockholm University. His PhD is from Stockholm University in 2000, on the topic of Bayesian reduced rank models. He continued there as a Postdoctoral Researcher and Senior Lecturer. During this time, he also worked at the Central Bank of Sweden, where he developed models and methods for macroeconomic forecasting and policy analysis. In 2011, Mattias became Professor of Statistics at Linköping University, where he continued to work on Bayesian statistical methodology and computing, with applications to machine learning, neuroimaging, robotics, and transportation. While there, he founded the Statistics and Machine Learning Division and contributed to the integration of the two fields of Statistics and Machine Learning. In 2018, Mattias returned to Stockholm University, where he holds the Professor Chair of Statistics. He has been an Associate Editor for Econometrics and Statistics, and he currently serves as Associate Editor for Bayesian Analysis and Annals of Statistical Data Science.

  Show details
• SSA WA Careers Panel on Statistical Consulting

  • When
    10 Nov 2026
  •  
    6:00 PM
  • Location
    Geographe Room, State Library of Western Australia
  • Spaces left
    23

  Register

  The Western Australian Branch of the Statistical Society of Australia invites you to join them as the four panellists share their experiences with statistical consulting in industry, government, and academic settings. The four panellists are Dr Ritu Gupta, Rebecca Herbst, Alex Stuckey, and Dr Robin van de Meeberg. Dr John Henstridge will moderate the evening, with questions fielded from the floor.

  Date: Tuesday 10 November 2026

  Time: 6:00 pm - 7:00 pm AWST

  Venue: Geographe Room, Ground Floor, State Library of Western Australia, Perth Cultural Centre, 25 Francis Street, Perth

  Format: In person

  This event is kindly sponsored by Data Analysis Australia (DAA).

  
  

  Presenter Bios:

  Dr Ritu Gupta

  
  

  Ritu is an academic statistician with over 25 years of teaching and consulting experience. She is an Associate Professor at Curtin University and previously worked at the Statistical Consulting Centre at the University of Western. Ritu has taught a broad range of theoretical and applied topics to diverse cohorts across Actuarial Science, Health, Science, and Engineering programs. She also serves as the Data Science Coordinator at Curtin University. She has completed over 30 consulting projects, providing practical solutions to challenging problems for industry, government and sporting clubs. She is an Accredited Statistician (AStat) with the Statistical Society of Australia.

  Rebecca Herbst

  
  

  Rebecca Herbst is a Senior Consultant Statistician at Data Analysis Australia. Rebecca holds a Master of Science (Applied Statistics) from Swinburne University of Technology and a Graduate Diploma in Epidemiology (Clinical) from The University of Queensland. She has previously worked as a medical research scientist where she developed an interest in statistics. Since completing post-graduate degrees in applied statistics and clinical epidemiology, she has worked as a consultant across a variety of areas including mine safety, transport, education, agriculture and financial services.

  Alex Stuckey

  
  

  Alex is a Principal Consultant Statistician and Managing Director at Data Analysis Australia. Alex is an Accredited Statistician with over 20 years of experience in applying a diverse range of design, analytical and computational methods to real world problems. His fields of expertise include sample survey design and analysis, time series analysis, forecasting, official statistics and automation to inform expert systems.

  Alex has formerly led teams within the Australian Bureau of Statistics responsible for supporting national economic and social statistics. Following his career in official statistics, Alex ran a statistical consulting firm supporting clients in government, industry and academia.

  Dr Robin van de Meeberg

  
  

  Robin is a biostatistician at The Kids Research Institute Australia, bringing across the analytical and computational skills developed as an extragalactic astrophysicist to the challenges of child health research. As a consultant statistician, he collaborates closely with clinicians, researchers and health services to design studies, manage and analyse complex datasets and turn research findings into evidence towards meaningfully improving child health outcomes. To this end, he has dedicated time and energy to developing software packages that streamline the production of scientific tables, figures and analytical workflows. Whether observing cosmic structures of the Universe or the intricacies of the human body, Robin has always been motivated by a common goal: using data to better understand the world and communicate scientific research in a meaningful and impactful way.

  Dr John Henstridge (Moderator)

  
  

  John Henstridge is the Chief Consultant Statistician at Data Analysis Australia and one of Australia’s most eminent Statisticians. In a career spanning 40 years, he has been recognised as a national leader in developing solutions to real world data problems, through modern technology and innovative statistics.

