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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

  
  

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• SSA NSW Branch: Early Career and Student Statisticians Career Event 2026

  • When
    13 Oct 2026
  •  
    6:00 PM - 8:00 PM
  • Location
    The Mezzanine at The Loft on Broadway, University of Technology Sydney
  • Spaces left
    5

  Register

  The New South Wales Branch of the Statistical Society of Australia warmly invites all undergraduate, postgraduate, and early career statisticians and data scientists to attend our annual Early Career and Student Statisticians event on Tuesday, 13 October 2026, from 6:00 pm – 8:00 pm, in The Mezzanine at The Loft on Broadway, University of Technology Sydney.

  This year, we are delighted to host an inspiring line-up of early and mid-career speakers, spanning academia, government, and industry. They will share what they have learned, achieved, and enjoyed in their careers, as well as the challenges, surprises, and insights that have shaped their journeys.

  Each speaker will give a short 5-minute talk with time allotted for questions, followed by a networking session with catering and drinks provided. This is a unique opportunity to connect with peers and professionals in a relaxed setting. 

  Date: Tuesday 13 October 2026

  Time: 6:00 pm - 8:00 pm AEDT

  Venue: The Mezzanine at The Loft on Broadway, University of Technology Sydney

  Format: In person

  Fees: 

  • Free for SSA members
  • $25 for non-members

  Reminder: non-member full-time students can join the SSA for $25 per year, which allows free entry to this event. Click here for more information.

  Meet our Speakers

  Rory Chen – Project Officer, Centre for Healthy Brain Aging UNSW Sydney

  
  

  Rory Chen is a health data scientist specialising in the data infrastructure that underpins dementia research. She leads CHeBA’s Dementias Platform Australia (DPAU) initiative, which is dedicated to advancing the FAIR principles - making research data more Findable, Accessible, Interoperable, and Reusable. Her work sits at the nexus of data management, statistical analysis, and the design of scalable, reproducible data workflows. Proficient in R, Python, SAS, SQL, and REDCap, and experienced in cloud computing with AWS, Rory brings strong technical expertise to every stage of the research data lifecycle. She leads the DPAU team using agile project management methodologies and contributes to the broader data science community through active roles in R-Ladies Sydney and the UNSW CodeRs Committee. With more than nine years’ experience working with large, complex datasets, her career spans academic and public health settings. Her previous roles include the National Drug and Alcohol Research Centre (NDARC), UNSW, and the Chinese Center for Disease Control and Prevention (CDC).

  Giles Dickenson-Jones – Applied Economist and Public Policy Advisor, Independent Consultant

  
  

  Giles is an applied economist and public policy advisor working at the intersection of economics, data science and public policy. He began as an economist at the Federal Department of the Treasury during the 2008 Global Financial Crisis before taking research and advisory roles with the Institute for Economics and Peace, the Myanmar parliament and the London School of Economics's International Growth Centre. He now consults independently. Recent work includes advising the Asian Development Bank on an AI-driven job-matching tool for India, designing composite risk indices for the UNDP and building automated policy analysis pipelines for parliaments in the Pacific.

  Jie Kang - Applied Statistician, The University of Sydney | CTO, SureStock

  
  

  Jie Kang is a statistician, researcher and technology leader working at the intersection of statistics, data science and real-world decision making. He is an Applied Statistician at the University of Sydney and Chief Technology Officer of SureStock, an agtech startup developing data-driven tools for livestock health and production. His career has taken him across academia, industry and entrepreneurship, applying statistics to problems ranging from genetics and biomarkers to animal health.

  Sarah Lee – PhD Student in Bayesian Statistics, University of Technology Sydney

  
  

  Sarah Lee is a PhD student in Bayesian Statistics at the University of Technology Sydney. After completing a Bachelor of Commerce, she spent two years working in technology at EY. Wanting to continue learning, she returned to university to pursue research in statistics, with her PhD focusing on Bayesian statistical methods and their applications.

