Every two years, Australia’s applied mathematics community invites a distinguished international academic to speak at universities across Australia.

This year, the AMSI-ANZIAM Distinguished Lecturer is Professor Konstantin Avrachenkov, Director of Research at France’s National Institute for Research in Digital Science and Technology, or INRIA.

The Random Sample caught up with Prof Avrachenkov at the recently held ANZIAM 2023 Conference in Cairns. Also joining us for this episode is his PhD Supervisor from some 20 years ago, Emeritus Professor Jerzy Filar.

Every two years, Australia’s applied mathematics community invites a distinguished international academic to speak at universities across Australia.
This year, the AMSI-ANZIAM Distinguished Lecturer is Professor Konstantin Avrachenkov, Director of Research at France’s National Institute for Research in Digital Science and Technology, or INRIA.
The Random Sample caught up with Prof Avrachenkov at the recently held ANZIAM 2023 Conference in Cairns. Also joining us for this episode is his PhD Supervisor from some 20 years ago, Emeritus Professor Jerzy Filar.

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>

The AMSI-ANZIAM Distinguished Lecturer: Prof Konstantin Avrachenkov

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.

Science at Pandemic Speed: The Clinical Trial that Changed COVID Care - with Professor Thomas Jaki

It’s a question many early career researchers grapple with: academia or industry?  For Professor Roslyn Hickson, the answer is simple: why choose?

Roslyn is an applied mathematician with a joint appointment at CSIRO and James Cook University, where she serves as Science Leader for Emerging Infectious Diseases.

Her career has taken her across academia, the military, government and industry, before arriving at her current role bridging research and real-world application.

In this episode, Roslyn reflects on the career decisions that shaped her journey, the different cultures she’s experienced across sectors, and the lessons she’s learned along the way.

Earlier this year, Roslyn was awarded the inaugural K.A. Landman Medal by ANZIAM, recognising her outstanding contributions to industrial and applied mathematics. She shares why the award is particularly meaningful to her and what it says about the growing importance of mathematics beyond the university setting.

Our host for this episode is Dr Sophie Raynor, a lecturer in mathematics at James Cook University.

Podcast Episode Page:  https://www.therandomsample.com.au/podcast/roslyn-hickson/

It&rsquo;s a question many early career researchers grapple with: academia or industry?&nbsp; For Professor Roslyn Hickson, the answer is simple: why choose?
Roslyn is an applied mathematician with a joint appointment at CSIRO and James Cook University, where she serves as Science Leader for Emerging Infectious Diseases.
Her career has taken her across academia, the military, government and industry, before arriving at her current role bridging research and real-world application.
In this episode, Roslyn reflects on the career decisions that shaped her journey, the different cultures she&rsquo;s experienced across sectors, and the lessons she&rsquo;s learned along the way.
Earlier this year, Roslyn was awarded the inaugural&nbsp;K.A. Landman Medal&nbsp;by ANZIAM, recognising her outstanding contributions to industrial and applied mathematics. She shares why the award is particularly meaningful to her and what it says about the growing importance of mathematics beyond the university setting.
Our host for this episode is Dr Sophie Raynor, a lecturer in mathematics at James Cook University.
Podcast Episode Page: &nbsp;<a href="https://www.therandomsample.com.au/?post_type=podcast&amp;p=2201&amp;preview=true">https://www.therandomsample.com.au/podcast/roslyn-hickson/</a>

Academia or Industry?  Why Professor Roslyn Hickson Chose Both

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 AMSI-ANZIAM Distinguished Lecturer: Prof Konstantin Avrachenkov

In 1 playlist(s)

The Random Sample

Social links

Follow podcast

Recent clips