  John’s particular strength is in quickly understanding complex systems, envisioning the approach to a solution and providing strategic and actionable advice. John is highly experienced in delivering results across a plethora of industries including government, commercial and legal. John has held the position of National President with the Statistical Society of Australia and is a Fellow and Chartered Statistician with the Royal Statistical Society in the United Kingdom.

  Refreshments and Dinner

  Members, visitors, and guests are invited to mingle over light refreshments from 5:45 PM. Following the meeting, everyone is invited to dine with the panellists and fellow attendees at a nearby restaurant.

  Venue details

  This meeting is in the Geographe Room on the Ground Floor of the State Library of Western Australia. The library is in the Perth Cultural Centre just north of Perth Train Station. Google map

  
  

  The area has numerous parking options, including on-street parking and parking beneath the library at the CPP State Library, accessed from 15 Francis Street, Northbridge. An alternative car park is the CPP Cultural Centre, with an entrance at 2 Roe Street, Northbridge.

  
  

  Due to construction work as part of the Perth Cultural Centre Rejuvenation Project, we recommend entering via the Francis Street Entrance or taking the lift from the underground car park.

  From the Francis Street Entrance, walk a short distance into the library before turning right down the ground floor gallery away from the café.

  For further information please contact the WA Branch Secretary: wa.branch@statsoc.org.au

  Show details
• SSA ACT Branch workshop: Deep Learning and Computer Vision in R: A Practical Introduction

  • Start
    17 Nov 2026
  •  
    1:30 PM
  • End
    18 Nov 2026
  •  
    5:00 PM
  • Location
    Online via Zoom
  • Spaces left
    15

  Register

  The Australian Capital Territory Branch of the Statistical Society of Australia proudly presents a practical, hands-on workshop "Deep Learning and Computer Vision in R: A Practical Introduction", presented by Dr Patrick (Weihao) Li from the Australian National University (ANU).

  Date: Tuesday 17 November AND Wednesday 18 November 2026

  Time: 1:30 pm to 5:00 pm AEDT on both days

  Format: Online via Zoom. Details will be provided in your registration confirmation email.

  Registrations Close: Tuesday 10 November

  About the Workshop

  Deep learning has transformed how we extract insights from images, powering applications across diverse fields such as medical imaging, precision agriculture, autonomous systems, and industrial inspection. While these techniques are increasingly important in modern research, many applied statisticians are unfamiliar with the key concepts and tools behind deep learning and computer vision.

  Presenter's Bio - Dr Patrick (Weihao) Li, ANU

  
  

  Dr Patrick (Weihao) Li is a Postdoctoral Research Fellow at the Australian National University, working on the Analytics for the Australian Grains Industry (AAGI) project. He holds a PhD in Statistics from Monash University. His research spans machine learning, data visualization, statistical modelling, and computer vision, with a focus on developing computational methods for analysing and interpreting complex data. His current research applies these methods to agricultural, biological, and public health applications. Within the AAGI project, he investigates the interpretation, robustness, and uncertainty of Vision Transformer-based models for automated canola blackleg severity quantification, and contributes to the development of new computational frameworks for fitting complex linear mixed models. He has also contributed to computer vision projects in IVF embryo assessment and video-based food safety monitoring using object detection and vision-language models.

  Key Learnings:

  This hands-on workshop introduces the fundamentals of deep learning and its applications in computer vision, with a focus on accessibility for R users. We will begin with a high-level overview of deep learning and neural networks, building intuition for the key components of modern deep learning models, including layers, activation functions, model training, and optimisation. The workshop will then introduce core computer vision techniques, including convolutional neural networks (CNNs) for image analysis and more recent approaches such as Vision Transformers (ViTs), which have become increasingly important in modern computer vision applications. Through practical examples, participants will explore how deep learning models can be applied to tasks such as:

  • Image classification (e.g. assigning images to different categories)
  • Object detection (e.g. identifying and locating objects within images)
  • Image segmentation (e.g. identifying and delineating objects or regions at the pixel level)

  All workshop activities will be conducted in R, with the reticulate package used to access Python-based deep learning tools. Participants will set up a local Python environment using conda and install the required deep learning libraries before the workshop. Setup scripts and a test script will be provided in advance to help participants verify that their environment is ready.