  Ika Yuni Wulansari - Statistician, Statistics Indonesia (BPS) | Assistant Professor, Politeknik Statistika STIS | PhD Candidate, University of Technology Sydney | Data Scientist, Health+Law Australia

  
  

  Ika Yuni Wulansari is a statistician, researcher and educator working across government statistics, academia, data science and applied research. She holds bachelor’s and master’s degrees in Statistics and is currently completing her PhD in Statistics at the University of Technology Sydney (UTS), while maintaining professional roles with Statistics Indonesia (BPS) and Politeknik Statistika STIS. Her research focuses on Small Area Estimation (SAE) and Official Statistics, developing methods that turn complex national data into reliable local evidence for policy and public decision-making. She also contributes to SAE knowledge sharing and collaboration across Australia, New Zealand, and the Pacific region, with research connections extending to Canada and Europe. At Health+Law Australia, Ika works as a data scientist in the quantitative team on the Legal Needs Study (LeNS), working across the survey data workflow from raw data preparation, cleaning and management through to statistical analysis, while supporting interpretation and national- and state-level reporting on the legal needs of people living with HIV and Hepatitis B in Australia. Across these roles, she is driven by rigorous statistical methods to make underrepresented communities more visible in data and to strengthen the evidence available to support better policy, services and decision-making.

  Paco Tseng - Statistical Analyst in Perils Modelling | IAG

  
  

  Paco Tseng is a statistical analyst working in Perils Modelling at IAG, with a focus on storm risk modelling for general insurance. He holds a PhD in Statistics, where his research centred on Variational Bayes computation. At IAG, Paco applies statistical methods to develop spatial storm risk models that combine long-term weather data, policy exposure, and claims experience to better understand loss patterns across Australia and New Zealand. His work sits at the intersection of statistical modelling, actuarial science, climate risk, and insurance pricing, with a particular interest in translating rigorous statistical methods into practical tools for risk assessment and decision-making.
  

  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 Vic & Tas Branch: Early Morning Coffee Catch-Up

  • When
    15 Oct 2026
  •  
    8:00 AM
  • Location
    Anda Cafe, 215 Spring St, Melbourne VIC 3000

  Register

  Join The Victorian and Tasmanian Branch Council of the Statistical Society of Australia for an early morning social catch-up. It's an opportunity to catch up with fellow statisticians and data scientists in an informal setting in person.

  Date: Thursday 15 October 2026

  Time: 8:00 am AEDT

  Venue: Anda Cafe, 215 Spring St, Melbourne VIC 3000

  
  

  Coffee Offer:

  A complimentary coffee is available for up to five ECSS and Transitional Members. Eligible members should register using the code: Free Coffee to redeem this offer.

  
  

  Registration:

  This is a free event, but registration is encouraged so we can provide attendees with information on how to locate the group on the day.

  Show details
• SSA ECSSN and NZSA SECS joint webinar: From scripts to R package: Lessons from developing moiraine

  • When
    20 Oct 2026
  •  
    1:00 PM
  • Location
    Online

  Register

  The Early Career & Student Statisticians Network (ECSSN) of the Statistical Society of Australia invites you to a joint webinar with the New Zealand Statistical Association's Student and Early Career Statisticians Network (NZSA SECS). The presentation titled "From scripts to R package: lessons from developing moiraine" will be delivered by Olivia Angelin-Bonnet and Lindy Guo.

  Date: Tuesday 20 October 2026

  Time: 1:00 pm AEST / 2:00 pm AEDT / 4:00 pm NZDT

  Format: Online via Zoom. Details provided upon registration

  Abstract: From scripts to R package: lessons from developing moiraine

  Statisticians often repeat similar analyses across different datasets, copying and tweaking existing code from one project to the next. Over time, this leads to accumulating several near-identical versions of the same code. Turning this code into an R package is one solution for facilitating code reuse, but for researchers without a software development background, this can seem daunting. In this seminar, we walk through the process of turning a collection of R scripts into moiraine, an R package for generating reproducible pipelines for multi-omics integration. We will cover our motivation for starting, the tools that supported the process, and the lessons learned along the way.

