We explore the field of discrete optimisation and how industries and companies use it to make decisions for complex problems. Our guest is Monash University Professor Peter Stuckey, a pioneer in constraint programming (CP) which is a powerful approach to solving discrete optimisation problems. Professor Stuckey explains why he believes optimisation is the intelligence behind AI. Our host is Dr Sevvandi Kandanaarachchi.

We explore the field of discrete optimisation and how industries and companies use it to make decisions for complex problems. Our guest is Monash University Professor Peter Stuckey, a pioneer in constraint programming (CP) which is a powerful approach to solving discrete optimisation problems. Professor Stuckey explains why he believes optimisation is the intelligence behind AI. Our host is Dr Sevvandi Kandanaarachchi.

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>

Optimisation: The Intelligence Behind AI

What does a data scientist actually do? And how do you become one?

Data is everywhere. Every day, vast amounts of information are generated through research, healthcare, business, technology, and our daily lives. But collecting data is only part of the story. The real challenge lies in making sense of it.

That's where data scientists come in.

In this episode, we meet four data scientists whose careers have taken them in very different directions, demonstrating that there is no single path into the field.

Joining us are:
Dr Farzana Jahan, Lecturer in Statistics and Data Science at Murdoch University
Dr Nick Tierney, Statistical Consultant
Joanna Salerno, Data Scientist and Developer at QCIF Digital Research Services
Dr Stuart Schvetz, Senior Data Scientist at the Hunter Medical Research Institute

Together, they share the experiences, opportunities, and turning points that led them into data science.

Whether you're exploring study or career options, looking to better understand the role of data science in research and industry, or simply curious about the people behind the data, this episode offers an engaging look at one of the fastest-growing professions in the world.

Our host is Macarena Rojas, Engagement and Outreach Manager at QCIF.

Episode webpage: https://www.therandomsample.com.au/podcast/many-paths-data-science/

What does a data scientist actually do? And how do you become one?
Data is everywhere. Every day, vast amounts of information are generated through research, healthcare, business, technology, and our daily lives. But collecting data is only part of the story. The real challenge lies in making sense of it.
That's where data scientists come in.
In this episode, we meet four data scientists whose careers have taken them in very different directions, demonstrating that there is no single path into the field.
Joining us are:
<ul>
<li>Dr Farzana Jahan, Lecturer in Statistics and Data Science at Murdoch University</li>
<li>Dr Nick Tierney, Statistical Consultant</li>
<li>Joanna Salerno, Data Scientist and Developer at QCIF Digital Research Services</li>
<li>Dr Stuart Schvetz, Senior Data Scientist at the Hunter Medical Research Institute</li>
</ul>
Together, they share the experiences, opportunities, and turning points that led them into data science.
Whether you're exploring study or career options, looking to better understand the role of data science in research and industry, or simply curious about the people behind the data, this episode offers an engaging look at one of the fastest-growing professions in the world.
Our host is Macarena Rojas, Engagement and Outreach Manager at QCIF.
Episode webpage: <a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=2231&amp;preview=true">https://www.therandomsample.com.au/podcast/many-paths-data-science/</a>

The Many Paths to Data Science

Multiple sclerosis, or MS, affects millions of people worldwide, yet many aspects of the disease remain poorly understood. One of its defining characteristics is the way symptoms can fluctuate over time, with periods of relapse followed by remission. What drives these cycles, and why does the disease appear stable one moment before suddenly worsening the next?

In this episode, we speak with Dr Adrianne Jenner, Senior Lecturer in QUT’s School of Mathematical Sciences, about her latest research tackling this question through mathematics. Adrianne and her collaborators have developed a groundbreaking mathematical model that reproduces the relapsing-remitting patterns seen in MS, offering new insights into the biological processes that may underlie disease progression.

We also explore Adrianne’s broader work in mathematical oncology, where mathematical models are helping researchers better understand how cancers grow, evolve and respond to their environment. Along the way, we discuss the unique role mathematics can play in biology and medicine, and why collaboration between mathematicians and experimental scientists is becoming increasingly important in modern research.