  Participant Requirements

  Participants should:

  • Have a working R and RStudio installation, and complete the required environment setup before the workshop (detailed setup instructions and a test script will be provided in advance)
  • Be comfortable with basic R tasks (e.g. loading data, using functions, navigating RStudio)
  • Have familiarity with basic statistical concepts (e.g. regression, classification, and model evaluation)
  • Be connected via Zoom for workshop participation

  Desirable

  • No prior experience with deep learning, computer vision, or Python is required
  • Some familiarity with matrices, linear algebra, or optimization concepts may help with understanding key ideas, but is not necessary
  • Experience with statistical modelling or data analysis workflows is beneficial

  
  

  Cancellation Policy:

  Cancellations received prior to two weeks before the event will be refunded, minus the Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20.

  From then on, no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au.  

  Show details
• SSA Statistical Education Section webinar: Rethinking Student Learning and Assessment in AI-Supported Classrooms

  • When
    19 Nov 2026
  •  
    11:00 AM
  • Location
    Online

  Register

  The Statistical Education section of the Statistical Society of Australia invites members to a webinar titled "Rethinking Student Learning and Assessment in AI-Supported Classrooms" delivered by Emanuela Furfaro.

  Date: Thursday 19 November 2026

  Time: 11:00 am AEDT

  Format: Online via Zoom. Details provided upon registration

  Abstract: Rethinking Student Learning and Assessment in AI-Supported Classrooms

  How can we support student learning with generative AI while ensuring students still engage in meaningful thinking? This webinar introduces LLteacher, an open-source tool for designing AI-mediated learning activities in statistics courses. Emanuela Furfaro will demonstrate the tool, share experiences from its use in a large introductory statistics course, and discuss how AI-supported learning can balance student support with productive struggle.

  The session will include time for Q&A and discussion.

  Presenter Bio: Emanuela Furfaro

  
  

  Emanuela Furfaro is an Associate Teaching Professor and the Undergraduate Program Coordinator. She has a strong commitment to connecting with learners, understanding where they are and creating opportunities to better support their learning experience. Her research has a highly interdisciplinary aspect and it focuses on the development and application of statistical methods and models with collaborations in the field of social sciences, psychology, and demography.

  Key Learnings from attending webinar

  Participants will:

  • Explore how conversational AI can support learning and assessment in statistics.
  • Identify approaches that promote conceptual understanding and critical thinking.
  • Consider how to balance AI support with productive struggle in student learning.

  Show details
• SSA NSW Branch 2026 Annual Event: JB Douglas Award and Annual Lecture

  • When
    19 Nov 2026
  •  
    2:00 PM - 7:15 PM
  • Location
    Swissôtel, 68 Market St, Sydney
  • Spaces left
    49

  Register

  The New South Wales Branch of the Statistical Society of Australia invites you to their Annual Event - the JB Douglas Award and Annual Lecture. The afternoon will begin with presentations from PhD students from across NSW as part of the JB Douglas Award, showcasing the depth, breadth and excellence of postgraduate research in statistics and related fields across the state, followed by the Annual Lecture by Dr Emi Tanaka, Australian National University (ANU). The Event will conclude with the Annual Dinner. 

  Date: Thursday 19 November 2026

  Times (AEDT): 

  • 2:00 pm – 5:45 pm – JB Douglas Award presentations (with refreshment break)
  • 5:45 pm - 6:15 pm - Refreshments and award presentation
  • 6:15pm – 7:15 pm – Annual Lecture by Dr Emi Tanaka
  • 7:15pm – Annual Dinner Separate registration required

  Venue: Swissôtel, 68 Market St, Sydney

  Format: In person

  JB Douglas Award details will be provided soon.

  Abstract: Shaping a Symbiotic Future for Statistics in the Age of AI: Culture, Practice, and Software Development

  Artificial intelligence (AI) is emerging as one of the most significant technological disruptors of contemporary society. It is transforming almost every aspect of our lives: how we generate and discuss ideas, gather and process information, write code and solve mathematical problems. Statistics, both as a discipline and as a profession, is no exception.

  Bio: Emi Tanaka, Australian National University

  
  

  Emi Tanaka is an academic statistician at the Australian National University (ANU). Her work spans experimental design, mixed-effects models and data visualisation, alongside open-source software development and the use of AI in agricultural analytics and statistical workflows. She serves as the Editor-in-Chief of the R Journal, leads the ANU team for the Analytics for the Australian Grains Industry Project, and is an Elected Member of the International Statistical Institute.

  Show details
• SSA NSW Branch 2026 Annual Dinner

  • When
    19 Nov 2026
  •  
    7:15 PM - 10:00 PM
  • Location
    Swissôtel, 68 Market St, Sydney
  • Spaces left
    49

  Register

  Join the New South Wales Branch of the Statistical Society of Australia for the Annual Dinner after the presentation of the JB Douglas Award and Annual Lecture.