  Presenter Bios

  Olivia Angelin-Bonnet

  
  

  Olivia Angelin-Bonnet completed her PhD in Statistics at Massey University, where she worked on unravelling genotype-to-phenotype relationships from multi-omics data, with a focus on polyploid organisms. After a year as a lecturer in Statistics at Massey University, she is now a Statistical Scientist at Bioeconomy Science Institute. Her research interests include Systems Biology, multi-omics data integration, the study of biological networks from a statistical and computational perspective, and the development of visualisation tools for omics data.

  Lindy Guo

  
  

  Lindy Guo is a Statistical Scientist in the Data Science Group at the Bioeconomy Science Institute (formerly Plant & Food Research) in Auckland. Her work spans the breadth of plant science, consumer research, and, increasingly, multi-omics integration. Working alongside domain scientists as the data expert, she leads and contributes to experimental design, methodology development, statistical modelling and data validation.

  
  

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• National Speaker Series by SSA QLD Branch: Research Quality Is Under Threat from Speed, Fraud and AI

  • When
    21 Oct 2026
  •  
    12:00 PM - 1:30 PM
  • Location
    Online

  Register

  The Statistical Society of Australia's branches have come together to launch the National Speaker Series, bringing you insightful talks from experts across the country.  During the year, a different branch will host an event, showcasing diverse topics in statistics and data science. 

  The Queensland Branch of the Statistical Society of Australia invites you to an online webinar titled "Research Quality Is Under Threat from Speed, Fraud and AI" presented by Prof. Adrian Barnett. 

  Date: Wednesday 21 October 2026

  Time: 12:00 pm - 1:30 pm AEST

  Format: Online via Zoom. Details provided upon registration

  Abstract: Research Quality Is Under Threat from Speed, Fraud and AI

  High-quality research takes time. The best research uses a detailed study protocol, carefully collects data, and thoroughly reports the findings and limitations. The pressure to "publish or perish" means that much current research is rushed, with corners cut so that research teams can be first at the cost of being correct. Statistical coding is often rushed and model checking is rarely done. As well as sloppy practice, there is also outright fraud where results are massaged or even entirely faked to get a published paper. These problems are being exacerbated by a research system under strain, as publication numbers are rising and stretching the already limited resource of peer review. AI is adding to the strain, as it allows researchers to quickly write papers and create code in areas that were previously outside their expertise. Large changes are needed to the research system to ensure that published research findings are reliable. Researchers who want to demonstrate good quality will soon need to leave detailed paper trails of their work to show their work's provenance. Better systems of reproducibility checks are urgently needed, which could be automated or carried out by qualified researchers for high-impact papers.

  Presenter Bio: Professor Adrian Barnett

  
  

  Professor Adrian Barnett graduated from University College London with a BSc in Statistics in 1994. After that, he worked for SmithKline Beecham and the Medical Research Council as a statistician before coming to Australia to do a PhD. He completed his PhD in Mathematics in 2002. He currently works at the Australian Centre for Health Services and Innovation at QUT. His research interests are in meta-research, research funding, data sharing, peer review, and reducing research waste. He is the past president of the Statistical Society of Australia and the Association for Interdisciplinary Meta-Research and Open Science (AIMOS). His main interest is how to increase the value of health and medical research.

  Key Learnings

  Attendees will leave with a clearer view of what quality research actually requires, how speed and AI are putting that at risk, and what statisticians can do to protect the provenance and reproducibility of published findings

  
  

  Show details
• Async and Parallel R: Building the Open Source Tools. A Webinar by the Statistical Computing and Visualisation section

  • When
    22 Oct 2026
  •  
    6:00 PM - 7:00 PM
  • Location
    Online

  Register

  The Statistical Computing and Visualisation section of the Statistical Society of Australia proudly presents an Invited Speaker webinar titled "Async and Parallel R: Building the Open Source Tools" delivered by Charlie Gao, Senior Software Engineer at Posit (formerly RStudio).

