2026

2025

• E. A. Cornish memorial lecture/National Speaker Series - Professor Martin Hazelton, 17 Nov 2025 
• Belz Lecture 2025 and ECSS Showcase - Prof Thomas Lumley, 27 Oct 2025
• World Statistics Day Webinar – “Data we can trust” - Lucy Farrell, Kalinda Griffiths, Ben Harrap, Simon Jackman, Sue Keay, Aaron Snoswell and Lynne Giles, 20 Oct 2025
• What Does It Take to Be a Mentor? Experiences from the SSA Mentoring Program - Adrian Barnett, Kristy Robledo, Kris Rogers, Rebecca Harding, 14 Oct 2025
• The Personal Journey of Helen MacGillivray - Helen MacGillivray, 4 Sep 2025
• Building Your Personal Brand with LinkedIn - Tim Macuga, 4 Sep 2025
• Panel Discussion: What Makes a Great Di Cook Prize Application? - Dianne Cook, Dr. Nicholas Tierney, Tomasz Woźniak, Fonti KarDr Patrick (Weihao) Li, 25 Aug 2025
• The Statistician and Public Controversy: The Murujuga Rock Art Monitoring Project, WA -  Professor Adrian Baddeley, FAA, Ian Gordon, 28 Aug 2025
• Smoking Guns - Generating Evidence to Inform Tobacco Control - Grace Joshy, 26 Aug 2025 
• National Speaker Series Hosted by ACT Branch:Combining Data from Different Sources in Official Statistics; Examples from Small Area Estimation and Population Size Estimation - James Brown, 29 Jul 2025
• Estimating Size of Hidden Populations in Sensitive Contexts: Applications in HIV, Reproductive Health, and Mental Health- Lessons from Iran - Dr Mohammad Reza Baneshi, 27 Jun 2025
• Personal Journey of Eric Sowey - 5 Jun 2025 
• Hidden Statistical Thinking—Weaving Stories of Strength on Integrating Indigenous Perspectives Across the Curriculum - Samantha Low-Choy, 27 May 2025
• The data analyst’s guide to PLIDA Personal Level Integrated Data Asset - Tom Lawrence, 6 May 2025

• Designing cluster randomised trials for the real world - Jessica Kasza, 25 Mar 2025

• Venables Award - Alex Lee, Rob Moss, 18 Mar 2025
• Enhancing Decision-Making with analytics in the Government and Mining sector - Ming Dong,  11 Mar 2025
• Personal Journey of Len Cook - 11 Mar 2025
• Celebrating International Women’s Day 2025 - Panel Discussion, 5 Mar 2025
• Where are the self-correcting mechanisms in science? - Simine Vazire, 3 Mar 2025
• Treatment effect estimation with entropy balancing in observational studies - Bronwyn Loong, 25 Feb 2025
• Di Cook Award: Promoting Open Source Statistical Software Development - 25 Feb 2025
• Personal Journey of Anthony Pakes - 21 Jan 2025 (some audio issues in the beginning of the video)