  Date: Thursday 19 November 2026

  Time: 7:15 pm til late AEDT

  Venue: Swissôtel, 68 Market St, Sydney

  Format: In person

  The dinner will be in a buffet setting, so please make sure to specify if you have any dietary requirements upon registration.

  To support our early career and student Statisticians community we are providing a discount:

  • If you are a student or transitional members, you will be able to use your corresponding registration type provided directly;
  • If you are not currently in the two membership type but within 5 years post your last Statistics degree, please send an email to secretary.nswbranch@statsoc.org.au with your name, last degree name, name of institution, time of your gradation, membership status and current position, we will verify and assist you with your registration. 

  
  

  Show details
• SSA Vic & Tas: Belz Lecture and ECSS Showcase

  • When
    20 Nov 2026
  •  
    2:00 PM - 5:30 PM
  • Location
    The University of Melbourne
  • Spaces left
    202

  Register

  Join The Victorian and Tasmanian Branch of the Statistical Society of Australia for the 2026 Belz Lecture and Early Career and Student Statistician (ECSS) Showcase. This hybrid event will begin with the ECSS Showcase, featuring presentations from early career and student statisticians, followed by afternoon tea. The annual Belz Lecture will then be delivered by Dr Carolyn Huston, Principal Research Consultant, CSIRO.

  Date: Friday 20 November 2026

  Time: 2:00 pm to 5:30 pm AEDT

  Format: Hybrid

  Venue: Peter Hall building, The University of Melbourne. If attending online, Zoom details will be provided closer to event date.

  Schedule:

  • 2:00–3:30 pm: ECSS talks (hybrid)
  • 3:30–4:30 pm: ECSS poster session and afternoon tea (in person only; sponsored by UoM Maths & Stats)
  • 4:30–5:30 pm: Belz Lecture (hybrid) 

  This event is free but registration is required. The ECSS talks and Belz Lecture will be held in the Evan Williams theatre or the JH Mitchell Theatre (to be confirmed after registrations close). The ECSS poster session and afternoon tea will be held in the Staff Tearoom. Abstracts for the ECSS Showcase have now closed.

  The evening will conclude with a canapés dinner at The Clyde at 5:45 pm. To secure your spot, please purchase your dinner ticket via the dinner event page. Each dinner ticket includes shared food platters and one drink. 

  Belz Lecture Abstract: Statistics and the 1%

  In world headlines, there are lots of 1%’s that feed news algorithms. There is the 1% who hold near 50% of the world’s wealth; there are 1% (or more) increases in inflation; the 1% change on bank lending interest; and similar. There are also those hazard events that apparently only have 1 in 100 year chance of occurrence, which seem to be happening much more often than once in 100 years!

  These headlines are contrast to the 1%’s I teethed on when first learning about and applying statistical practices. In statistics, it is more common for it to be discussion of 1% p-values; a 1% improvement in model prediction relative to a reference approach; assessing leverage point in data that has a more than 1% influence on model parameters; and similar.

  When I consider the aspects of my career so far as a statistician, some of my most satisfying 1% achievements don’t sit in either the drama of the headlines, or the perfection of publishing new methods or highly significant results, but rather somewhere in-between. This is the 1% of statistical practice that I will be presenting on as an opportunity for statistics as a discipline to consider in terms of how we think about and articulate our outcomes and impacts. 

  Belz Lecturer Bio: Dr Carolyn Huston, CSIRO

  
  

  Carolyn Huston is Principal Research Consultant at CSIRO with a background in statistics who enjoys applying statistical thinking from data design, modelling, reporting on uncertainty etc. to real life problems where results and methods will be used. She has led multiple projects related to bushfire resilience planning, particularly in the domain of improving electrical network safety.

  Key achievements include involvement with the Victorian Government Powerline Bushfire Safety Program (PBSP), contributing to numerical methods that guided $750 million of government investment. This investment resulted in an estimated 60% bushfire safety improvement across electrical distribution networks, and improved statistically supported regulation to support operation of new technologies.

  Continued work in this area has led to deep expertise in understanding the factors that cause bushfires; prevent or slow bushfires; and understanding and reporting on different aspects of bushfire consequence. In addition to bushfire commercial work, Carolyn is currently contributing to the strategic development of a number of natural hazards models and emulators, as well as programs to identify efficiency opportunities in manufacturing and supply chain processes.