Our host is Dr Haripriya Sridharan, a Research Fellow with MACSYS at The University of Melbourne.

Episode webpage:  https://www.therandomsample.com.au/podcast/ms-maths-adrianne-jenner/

Multiple sclerosis, or MS, affects millions of people worldwide, yet many aspects of the disease remain poorly understood. One of its defining characteristics is the way symptoms can fluctuate over time, with periods of relapse followed by remission. What drives these cycles, and why does the disease appear stable one moment before suddenly worsening the next?
In this episode, we speak with Dr Adrianne Jenner, Senior Lecturer in QUT&rsquo;s School of Mathematical Sciences, about her latest research tackling this question through mathematics. Adrianne and her collaborators have developed a groundbreaking mathematical model that reproduces the relapsing-remitting patterns seen in MS, offering new insights into the biological processes that may underlie disease progression.
We also explore Adrianne&rsquo;s broader work in mathematical oncology, where mathematical models are helping researchers better understand how cancers grow, evolve and respond to their environment. Along the way, we discuss the unique role mathematics can play in biology and medicine, and why collaboration between mathematicians and experimental scientists is becoming increasingly important in modern research.
Our host is Dr Haripriya Sridharan, a Research Fellow with MACSYS at The University of Melbourne.
Episode webpage: &nbsp;<a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=2221&amp;preview=true">https://www.therandomsample.com.au/podcast/ms-maths-adrianne-jenner/</a>

Modelling the Mysteries of Multiple Sclerosis – with Dr Adrianne Jenner

In 2020, as COVID-19 spread across the globe, researchers faced an urgent challenge: finding treatments that could save the lives of patients hospitalised with the virus. One of the most important efforts was the RECOVERY trial, a clinical trial designed to rapidly test potential therapies and generate reliable evidence at a time when the world desperately needed answers.

Our guest, Professor Thomas Jaki, was part of the team behind RECOVERY from its earliest days. In this episode, he shares how the trial came together at remarkable speed, the challenges of conducting research during a global pandemic, and the key statistical and design decisions that allowed the study to deliver results quickly without compromising scientific rigour.

The impact was extraordinary. RECOVERY identified five life-saving COVID-19 treatments while also showing that several commonly used therapies were ineffective. Its findings influenced clinical practice around the world and helped shape the care of millions of patients.

It’s a fascinating conversation about clinical trials, decision-making under pressure, and the power of statistics to improve healthcare on a global scale.

Our host for this episode is Dr Min Zhang – a biostatistician with the University of Queensland's Clinical Trials Capability (ULTRA). She also serves on The Random Sample editorial group as a representative of the Statistical Society of Australia.

In 2020, as COVID-19 spread across the globe, researchers faced an urgent challenge: finding treatments that could save the lives of patients hospitalised with the virus. One of the most important efforts was the RECOVERY trial, a clinical trial designed to rapidly test potential therapies and generate reliable evidence at a time when the world desperately needed answers.
Our guest, Professor Thomas Jaki, was part of the team behind RECOVERY from its earliest days. In this episode, he shares how the trial came together at remarkable speed, the challenges of conducting research during a global pandemic, and the key statistical and design decisions that allowed the study to deliver results quickly without compromising scientific rigour.
The impact was extraordinary. RECOVERY identified five life-saving COVID-19 treatments while also showing that several commonly used therapies were ineffective. Its findings influenced clinical practice around the world and helped shape the care of millions of patients.
It&rsquo;s a fascinating conversation about clinical trials, decision-making under pressure, and the power of statistics to improve healthcare on a global scale.
Our host for this episode is Dr Min Zhang &ndash; a biostatistician with the University of Queensland's Clinical Trials Capability (ULTRA). She also serves on The Random Sample editorial group as a representative of the Statistical Society of Australia.

Optimisation: The Intelligence Behind AI

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