2024

• Wilson Lecture 2024 - Gillian Heller, 2 Dec 2024

• Belz Lecture: Challenges of High Dimension Low Sample Size Data Analysis - J. S. Marron, 7 Nov 2024
• Presenting effectively at mixed mode events presented - Karen Lamb, 28 Oct 2024
• Forecasting demand for Australian passports - Edward Kang, 24 Sep 2024
• Analysing haphazard Surveys with mild ish Assumptions - Gordana Popovic, 24 Sep 2024
• Are AFL players peaking in performance at a younger age? - Dr Shane A. Richards, 17 Sep 2024
• Harnessing the Power of Predictive Analytics for Statisticians - Minitab - Ming Dong, 3 Sep 2024
• A Neural-Statistical Hybrid Model for Spatio-temporal Prediction of Groundwater Dynamics in Bangladesh - Dan Pagendam, 29 Aug 2024
• Personal Journey of Brian Phillips - 27 Aug 2024
• Causal machine learning in health research - Daisy Shepherd, 20 Aug 2024
• Setting up a reproducible data analysis project in R – featuring Github, renv, targets and more - Olivia Angelin-Bonnet, 20 Aug 2024
• Are Statisticians Sufficiently Engaged with Public Policy? - Dennis Trewin AO FASSA,  30 July 2024
• Explainable AI And Different Types Of Graphs - Carolyn Huston, 16 Jul 2024
• The Use of Compositional Data Analysis in Physical Behaviour Research - Dr Charlotte Lund Rasmussen, 11 Jun 2024
• What goes into a global temperature number? - Blair Trewin, 19 June 2024
• Adventures in Statistics and Genetics a brief history of the methods in Animal Breeding - Roy Costilla, 25 June 2024
• Using Propensity Scores in Observational Data Analysis: Some Theory and a Practical Application - Daniel Chateau, 25 June 2024
• Using leave-one-out cross-validation in a multilevel regression and poststratification workflow: A cautionary tale - Dr Fui Swen Kuh (Swen), 21 May 2024
• SSA WA: Early Career & Student Statisticians Evening - George Malone, Alistair Martin, 14 May 2024 (Poor audio)
• Fast Integrative Factor Models: Applications from Nutritional Epidemiology to Cancer Genomics - Dr Alejandra Avalos-Pacheco, 10 Apr 2024
• Building Data Science Capacity within the BC Public Service: A Decade of Progress - Dr Stephanie Hazlitt, 9 Feb 2024
• Bayesian semi-mechanistic modelling with greta for ecology and epidemiology - Nick Golding, 6 Feb 2024

2023

• Much More Than Just Fitting Models - Perspective from an Applied Statistical Scientist - Olivia Angelin-Bonnet

• Novel applications of cross-sectoral data linkage to understand and reduce health inequities among Australians in contact with the criminal justice system - Professor Stuart Kinner and Lindsay Pearce
• SmP2023: Perspectives from two Early Career Statisticians - Melissa Middleton, Shih Ching Fu
• Statistical methods for quantifying empathic accuracy - Linh Nghiem
• Detection of Lymph Node Metastasis in Endometrial Cancer Patients/and Estimation with Extended Sequential Order Statistics - Sophie Giraudo, Tim Pesch
• Machine Learning at the AIHW - Dr. Sumon Shahriar
• Getting to Know Stats New Zealand - Wendy Dobson, Tiana Whitehead
• Why statisticians must have a tailored insurance program - KBI
• Causal inference in Econometrics and Health Sciences - Associate Professor Margarita Moreno-Betancur and Dr Akanksha Negi

2022

• Enacting sovereign rights of Aboriginal and Torres Strait Islander people in official statistics and other data - Dr Kalinda Griffiths