  Altogether her work requires a keen interest in understanding how to improve uptake and effectiveness of AI (as a complex model) in real-life decision making. As a consequence of these interests, Carolyn is currently performing more formal research in responsible innovation and operationalisation and dissemination of equitable AI tools in a trusted and defensible way.

  She is also an Officer and Chair of the Data61 Diversity Inclusion and Belonging (DIB) committee, and the Analytics and Decision Sciences (ADS) representative for Reconciliation Action Plan (RAP) activities and reporting.

  Acknowledgements

  Organising team: Rick Tankard, Tong Chen, Leon Di Stefano, Elena Tartaglia and Susan Wei

  Local support at the University of Melbourne:

  Pavel Krupskiy, Rosie Pingitore and Cait Pryse. Thank you to the School of Mathematics and Statistics for sponsoring this event.

  For further information, please get in touch with the Victorian and Tasmanian Branch at vic.branch@statsoc.org.au 

  Show details
• SSA Vic & Tas: Belz Event Dinner

  • When
    20 Nov 2026
  •  
    5:45 PM
  • Location
    The Clyde, 385 Cardigan St, Carlton VIC 3053
  • Spaces left
    8

  Register

  Join The Victorian and Tasmanian Branch of the Statistical Society of Australia for a casual dinner after the Belz Event and ECSS Showcase. Tickets include shared platters of finger food and one drink.

  Date: Friday 20 November 2026

  Time: 5:45 pm AEDT

  Format: In person

  Venue: The Lounge, Ground Floor, The Clyde, 385 Cardigan St, Carlton VIC 3053

  
  

  For further information, please contact the Victorian and Tasmanian Branch at vic.branch@statsoc.org.au.

  Show details
• SSA WA Branch End of Year Function

  • When
    24 Nov 2026
  •  
    6:30 PM - 9:30 PM
  • Location
    Lil's Rooftop & Bar, 437 Murray St, Perth​

  Register

  The Western Australian Branch of the Statistical Society of Australia warmly invites members and guests to the 2026 WA Branch End of Year Function, an informal sit-down meal in a private dining room at a venue in the Perth CBD. The WA Branch is pleased to cover the cost of the first drink for WA Branch members.

  Date: Tuesday 24 November 2026

  Time: 6:30 pm - 9:30 pm AWST

  Venue: Lil's Rooftop & Bar, 437 Murray St, Perth​

  Cost: A la carte (menu), WA Branch will pay for your first drink (beer/wine/soft drink).

  Please register your attendance and indicate the number of accompanying guests.

  Lil’s Rooftop & Bar is located on Murray Street, approximately halfway between the Elder Street CPP and His Majesty’s CPP carparks. (Google Maps)

  
  

  The dinner itself is in the ground-floor private dining room “Lil’s Hideout” in the back of the venue, not at the upstairs bar.

  Wilson Car Park (427 Murray Street, Perth) is the most convenient (paid) parking option, along with timed street parking along Murray Street. There are also the CPP carparks at Elder Street and His Majesty’s.

  For further information please contact the WA Branch Secretary: wa.branch@statsoc.org.au

  Show details
• ADSN Pre-Conference Workshop: Modern Data Linkage Methods and Implementation Using Splink

  • When
    25 Nov 2026
  • Location
    In-person only: ABS House, Belconnen, ACT
  • Spaces left
    20

  Register

  
  

  
  

  Pre-Conference Workshop

  Linked data assets, such as Person Level Integrated Data Asset (PLIDA), are a rich source of information, allowing the analysis of interconnected systems such as healthcare, government services, education, and taxation. But the creation of these assets is not always straightforward, as often there is not a deterministic way of identifying individuals across datasets, such as with a unique identifier. Probabilistic data linkage methods can help resolve this problem by comparing fields common across datasets and give an estimate of how likely two records belong to the same individual.
  

  Join us for a separate one-day pre-conference workshop on probabilistic linking using the Python package Splink, presented by Aymon Wuolanne and Daniel Fearnley from the Data Linking Methodology section in the Australian Bureau of Statistics. The workshop will cover the theory underpinning probabilistic linking, as well as how to perform a basic Splink linkage. It will also explore advanced techniques for customising Splink for specific use cases. No prior background in probabilistic linking theory is required, although a basic understanding of Python is recommended.

  The workshop will be held day before the Australian Data Science Network Conference and  is open to everyone, not just conference delegates.

  Please note that workshop registration is separate from conference registration.

  Registration will close on Monday 2 November.