  Date: Thursday 22 October 2026

  Time: 6:00 pm - 7:00 pm AEDT

  Format: Online via Zoom. Details provided upon registration

  Abstract: Async and Parallel R: Building the Open Source Tools

  Simulation studies, bootstrapping, cross-validation, MCMC - statistical computing is full of work that could run in parallel, yet parallel R too often means a blocked session, a copy of your data on every worker, and code rewritten for each new environment. Over several years I've built the layers needed to fix this: a messaging substrate for reliable async I/O, a framework for async and parallel computing on top of it, and a way to share R objects across processes without copying. This talk is a practical tour of that stack from laptop to HPC cluster, with patterns you can apply to your own analyses straight away, plus a closing look at where the zero-copy model is headed next.

  Key Learnings

  Attendees will:

  • Recognise the parallelism already in their workflows — simulation studies, bootstrap, cross-validation, multiple chains — and the two costs that usually cap it: blocked sessions and copied data.
  • Run R code in parallel with mirai in a few lines, then scale the identical code to their own servers, HPC schedulers or the cloud by changing one line of configuration.
  • Keep large data in one place with mori: `share()` a dataset once so every worker maps the same memory instead of holding a private copy.
  • Keep interactive sessions and Shiny apps responsive while heavy computation runs, using event-driven async instead of batch-and-wait.
  • Know where to start on their own projects: both packages are on CRAN, with a mechanical migration path from existing parallel/future code.

  Presenter Bio: Charlie Gao

  
  

  Charlie Gao is a Senior Software Engineer at Posit (formerly RStudio), where he builds open-source tools for data science and technical communication. He is the author of mirai — R's modern framework for async and parallel computing, now the shared backend behind Shiny, plumber2, purrr, tidymodels, and targets — and mori, which brings zero-copy shared memory to R. Recent speaking engagements include posit::conf(2025) in Atlanta, Japan R 2025 (keynote), and useR! 2026 in Warsaw. He is also a member of the Quarto core team, developing Quarto 2 — the next version of Posit's authoring system, designed for collaboration at its heart.

  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

  • Monday 26 October 2026 12:30 pm - 1:30 pm AEDT
  • Monday 23 November 12:30 pm - 1:30 pm AEDT
  • Monday 22 February 2027 12:30 pm - 1:30 pm AEDT
  • Monday 22 March 2027 12:30 pm - 1:30 pm AEDT

  
  

  Show details
• SSA Vic & Tas Branch seminar: Good Practice When Incorporating AI into Statistical Analyses

  • When
    28 Oct 2026
  •  
    11:00 AM - 1:00 PM
  • Location
    The Forest Building, University of Tasmania, Hobart
  • Spaces left
    19

  Register

  The Victorian and Tasmanian Branch of the Statistical Society of Australia invites you to the annual Tasmanian section lunch-time meet-up and informal seminar. This year we have Dr Luke Yates presenting his experience with using AI tools to improve the quality of his statistical analyses. The seminar will be held in The University of Tasmania's new Forest Building in Hobart, and the room is accessible to the public. Some lunch snacks will be provided and discussions about anything statistics-related is encouraged.

  Date: Wednesday 28 October 2026

  Time: 11:00 am - 1:00 pm AEDT

  Venue: Rm 1008, Floor L01, The Forest Building, University of Tasmania, 83 Melville Street, Hobart CBD

  Format: In person

  Presenter Bio - Dr Luke Yates

  
  

  Dr Luke Yates is a postdoctoral research fellow with the ARC Centre of Excellence for Plant Success in Nature and Agriculture. In 2019 he completed a PhD in mathematical physics after which he took up a postdoctoral position in mathematical ecology prior to his current role which began in 2022.

  Luke is interested in applied and theoretical aspects of mathematical and statistical modelling. His areas of interest include: model selection, cross validation, Bayesian inference and computational aspects, comparative phylogenetics, statistical 'omics' analysis, multivariate methods, and joint species distributions. Luke particularly enjoys cross-disciplinary projects that bring together mathematical innovation and domain-specific expertise to make progress on applied problems.