• Belz lecture - Dr Dina Neiger
• Bad Statistics in Medical Research - Prof Adrian Barnett
• Optimal Design of Comparative Experiments and the odw R Package - Brian Cullis
• Evaluation of spatial Bayesian Empirical Likelihood models in analysis of small area data - Dr Farz
• clusterBMA: Combine insights from multiple clustering algorithms with Bayesian model averaging - Owen Forbes
• Recognising the value of research software - Tom Honeyman
• Geostatistics for Regionalised Compositions - AProf Ute Mueller
• The initial impact of the COVID-19, social distancing and movement restrictions on crime in NSW, Australia - Dr Joanna Wang
• Non parametric and semi parametric models for analysing longitudinal data - Dr Kefei Chen
• Managing uncertainty: statistics and econometrics as part of a multidisciplinary approach - Dr Steph Stammel
• Considering patient outcomes and healthcare costs when obtaining prediction model cutpoints may improve value-based care -  Rex Parsons
• The UK Coronavirus Dashboard How we provide a daily, high demand service - Clare Griffiths
• Mosaic single cell data integration - Shila Ghazanfar
• Really Useful Engines Engineering Data Science - Miles McBain
• Current state and prospects of R packages for the design of experiments - Emi Tanaka
• Bayesian Analysis of Raman Spectroscopy - Matt Moores
• From AI to Action - Michael Bewley
• Presentation of Di Cook Award projects - Weihao (Patrick) Li, Jeffrey Pullin, Sayani Gupta
• Elastic Registration of NMR spectra from patients with autism spectrum disorder-Michael Gerrard and Clustering wheat grain yield responses to develop new maturity types - Tinula Kariyawasam
• On Arbitrarily Underdispersed Discrete Distributions - Dr Alan Huang
• Research software engineers how will they shape statistics - Maëlle Salmon, Paula Andrea Martinez. Thomas Lumley , Nick Golding 
• Elections…Trust Verify! - Damjan Vukcevic
• COVID-19: Unexpected Opportunities and Lessons for Australia's Biostatistics, Bioinformatics and Epidemiological Community - Prof Adrian Esterman, Gideon Meyerowitz-Katz
• Lancaster Lecture- A mixing path from theory to applications - Dr Clara Grazian
• A loss-based prior distribution on the number of components of mixture models - Dr Clara Grazian
• Linking Heterogeneous Human Cognition with Household Financial Stress in an Agent-Based Model: Livestock Vaccine Decision-Making Among the Global Poor - Dr Richard A. Iles
• From PhD to post doc navigating life as an early career researcher  - Dr Rheanna Mainzer
• The Academia Industry War Surviving the conflict between two opposing ideals as a graduate student - Dr. Timothy Bilton
• Measuring Sex, Gender Identity, and Sexual Orientation - Nancy Bates, Kellan E. Baker, Bianca D. M. Wilson
• Kernel Stein discrepancy minimization for MCMC thinning in cardiac electrophysiology - Dr Marina Riabiz
• SSA-AMSI Data Science Review: introduction and aims - Jessica Kasza
• ECSSMini 2022 Day 3 Keynote 4
• ECSSMini 2022 Day 3 session 11
• ECSSMini 2022 Day 3 session 10
• ECSSMini 2022 Day 3 session 9
• ECSSMini 2022 Day 3 session 8
• ECSSMini 2022 Day 3 keynote 3
• ECSSMini 2022 Day 2 Keynote 2
• ECSSMini 2022 Day 2 Session 7
• ECSSMini 2022 Day 2 Session 6
• ECSSMini 2022 Day 2 Session 5 
• ECSSMini 2022 Day 2 Sessions 3 and 4
• ECSSMini 2022 Day 2 Keynote 1
• ECSSMini2022 Day 1 panel
• ECSSMini2022 Day 1 Session 2
• ECSSMini2022 Day 1 Session 1
• ECSSMini2022 workshop part 2
• ECSSMini 2022 workshop part 1
•  

2021

• Statistics in the public eye the case of predicting election outcome - Prof Simon Jackman

• COVID-19 and turnover in the Australian labour market - Gabriela Nodari
• Statistical Methodology Development and Software Dissemination - Prof Matt Wand
• E.A. Cornish Lecture - Rob Hyndman
• Sieve bootstrap memory parameter in long-range dependent stationary functional time series - Prof Hanlin Shang
• When your research meets Covid A case study - Dr Nancy Briggs
• Research in Engineering Statistics: Current Trends and Future Challenges - Dr Manuel Herrera
  
• Dennis Trewin prize- Ali Shojaeipour, Xian Li
• Peer-Review Seminar and Panel Discussion - Dr Myra McGuinness, Prof Kate Lee, Prof Andrew Forbes, Prof Alan Welsh
• "A Unified Bayesian Model for Predicting Volleyball Games" - Prof. Ioannis Ntzoufras
• Belz Lecture - Professor Andrew Forbes
• September Industry Event 
• Can a digital, geospatially enhanced data ecosystem incorporate Indigenous defined protocols, principles and approaches to achieve data democracy for Aboriginal and Torres Strait Islander peoples? - Darren Clinch
• Biostatistics collaborations in Health and Social research: The road taken - Alberto Nettel-Aguirre
• The Science of Survival in Game of Thrones - Reidar Lystad 
• Carrots are good for vision, models are good for visualising discrete data - Gordana Popovic 
• Consulting environments and their consequences - Alun Pope
• Lancaster lecture: Bad statistics in health and medical research - Adrian Barnett
• How to see the forest from the trees: Removing pesky artefacts from discrete data for better visualisation - Gordana Popovic
• The statistical quandaries of an ecologist: Applied and theoretical statistics for conservation - David Wilkinson
• Mental Health and Well-being and the Statistical Society of Australia - Desiree Dickerson, PhD-Only available until 8 November 2021
• Uncertain Futures: What Can We Forecast and When Should We Give Up - Professor Rob J. Hyndman
• Parallel Tempering on Optimized Paths - Trevor Campbell
• Principal stratification based on latent survival classes to predict treatment outcomes for localized kidney cancer - Brian Egleston
• Introducing the SSA Mentoring Program - Karen Lamb