  Date: Wednesday 25 November 2026

  Times (AEDT): 9:00 am - 5:00 pm (Schedule will be released closer to the date) 

  Venue: ABS House, Belconnen, ACT

  Format: In person

  Key Learnings:

  Participants will come away with an understanding of the fundamental methods underlying probabilistic linkage and how to perform linkages using Splink.

  Presenter Bio:

  Daniel Fearnley

  

  Daniel Fearnley joined the ABS in 2011, and has spent the last 3 years in Data Linking Methodology where he has led the team responsible for assessing the feasibility of the probabilistic linkage tool Splink, and the transition to using Splink as the default linking tool for all ABS person-level linkages. His team won the 2026 APS Data Award in Data System and Innovation for their work on Splink. Outside of work, Daniel enjoys cooking and running (because he likes cooking) and earlier this year he and his wife watched every game of the FIFA World Cup.

  Aymon Wuolanne

  
  

  
  

  
  

  Aymon Wuolanne joined the ABS as a graduate in 2022 and is currently a methodologist in Data Linking Methodology. In 2025 he won the Ken Foreman Award for his work on building the Person Linkage Spine using Splink, and was a member of the team that won the 2026 APS Data Award in Data System and Innovation for their work on Splink. Outside of work, Aymon enjoys walking, reading, video games and running much slower than Daniel.

  Cancellation Policy

  Refunds: Cancellations made more than two weeks before the event are eligible for a refund, minus: Stripe processing fee: 1.75% + $0.30 per transaction and SSA administration fee: $20. No refunds will be issued for cancellations made within two weeks of the event.

  
  

  Transfer of Registration: Registrations can be transferred to another person within the same organisation at any time. Please notify changes via email: events@statsoc.org.au 

  
  

  For more information, please contact Ben Harrap : benjamin.harrap@anu.edu.au

  
  

   

  Show details
• ADSN Conference 2026

  • Start
    26 Nov 2026
  •  
  • End
    27 Nov 2026
  •  
  • Schedule
    2 sessions
  • Location
    In-person only: ABS House, Belconnen, ACT
  • Spaces left
    20

  Register

  
  

  
  

  Join us in the nation’s capital for the annual Australian Data Science Network Conference. This year’s theme is From Data to Decisions, which focuses on impactful data science that informs decisions, changes minds, and shapes policy.

  Conference registration covers both days of the conference and includes registration for the social event in the evening of the first day.

  Registration will close 3 weeks prior to conference date, on Monday 2 November.

  Visit the conference website for more details: Australian Data Science Network Conference 2026 – ADSN2026

  Cancellation Policy

  
  

  Refunds: Cancellations made more than two weeks before the event are eligible for a refund, minus: Stripe processing fee: 1.75% + $0.30 per transaction and SSA administration fee: $20. No refunds will be issued for cancellations made within two weeks of the event.

  
  

  Transfer of Registration: Registrations can be transferred to another person within the same organisation at any time. Please notify changes via email: events@statsoc.org.au 

  
  

  
  

  
  

   

  Show details
• OceaniaR 2026 presented by the Statistical Computing and Visualisation section

  • When
    29 Nov 2026
  •  
    9:00 AM - 4:00 PM
  • Location
    Monash College City Campus, 750 Collins St, Docklands, Melbourne VIC 3008
  • Spaces left
    18

  Register

  The Statistical Computing and Visualisation section of the Statistical Society of Australia are excited to announce the next OceaniaR event.

  Date: Sunday 29 November 2026
  Time: 9:00 am - 4:00 pm AEDT
  Format: In person only
  Venue: Monash College City Campus, 750 Collins St, Docklands, Melbourne VIC 3008
  Cost: $50 per person

  This is an interactive development day and a chance to collaborate and hack in-person on R-focused projects for social good, with some of the leading developers in the R community. There will also be time to hold informal talks to share ideas, concepts and new packages for feedback.

  This event will have a focus on promoting projects and participation from R users in the Oceania region including Australia, New Zealand and the Pacific Islands.

  This is the day before the Workshop Organised by the Monash Business Analytics Team (WOMBAT) conference.

  Get Involved!

  All project ideas for this event are created by attendees!

  All participants are encouraged to put forward and idea to work on. These will be listed as Issues on the project Github and the working groups will be decided on the day.

  Submit your idea here

  Further event details

  Cancellation Policy:

  Occasionally events have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.

  Cancellations received prior to two weeks before the event will be refunded, minus the Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20.

  From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au. 

  Show details