Here’s something to toast to. Australia’s wine industry is leading the way when it comes to a very important issue: sustainability.

And Data Science is helping the industry do that!

In this episode, we explore the Data Science project being carried out by the Australian Wine Research Institute (AWRI), how and why it started, and how grape growers and wine makers are coming to embrace these new data-driven efforts.

Our guests are Mardi Longbottom, General Manager for Industry Development and Support at the AWRI, and Bryce Polley, a PhD Candidate at the QUT Centre for Data Science and the University of Adelaide working with AWRI.

Our host is Tim Macuga, Senior Project Officer for the QUT Centre for Data Science and the Australian Data Science Network.

Website link: https://www.therandomsample.com.au/podcast/data-for-sustainable-winemaking/

Here’s something to toast to. Australia’s wine industry is leading the way when it comes to a very important issue: sustainability.
And Data Science is helping the industry do that!
In this episode, we explore the Data Science project being carried out by the Australian Wine Research Institute (AWRI), how and why it started, and how grape growers and wine makers are coming to embrace these new data-driven efforts.
Our guests are Mardi Longbottom, General Manager for Industry Development and Support at the AWRI, and Bryce Polley, a PhD Candidate at the QUT Centre for Data Science and the University of Adelaide working with AWRI.
Our host is Tim Macuga, Senior Project Officer for the QUT Centre for Data Science and the Australian Data Science Network.
Website link: <a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=1605&amp;preview=true">https://www.therandomsample.com.au/podcast/data-for-sustainable-winemaking/</a>

Welcome to The Random Sample - a podcast from the ARC Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS).  In this podcast, we share stories about mathematics, statistics, data science and the people involved. The Random Sample is also proud to have the support of these supporting partners: 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 - a podcast from the ARC Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS).&nbsp; In this podcast, we share stories about mathematics, statistics, data science and the people involved. The Random Sample is also proud to have the support of these supporting partners: 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

Welcome to The Random Sample - a podcast from the Australian Research Council Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS). In this podcast, we share stories about mathematics, statistics, data science and the people involved. The Random Sample is also proud to have the support of these supporting partners:  Australian Data Science Network (ADSN), Statistical Society of Australia (SSA), Australian Mathematical Society (AustMS), OPTIMA ARC Training Centre, 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 - a podcast from the Australian Research Council Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS). In this podcast, we share stories about mathematics, statistics, data science and the people involved. The Random Sample is also proud to have the support of these supporting partners:&nbsp; Australian Data Science Network (ADSN), Statistical Society of Australia (SSA), Australian Mathematical Society (AustMS), OPTIMA ARC Training Centre, 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>

Grapes & Algorithms: the Data Science of Sustainable Winemaking

How do airlines schedule flights, logistics companies route deliveries, and supermarkets manage stock?

Many of these challenges are examples of linear programming problems – and one algorithm has dominated their solution for decades: the Simplex Method.

Widely regarded as one of the most important algorithms ever developed, the Simplex Method has helped organisations save vast amounts of time, money and resources.

But despite its remarkable success, one question has puzzled mathematicians for decades: why does it work so well in practice?

In this episode, Dr Sophie Huiberts from the French National Centre for Scientific Research (CNRS) explores one of optimisation’s biggest open questions: why is the Simplex Method so much faster than theory often predicts?

We also discuss Sophie’s research journey and how she brings her values and social awareness into her work as a mathematician.

Our host is Professor Kate Smith-Miles – Director of the OPTIMA ARC Training Centre, and a Professor of Applied Mathematics at The University of Melbourne.

Episode webpage:  https://www.therandomsample.com.au/podcast/simplex-method/

How do airlines schedule flights, logistics companies route deliveries, and supermarkets manage stock?
Many of these challenges are examples of&nbsp;linear programming&nbsp;problems &ndash; and one algorithm has dominated their solution for decades: the&nbsp;Simplex Method.
Widely regarded as one of the most important algorithms ever developed, the Simplex Method has helped organisations save vast amounts of time, money and resources.
But despite its remarkable success, one question has puzzled mathematicians for decades: why does it work so well in practice?
In this episode,&nbsp;Dr Sophie Huiberts&nbsp;from the&nbsp;French National Centre for Scientific Research (CNRS)&nbsp;explores one of optimisation&rsquo;s biggest open questions: why is the Simplex Method so much faster than theory often predicts?
We also discuss Sophie&rsquo;s research journey and how she brings her values and social awareness into her work as a mathematician.
Our host is Professor Kate Smith-Miles &ndash; Director of the OPTIMA ARC Training Centre, and a Professor of Applied Mathematics at The University of Melbourne.
Episode webpage: &nbsp;<a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=2190&amp;preview=true">https://www.therandomsample.com.au/podcast/simplex-method/</a>

