The Random Sample

How are statistics and data science transforming advances in genetic sequencing into new insights about how people lived, formed families, and organised their societies thousands of years ago? Our guests are Dr Adam “Ben” Rohrlach, an Australian statistician at the Max Planck Institute for Evolutionary Anthropology in Germany, and Dr Simon “Jono” Tuke, Senior Lecturer in the School of Mathematical Sciences at the University of Adelaide. From their early collaboration during Ben’s PhD to their ongoing work today, they’ve combined mathematical rigour with archaeological and genetic research to help uncover patterns in ancient human life that would otherwise remain hidden. Together, they’ve applied cutting-edge statistical methods to support major discoveries – including their contribution to the 2017 Eureka Prize–winning research confirming the connection between Aboriginal Australians and their ancestral lands. In this conversation, we revisit that work and dive into their latest research, using ancient DNA to reconstruct family networks in a European society from over 1,300 years ago. It’s a fascinating look at how collaboration across disciplines – and the power of statistics – can bring us closer to understanding the lives of people from the distant past. Our host is Dr Haripriya Sridharan – a MACSYS Research Fellow at The University of Melbourne. Episode webpage:   https://www.therandomsample.com.au/podcast/ancient-dna/  See omnystudio.com/listener for privacy information.

The Random Sample steps into the dynamic world of interdisciplinary research—viewed through the lens of data science and statistics. Our guest is a true leader in collaborative science: Professor Galit Shmueli. Galit is the Tsing Hua Chair Professor at the Institute of Service Science at National Tsing Hua University in Taiwan, the inaugural editor-in-chief of the INFORMS Journal on Data Science, and a Fellow of the Institute of Mathematical Statistics. In this episode, she shares her insights on building meaningful connections across disciplines — and reflects on the role of artificial intelligence and large language models in shaping the future of research. Our host is Cynthia Huang. Episode webpage: https://www.therandomsample.com.au/podcast/interdisciplinar…ch-galit-shmueli/See omnystudio.com/listener for privacy information.

We’re diving into the design and development of the tools that have transformed data science and statistical programming — with none other than Dr Hadley Wickham. Hadley is the Chief Scientist at Posit (formerly RStudio), where he leads the Tidyverse team. This team is behind some of the most widely used open-source packages in the R programming language — including dplyr and ggplot2. These tools have empowered thousands of data scientists and researchers to explore complex datasets and communicate insights through compelling visualisations. In this episode,  Hadley shares key lessons he’s learnt from over two decades of building and maintaining open-source software. We also look ahead, as he discusses where he sees data science tooling headed — and the principles that will shape its future. Our host is Cynthia Huang. Episode webpage: https://www.therandomsample.com.au/podcast/hadley-wickham/See omnystudio.com/listener for privacy information.

Artificial Intelligence, or AI, is no longer a futuristic concept.  It’s here, embedded in almost every technology we use. It’s one of the most transformative forces of our time, and in this episode, we’re unpacking what that means, focusing on the powerful engines behind it: large language models, or LLM’s. A year and a half ago, The Random Sample did an episode exploring the science behind ChatGPT and its groundbreaking use of LLM’s.  Fast forward to now, and the A-I landscape has already shifted dramatically. The pace of innovation is staggering. Today, we’re bringing back our guest from that previous episode. Simon Angus is a Professor in the Department of Economics at Monash University. Simon is also a Principal Investigator with SoDa Labs at Monash Business School, a research lab that applies new tools from data science and machine learning to answer social science questions. Simon will help us navigate what’s new, and what we should be thinking about as AI continues to reshape the world. Whether you’re new to AI and unsure where to start, or already exploring how it can transform your work or life, this episode has something for you. Understanding this transformative technology isn’t optional. It’s essential – and Simon is here to break it all down in a way that’s clear, approachable, and practical. Our host is Pranita Shrestha, a PhD Candidate at the Action Lab in the Faculty of Information Technology at Monash University. Episode webpage with links:  https://www.therandomsample.com.au/podcast/beyond-chatgpt-ai-landscape/See omnystudio.com/listener for privacy information.

This is the first of our two-part series on a topic that’s sweeping the headlines: Artificial Intelligence or A-I. But we’re taking a different angle, one that many in the data and mathematical sciences might not consider often, but absolutely should. We’re talking about the law! This series will dig into the surprising intersections between A-I and legal frameworks—and the ways in which they’re increasingly intertwined. This episode gets into the here and now – how A-I is already impacting legal practice and policy. Our guest, Associate Professor Michael Guihot from QUT’s School of Law, is an expert on the intricate connections between emerging technologies and the legal system. He studies the societal impacts of innovations like A-I and how they challenge traditional legal frameworks. Guihot also brings A-I into his classroom, giving future legal minds hands-on experience with the technology that will shape their field. Our host for this series is Dr. Aaron Snoswell, a senior research fellow in A-I accountability at the QUT Generative AI Lab, and co-lead of the Responsible Data Science and A-I program at the QUT Centre for Data Science. Episode webpage: https://www.therandomsample.com.au/podcast/ai-law-part-1/See omnystudio.com/listener for privacy information.

Atherosclerosis is a silent but deadly condition. It happens when your arteries get clogged with plaque, restricting blood flow and putting you at serious risk for heart attacks and strokes. But here’s the fascinating part: maths is stepping up to help doctors and scientists understand how this condition develops and progresses. In this episode, we’re joined by two brilliant minds who organised a recent research program at MATRIX, Australia’s residential institute for the mathematical sciences. University of Oxford Professor Helen Byrne sits down with the University of Sydney’s Professor Mary Myerscough. Together, they unpack the complexities of using maths to model biological conditions like atherosclerosis.See omnystudio.com/listener for privacy information.