2020

• Lancaster Lecture: Count on someone who can count - Thomas Fung

• The new normal: distributional regression - Gillian Heller
• Models and Uncertainty in the time of COVID-19 - Sally Cripps
• Knibbs lecture: A personal tour with Prof. Raymond Carroll - Raymond Carroll
• Just not cricket: How did sports science get stuck in the statistical outfield? - Stephen Woodcock
• Belz Lecture: "To be trusted is a greater compliment than to be loved": a maxim for official statistics - Teresa Dickinson
• The 2020 Statistical Science Lecture (SSL): Zen and the Art of Bayesian Geology/Hydrology/Ecology - Sally Cripps
• Partners in Prevention: Understanding and Enhancing First Response to Suicide Crisis Situations - Carla Meurk, Megan Steele, Lisa Wittenhagen, Ed Heffernan
• Modelling the Rate of Spread of Fire: A Stochastic Differentiation Equation Approach - Smaila Sanni
• Early Career Industry Showcase - Michelle Lugton, Nick de Silva, Ben Phillips, Sarah Romanes, Peter Taylor, Rose Skandari
• The Eye of the Beholder: Regression Coefficients & Mechanical Objectivity in Public Health Research - Taya Collyer
• SSA Vic Branch Mentoring Evening 
• Foreman Lecture: What is the difference and does it matter? Reflections on how the methodology work in Official Statistics relates among countries and on the Australian opportunities - Anders Holmberg
• Sharpening the Blade: Missing Data Imputation using Supervised Machine Learning - Marcus Suresh, Warren Jin
• How Statistics is used to help creating better justice system - A case study - Joanna Wang
• Beyond Beamer: Modern and Dynamic Presentations with R Markdown - Emi Tanaka
• Restructuring Categorical Predictors using L1-Norm Penalties - Application to Stillbirth Prediction - Emily Whitney
• Sensor Networks and Distributed Intelligence - Rachel Cardell-Oliver
• Leveraging Statistical Shapes in Genomics: Looking beyond what's normal - Jessica Mar
• Raising Heretics: Teaching effective scepticism using data science - Linda McIver
• Generalizations of Orthogonal Components in Analysis of Variance - Brenton Clarke
• Panel discussion on COVID-19 - Raina MacIntyre, John Maindonald
• Mighty Maps: Showcasing Estimate Uncertainty - Susanna Cramb, Lydia Lucchesi
• Variable Selection for Decision-Making in Individualised Treatments - Howard Bondell
• COVID-19: Modelling and Public Health Policy - Allen Cheng, Freya Shearer
• Measuring Well-being - Dennis Trewin
• Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies - Murthy Mittinty
• Data Co-ops in Australia - Tom Verhelst
• Inferring genetic relatedness to identify disease-causing variants and selection signals - Melanie Bahlo
• The Advent of "Grammar": Bridging Statistics and Data Science for the Design of Experiments - Emi Tanaka
• Computing Bayes: Bayesian Computation from 1763 to the 21st century - Gael M. Martin
• It's Alive! Frankenstein for President - James Cochran
• Advances in Data Linking Methodologies at the ABS - Daniel Elazar
• An application of network meta-analysis: is electronic cigarette effective for smoking cessation? - Gary Chan
• Random Effects Inference in Linear Mixed Models: The good, the bad, and the misspecified - Francis Hui, Alan Welsh , Samuel Muller
• Can multiple disparate data sources complement each other? - Anders Holmberg, Rajeev Samarage
• Statistical Consulting in the 21st Century
• Getting to know our "Cell mates": A practical approach to microbiome analysis through a biostatistician's lens - Elasma Milanzi
• Writing Successful Fellowships - Scott Sisson, Kerrie Mengersen, Adrian Barnett
• Tales of An Applied Statistician - Marijke Welvaert
• How to make a learning healthcare system work”: from linking data, machine learning to ethics - Katrien Groenhof
• Learning about COVID-19 Knowns Unknowns: The essential role of Statisticians - Nicholas Fisher, Dennis Trewin
• Statistical Machine Learning for Spatio-Temporal Forecasting - Andrew Zammit-Mangion
• Do we die of only one cause ? Unlocking the full potential of multiple-cause mortality data - James Eynstone-Hinkins, Lauren Moran, Margarita Moreno-Betancur