  Show details
• SSA QLD Branch: Early Career and Student Networking Night

  • When
    30 Oct 2026
  •  
    5:30 PM - 7:30 PM
  • Location
    Room 14-216, Sir Llew Edwards Building, St Lucia Campus, University of Queensland
  • Spaces left
    38

  Register

  The Queensland Branch of the Statistical Society of Australia invites postgraduate students and early career statisticians to an evening built around the question: What does a career in statistics look like?  Three speakers, with backgrounds in academia, industry and government, will share their perspective about their beginnings, what their week involves and advice for those starting out. A brief panel session will give an opportunity to ask questions, with an extended networking session over food and drinks following this.

  Date: Friday 30 October 2026

  Time: 5:30 pm - 7:30 pm AEST

  Venue: Room 14-216, Sir Llew Edwards Building, St Lucia Campus, University of Queensland
  Format: In person

  Presenter Bios:

  Louise Marquart-Wilson, The University of Queensland and Cancer Council Queensland

  
  

  Louise is a Senior Research Fellow in biostatistics in UQ's School of Public Health and Viertel Cancer Research Centre at CCQ and came to academia after several years as a biostatistician and then senior biostatistician at QIMR. Louise leads and contributes to a range of projects within public health and cancer research, including leading analyses of the Australian Childhood Cancer Registry. Her methodological work centres on interrupted time series and understanding impact of mis-specified models for statistical inference.

  Cheng-Han (Kerwin) Lin, Sanofi

  
  

  Kerwin is a Senior Clinical Biostatistician in Sanofi's Translational Science Hub (TSH), based in Brisbane. He contributes to the statistical and operational aspects of vaccine development, focusing on study design and strategic planning in accordance with ICH GCP guidelines. He also supports data management to ensure clinical data integrity and quality throughout the trial lifecycle. Kerwin has gained comprehensive experience across both contract research organizations (CROs)—including Novotech and Avance—and the sponsor side (Sanofi). His CRO background specialized in operational implementation and trial execution, while his current sponsor-side role emphasizes design and strategic development phases. He holds a Master of Science in Public Health from National Yang Ming University in Taiwan.

  David Bridge, Australian Bureau of Statistics

  
  

  David is the Assistant Director with the Australian Bureau of Statistics Health and Vital statistics division, the national statistical agency responsible for the Census and for the official statistics that inform government policy. Within this role, he contributes to analysis and production of national health and population statistics.

  Key Learnings

  • Understanding the different career pathways available to statisticians, in academia, industry and government
  • Learning how early stages of a statistics career can look like and how they can evolve over time
  • Hearing about the application of statistics in diverse projects

  
  

  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
    18

  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 Vic & Tas: Belz Lecture and ECSS Showcase

  • When
    20 Nov 2026
  •  
    2:00 PM - 5:30 PM
  • Location
    The University of Melbourne
  • Spaces left
    244

  Register

  Abstract submissions for the ECSS Showcase are now open! Closing Wednesday 7 October
  

  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.

  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. Early bird registrations will close Friday 16 October.

  Call for Abstracts:

  Abstract submissions for the ECSS Showcase are now open and will close at
  11:59 pm AEDT on Wednesday 7 October 2026. Early Career and Student Statisticians (as defined by SSA) are invited to submit an abstract using the abstract submission page. Awards will be presented for best oral and poster presentations.

  Eligibility: The Showcase is open to Early Career and Student Statisticians - those who are either:

  • studying statistics or a related field; or
  • have graduated within the past 5 years and work in a statistics-related area.

  There are no age restrictions, and both SSA members and non-members are welcome to submit.

  

  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 

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• SSA Vic & Tas: Belz Event Dinner

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

  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.

  The number of early bird tickets we sell will determine how big a venue we book, so get in early for a discount and to make sure you don't miss out! Early bird registrations will close Friday 16 October.

  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.

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• 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 3 weeks prior to Pre-Conference Workshop and Conference dates.

  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

  
  

   

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• ADSN Conference 2026

  • Start
    26 Nov 2026
  •  
  • End
    27 Nov 2026
  •  
  • Schedule
    2 sessions
  • Location
    In-person only: ABS House, Belconnen, ACT
  • Spaces left
    35

  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.

  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
    20

  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