The Algorithm that Transformed Optimisation - with Dr Sophie Huiberts

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/

 

How are&nbsp;statistics and data science transforming advances in genetic sequencing&nbsp;into new insights about how people lived, formed families, and organised their societies thousands of years ago?
Our guests are Dr Adam &ldquo;Ben&rdquo; Rohrlach, an Australian statistician at the Max Planck Institute for Evolutionary Anthropology in Germany, and Dr Simon &ldquo;Jono&rdquo; Tuke, Senior Lecturer in the School of Mathematical Sciences at the University of Adelaide. From their early collaboration during Ben&rsquo;s PhD to their ongoing work today, they&rsquo;ve combined mathematical rigour with archaeological and genetic research to help uncover patterns in ancient human life that would otherwise remain hidden.
Together, they&rsquo;ve applied cutting-edge statistical methods to support major discoveries &ndash; including their contribution to the 2017 Eureka Prize&ndash;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&rsquo;s a fascinating look at how collaboration across disciplines &ndash; and the power of statistics &ndash; can bring us closer to understanding the lives of people from the distant past.
Our host is Dr Haripriya Sridharan &ndash; a MACSYS Research Fellow at The University of Melbourne.
Episode webpage: &nbsp;&nbsp;<a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=2154&amp;preview=true">https://www.therandomsample.com.au/podcast/ancient-dna/</a>
&nbsp;

From DNA to Discovery: How Statistics Brings the Ancient Past to Life - with Dr Adam "Ben" Rohrlach & Dr Simon "Jono" Tuke

In this episode of The Random Sample, we explore the science of scale – from the behaviour of granular materials to the remarkable world of nanotechnology. Professor Natalie Thamwattana, an applied mathematician from the University of Newcastle, shows how studying the very small can lead to big insights across science and engineering.

Her pioneering work in nanotechnology is helping unlock how some of nature’s smallest building blocks can tackle some of our biggest challenges – in medicine, energy, and electronics. In a field often dominated by heavy numerical simulations, Natalie was among the first to take a different path, developing analytical, formula-based approaches to understand the mechanics of carbon nanostructures.

Alongside her research, Natalie shares a deeply personal story of growing up in Thailand and forging a path into mathematics. It’s a journey shaped by resilience, curiosity, and the support of her family – one that led to an international career at the forefront of applied mathematics.

Our host is Cait Pryse – from The University of Melbourne.

Episode webpage:  https://www.therandomsample.com.au/podcast/nanotechnology-natalie-thamwattana/

In this episode of&nbsp;The Random Sample, we explore the science of scale &ndash; from the behaviour of granular materials to the remarkable world of nanotechnology. Professor Natalie Thamwattana, an applied mathematician from the University of Newcastle, shows how studying the very small can lead to big insights across science and engineering.
Her pioneering work in nanotechnology is helping unlock how some of nature&rsquo;s smallest building blocks can tackle some of our biggest challenges &ndash; in medicine, energy, and electronics. In a field often dominated by heavy numerical simulations, Natalie was among the first to take a different path, developing analytical, formula-based approaches to understand the mechanics of carbon nanostructures.
Alongside her research, Natalie shares a deeply personal story of growing up in Thailand and forging a path into mathematics. It&rsquo;s a journey shaped by resilience, curiosity, and the support of her family &ndash; one that led to an international career at the forefront of applied mathematics.
Our host is Cait Pryse &ndash; from The University of Melbourne.
Episode webpage: &nbsp;<a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=2078&amp;preview=true">https://www.therandomsample.com.au/podcast/nanotechnology-natalie-thamwattana/</a>

Grapes & Algorithms: the Data Science of Sustainable Winemaking

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