2016 - 2019

• Modelling Molecule Dropout in Single Cell RNA-SEQ Experiment Leads to Improved Identification of Marker Genes - A/Prof Agus Salim
• Communicating health risks and scientific uncertainty - Sir David Spiegelhalter
• Introduction to Business Analytics Beyond Statistical Analysis - Dr Mark Griffin 
• Inference for Spatio-Temporal Changes of Arctic Sea - Professor Noel Cressie 

• We all count: Strengthening Stats and Maths through diversity (Talks)

• We all count: Strengthening Stats and Maths through diversity (Panel Discussion)
• P-values: the good, the bad and the wrong - Ian Marschner
• Belz Lecture: Statistics is the Crown Jewel of Data Science - Antony Ugoni
• Stochastic modelling and Statistical Analysis of Cosmic Microwave background data - Ravindi Nanayakkara
• Using Polygenic Risk Scores to Predict Risk of Disease: hype, hope and statistical reality - Cathryn Lewis
• Presenting Uncertainty and Risk - John Henstridge
• Foreman Lecture: Challenges in Balancing Data Confidentiality and Utility - Daniel Elazar
• Multiple imputation in three-level data structures - Rushani Wijesuriya
• Automated Technologies: Systematic Review & Meta-Analysis - Alexandra Bannach-Brown
• Detecting Botnet Activity using Machine Learning - Jill Slay
• Nonparametric estimation for streaming data - Mao Jiadong
• Population Sampling: A Mixed Method Study - Matt Schneider
• A Notion of Depth for Curve Data - Pierre Lafaye de Micheaux
• Gender and cultural bias in student evaluations of teaching - Yanan Fan
• Data science helping to create a better justice system - Suzanne Poynton, Joanna Wang
• Time Series: A conference honouring Prof. William Dunsmuir 
• Cancer maps: the future is here - Susanna Cramb
• A recipe for quantifying the impact of prevention - Tony Blakely
• Tutorial on Sequential Monte Carlo Methods - Anthony Lee
• Lancaster lecture: "Expectations of Life: from past to present" - Kerrie Mengersen
• The present and future of tidy data - Hadley Wickham
• Latest developments in species distribution modelling - Ian Renner
• Multimorbidity: Measurement for HRQoL and Health Service Use - Jeeva Kanesarajah
• Reproducibility and Open Science - Fiona Fidler, Hannah Fraser, Matthew Ling
• Statistics with industry: demonstrating impact - Shirley Coleman
• Big data: does it have anything to do with me? - Xue Li
• The journey of an errant statistician: using science to tackle social problems - Ross Homel
• Human vs computer: when visualising data, who wins? - Di Cook
• Optimisation in the darkness of uncertainty - Kate Smith-Miles
• Biostats bonanza! - Valentijn de Jong, Jennifer Thompson, Simon White
• The statistician as an expert: the truth, the whole truth, and statistics - John Henstridge
• Credit scoring: improved predictions or improved interpretability? - Ed Stokes
• Data and Decision-Making: Informative missingness, recommender systems, and personalised medicine - Howard Bondell
• Towards massive-scale predictive modelling of infectious disease distributions - Nick Golding
• An applied statistician in the 'omics era - Kim-Anh Le Cao
• Women in Statistics and Mathematics: Repairing the Leaky Pipeline
• Open data: unlocking Melbourne - Steve Bennett
• But I'm a data scientist too, aren't I? - Louise Ryan
• What does industry need from statisticians? (panel discussion)
• A Bird's-Eye View of Statistics for Remote Sensing Data - Noel Cressie
• Statistical evaluation of evidence in criminal casework - David Balding
• Data Science: Will Computer Science and Informatics Eat our Lunch? - Thomas Lumley
• VIC branch: 2017 Young Statisticians Showcase - Anurika De Silva, Dilini Talagala, Kelsey Grantham, Thiyanga Talagala
• Statistical Issues in Randomized Breast Cancer Trials - Prue Francis
• Probabilistic modelling and inference made easy - Bob Carpenter
• Recent Advances in the area of deep learning for big data - Zhen He