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/

The Random Sample&nbsp;steps into the dynamic world of interdisciplinary research&mdash;viewed through the lens of data science and statistics. Our guest is a true leader in collaborative science:&nbsp;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&nbsp;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 &mdash; 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: <a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=1853&amp;preview=true">https://www.therandomsample.com.au/podcast/interdisciplinar&hellip;ch-galit-shmueli/</a>

Welcome to The Random Sample! In this podcast, we share stories about mathematics, statistics, data science and the people involved. This is a collaboration between the Australian Data Science Network (ADSN), the Statistical Society of Australia (SSA), the Australian Mathematical Society (AustMS), the OPTIMA ARC Training Centre, the MATRIX Mathematical Research Institute, and the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). ACEMS created the podcast in 2018. For further resources and show notes, visit therandomsample.com.au

Welcome to The Random Sample! In this podcast, we share stories about mathematics, statistics, data science and the people involved. This is a collaboration between the Australian Data Science Network (ADSN), the Statistical Society of Australia (SSA), the Australian Mathematical Society (AustMS), the OPTIMA ARC Training Centre, the MATRIX Mathematical Research Institute, and the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS). ACEMS created the podcast in 2018. For further resources and show notes, visit <a href="https://www.therandomsample.com.au/">therandomsample.com.au</a>

Stories about mathematics, statistics and the people involved

The Random Sample

Bridging the Interdisciplinary Gap with Stats & Data Science - with Prof Galit Shmueli

Technology is transforming how we understand society. For decades, researchers relied on surveys to learn about populations. But today, data comes from everywhere - administrative records, social media, and even fitness trackers.

In this episode, we explore this shift with Professor Frauke Kreuter - a global leader in social data science. She explains how combining traditional survey methods with diverse data sources can help answer critical questions about health, education, and public policy, while also revealing the challenges of bias in digital data.

Recently, Frauke has made a bold move into artificial intelligence and large language models (LLMs). She shares why this transition matters, how AI is reshaping social research, and what the future holds for data-driven insights.

Our host is Cynthia Huang.

Episode page: https://www.therandomsample.com.au/podcast/social-data-science/

Technology is transforming how we understand society. For decades, researchers relied on surveys to learn about populations. But today, data comes from everywhere - administrative records, social media, and even fitness trackers.
In this episode, we explore this shift with Professor Frauke Kreuter - a global leader in social data science. She explains how combining traditional survey methods with diverse data sources can help answer critical questions about health, education, and public policy, while also revealing the challenges of bias in digital data.
Recently, Frauke has made a bold move into artificial intelligence and large language models (LLMs). She shares why this transition matters, how AI is reshaping social research, and what the future holds for data-driven insights.
Our host is Cynthia Huang.
Episode page: <a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=1951&amp;preview=true">https://www.therandomsample.com.au/podcast/social-data-science/</a>

From Surveys to LLMs: The New Era of Social Data – with Professor Frauke Kreuter

For decades, surveys have been the backbone of official statistics - helping us measure everything from population trends to economic activity. But response rates have been falling dramatically across the world for the past few decades. This decline is forcing statistical agencies to rethink how they collect the data we all rely on.

In this episode, we explore the shift toward multi-source data with our special guest, Dr Anders Holmberg, General Manager and Chief Methodologist for the Australian Bureau of Statistics (ABS).

What is multi-source data, how is it collected, and what are the challenges for official statistics agencies as they move to these new data sources?

Our host is Professor James Brown, Professor of Official Statistics and current head of discipline for Mathematical Sciences at the University of Technology Sydney.

Episode webpage:  https://www.therandomsample.com.au/podcast/multi-source-data-abs/

For decades, surveys have been the backbone of official statistics - helping us measure everything from population trends to economic activity. But response rates have been falling dramatically across the world for the past few decades. This decline is forcing statistical agencies to rethink how they collect the data we all rely on.
In this episode, we explore the shift toward multi-source data with our special guest, Dr Anders Holmberg, General Manager and Chief Methodologist for the Australian Bureau of Statistics (ABS).
What is multi-source data, how is it collected, and what are the challenges for official statistics agencies as they move to these new data sources?
Our host is Professor James Brown, Professor of Official Statistics and current head of discipline for Mathematical Sciences at the University of Technology Sydney.
Episode webpage: &nbsp;<a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=1942&amp;preview=true">https://www.therandomsample.com.au/podcast/multi-source-data-abs/</a>

Multi-Source Data & the Evolution of Official Statistics - with Dr Anders Holmberg

Modern slavery is often hidden in corporate supply chains, making it hard to detect and eliminate. Countries like Australia now require companies to publish annual reports on their efforts to combat slavery - but with thousands of reports, no government can read them all.

That’s where Project AIMS comes in. Led by Adriana Bora at the QUT Centre for Data Science, Project AIMS explores how cutting-edge AI can be used to compare thousands of these reports. To push this work further, Adriana helped organise a global hackathon, bringing together teams from around the world to develop innovative solutions.

In this episode of The Random Sample, we meet Adriana and members of the winning hackathon teams – from South Africa, Cameroon, and Australia – who share how data science can make the invisible visible and why technology can play a vital role in ending modern slavery.

Our host is Tim Macuga.

Episode webpage:  https://www.therandomsample.com.au/podcast/aims-hackathon/

Modern slavery is often hidden in corporate supply chains, making it hard to detect and eliminate. Countries like Australia now require companies to publish annual reports on their efforts to combat slavery - but with thousands of reports, no government can read them all.
That&rsquo;s where Project AIMS comes in. Led by Adriana Bora at the QUT Centre for Data Science, Project AIMS explores how cutting-edge AI can be used to compare thousands of these reports. To push this work further, Adriana helped organise a global hackathon, bringing together teams from around the world to develop innovative solutions.
In this episode of&nbsp;The Random Sample, we meet Adriana and members of the winning hackathon teams &ndash; from South Africa, Cameroon, and Australia &ndash; who share how data science can make the invisible visible and why technology can play a vital role in ending modern slavery.
Our host is Tim Macuga.
Episode webpage: &nbsp;<a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=1927&amp;preview=true">https://www.therandomsample.com.au/podcast/aims-hackathon/</a>

Bridging the Interdisciplinary Gap with Stats & Data Science - with Prof Galit Shmueli

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