2019 Ihaka Lecture Series | Rise of the machine learners: Statistical learning in the computational era

Department of Statistics


Ihaka Lecture Series

In March 2017 the Department of Statistics launched a new, annual lecture series named after Associate Professor Ross Ihaka in honour of his contributions to the field. Find out about the 2019 lecture series below.

The Ihaka lectures


The series is named after Ross Ihaka, Associate Professor in the Department of Statistics at the University of Auckland. Ross, along with Robert Gentleman, co-created R – a statistical programming language now used by the majority of the world’s practicing statisticians. It is hard to over-emphasise the importance of Ross’s contribution to our field. We named this lecture series in his honour to recognise his work and contributions to our field in perpetuity.

Following on from the success of last year's series, the theme of the 2019 Ihaka lectures is Rise of the machine learners: Statistical learning in the computational era. The series will run from 13 March to 3 April; find out more below.

Our thanks to The New Zealand Statistical Association who are our official sponsors for the 2019 Ihaka Lecture Series.

The New Zealand Statistical Association
Top

2019 series


Rise of the machine learners | Statistical learning in the computational era

Whether labelled as machine learning, predictive algorithms, statistical learning, or AI, the ability of computers to make real-world decisions is rising every year.

The 2019 Ihaka Lecture Series brings together four experts at the interface of statistics and computer science to discuss how computers do it, and how much we should let them.

Location | Lecture Theatre PLT1, Ground Floor, Building 303, 38 Princes Street, City Campus.

Time | 6.30pm, Wednesdays.

Refreshments will be available before each lecture at 6pm in the basement foyer, Building 303.

 

Professor Bernhard Pfahringer, University of Waikato Ihaka Lecture Series 2019 speaker
Professor Bernhard Pfahringer

13 March - Open source Machine Learning @ Waikato

Professor Bernhard Pfahringer
University of Waikato

Watch the lecture.

Professor Thomas Lumley, Department of Statistics, Ihaka Lecture Series 2019 speaker
Professor Thomas Lumley

20 March - Deep learning: why is it deep, and what is it learning?

Professor Thomas Lumley
Univeristy of Auckland

Watch the lecture.

This lecture replaces Machine Learning with TensorFlow and R, which has been cancelled.
Our guest speaker, JJ Allaire, is no longer able to present as part of the 2019 Ihaka Lecture Series due to ill-health. 

Dr Kristian Lum, Human Rights Data Analysis Group (HRDAG) Ihaka Lecture Series 2019 speaker
Dr Kristian Lum
Professor Robert Tibshirani, Stanford University Ihaka Lecture Series 2019 speaker
Professor Robert Tibshirani

3 April - Statistical learning and sparsity

Professor Robert Tibshirani
Stanford University

Watch the lecture.

Top

Ross Ihaka


Photograph of Associate Professor Ross Ihaka
Associate Professor Ross Ihaka

Associate Professor Ross Ihaka was born in South Auckland and received his education in a variety of small country schools in the Cook Islands and the northern North Island. He completed his BSc(Hons) and MSc Mathematics degrees at the University of Auckland before undertaking his doctoral study in statistical aspects of seismology at the University of California at Berkeley.

After completing his PhD he held positions at Yale University and the Massachusetts Institute of Technology before taking up a joint position as lecturer for the departments of Computer Science, Mathematics and Statistics at the University of Auckland. Ross retired from the University of Auckland as an Associate Professor in 2017.

Ross's first experience with computing was in an Applied Mathematics course taught by Garry Tee, John Butcher and F D K Roberts. His next serious exposure to computing was in a group of Berkeley students working on a local variant of the Princeton ISP system under the guidance of Jim Reeds. He also learned about computational statistics and graphics under the guidance of Dan Asimov, Leo Breiman, David Brillinger, Louis Jaekal and Jim Reeds.

During his student career, Ross honed his computing skills by developing two of his own interactive systems for statistical computing and added a further two soon after graduating (with some input from John Hartigan).

At the University of Auckland he developed the R statistical system with Robert Gentleman. Initially R was a platform for computing experiments, but it was given a superficial veneer to make it look like the Bell Laboratories’ S system. The rationale for imposing this similarity was to get access to the large amount of ‘free’ code available for S.

The R system has gone on to achieve significant success and is now widely used all over the world.

Top

Archived lectures


2018 Ihaka Lecture Series

A thousand words: visualising statistical data

A picture is worth a thousand words – or perhaps that should be a million numbers. The distillation of data into an honest and compelling graphic is essential component of modern (data) science. This year’s Ihaka Lecture Series displays the contributions of three experts across different facets of data visualisation.

Everyone is welcome to attend our lectures in person, but if you cannot make it along on the day don't worry - each lecture will be live streamed via our website (follow the links below for details), and uploaded as videos to watch at a later date. For any technical help regarding the live streaming, please contact webmaster@stat.auckland.ac.nz

 

Photograph of Associate Professor Paul Murrell

Wednesday 14 March – Making colour accessible

Associate Professor Paul Murrell
Department of Statistics, The University of Auckland

Watch the lecture

Photograph of Alberto Cairo

Wednesday 21 March –  Visual trumpery: How charts lie — and how they make us smarter

Alberto Cairo
Knight Chair in Visual Journalism, University of Miami

Watch the lecture

 

2017 Ihaka Lecture Series

Statistical Computing in the Data Age

Statistics has become essential in the data age. We have increasing ability to collect vast quantities of data, but often still struggle to make sense of it. The 2017 Ihaka lectures aimed to highlight the important role that both statistics and computing play in this endeavour.

Learn about each of our guest speakers and watch videos from their lectures below.

 

Photograph of Hadley Wickham

Wednesday 8 March – Expressing yourself with R

Hadley Wickham 
Chief Scientist, RStudio
Honorary Associate Professor, Department of Statistics, University of Auckland

Watch the lecture

Photograph of Genevera Allen

Wednesday 22 March – Interactive visualisation and fast computation of the solution path for convex clustering and biclustering

Genevera Allen
Dobelman Family Junior Chair
Departments of Statistics and Electrical and Computer Engineering, Rice University

Watch the lecture

Photograph of Ross Ihaka

Wednesday 29 March – Statistical computing in a (more) static environment

Ross Ihaka
Associate Professor, Department of Statistics, University of Auckland

Watch the lecture

Top