Talks and presentations
See a map of all the places I've given a talk!
September 16, 2023
Talk, ICCDA 2023 - Paper Presentation., Guiyang - China
Contextual targeting is a common strategy that places marketing messages in media locations that are aligned with a target audience. The challenge of contextual targeting is knowing the ideal schema and the set of categories that provide the right audience. Refinement of the contextual targeting process has been limited by the use of metrics that are either rapid but unreliable (click through rates), or reliable but slow, expensive and inaccessible in real-time (conversions or brand awareness).
August 19, 2023
Talk, DSCC 2023 - Paper Presentation., Chennai - India
Consumers are expected to partially reveal their preferences and interests through the media they consume. The development of visual attention measurement with eye tracking technologies allows us to investigate the consistency of these preferences across the creative executions of a given brand and over all brands within a given vertical.
March 25, 2023
Talk, MLHMI 2023 - Paper Presentation., Singapore
Eye tracking applications produce a series of gaze fixation points that can be attributed to objects within a subject’s field of vision. Error is typically measured on the basis of individual gaze fixation point measurements. These applications are often used to infer a gaze duration metric from a series of fixation measurements. There is no direct method for infering the error in a gaze duration measurement from an error in fixation points.
March 17, 2023
Talk, Imperial College London - Guest Lecture., London - United Kingdom
In this guest lecture for data science and analytics students at Imperial College London we discussed the emergence of data science as a career in industry. We covered both the historical conditions that created the field, and the onging changes and challenges that people face with being technical detail oriented people working with a wide variety of different business people.
September 20, 2022
Talk, Australian Graduate School of Management - Guest Lecture., UNSW - Sydney Australia
In this guest lecture at the Australian Graduate School of Management we discussed a range of fundamental ideas in analytics projects. All of these ideas relate to framing problems such that they have a greater chance of success.
December 18, 2020
Talk, CSEA 2020, Sydney Australia
Prioritization of machine learning projects requires estimates of both the potential ROI of the business case and the technical difficulty of building a model with the required characteristics. In this work we present a technique for estimating the minimum required performance characteristics of a predictive model given a set of information about how it will be used. This technique will result in robust, objective comparisons between potential projects. The resulting estimates will allow data scientists and managers to evaluate whether a proposed machine learning project is likely to succeed before any modelling needs to be done. The technique has been implemented into the open source application MinViME (Minimum Viable Model Estimator) which can be installed via the PyPI python package management system, or downloaded directly from the GitHub repository.
October 16, 2020
Talk, Selenium Day, 16 Oct 2020, Sydney., Sydney Australia
In this invited talk for the Selenium Day I presented an overview of the technical innovations that have led to modern machine learning successes with language processing. This involved discussing what is special about processing text, the fundamentals of recurrent processing, the development of attention and self-attention models, and finally how this led to the Transformer architecture.
Event Link
November 28, 2019
Talk, Machine Learning & Deep Learning Day, 28 Nov 2019, Sydney., Sydney Australia
In this invited talk for the Machine Learning & Deep Learning Day I presented a ground-up introduction to understanding the fundamentals of Bayesian Machine Learning. I introduced the idea of Bayesian statistics and described the connections between maximum likelihood, maxium a-posteriori and finally the Bayesian goal of a complete estimate of the posterior distribution. I introduced Markov Chain Monte Carlo and the Metropolis Hastings Algorithm. Finally I share some brief cautions on how people from freqeuntist machine learning tend to go wrong either through their expectations or implementations.
Event Link
September 10, 2019
Talk, Chief Data and Analytics Officer Conference, Melbourne, Australia
In this talk I gave a brief overview of the Red Queen effect that has been used in evolutionary biology to describe co-evolution of competing species. I apply this idea to the competition betweenm organisations that are using data science and machine learning to differentiate against their competitors.
May 31, 2018
Talk, Sydney Data Science Meet-Up, Sydney Australia
In this Sydney Data Science Sponsored Meet-Up talk I gave an introduction of the idea of Model Factories, discussing the history of the idea and how it has lead to AutoML systems like DataRobot. Ultimately enabling us to build new forms of automated ML systems.
November 29, 2016
Talk, Sydney Data Science Meet-Up, Sydney Australia
In this Sydney Data Science Meet-Up talk I gave an overview of the history and reasoning that lead to the distinction beetwen Frequentist and Bayesian Inference. I give several worked examples and show the results of simulations designed to answer the question under which circumstances should we prefer one over the other.
Full video of the talk here
December 13, 2010
Talk, BioTec Dresden, Germany., Dresden, Germany
In this BIOTEC Post-Doc Seminar Series talk I gave an overview of the algorithms used to search protein databases to look for functional motifs and active sites that determine biological function and potetnial biomedical applications.
July 01, 2009
Talk, Intelligent Systems for Molecular Biology, Stockholm, Sweden
In this talk I gave an overview of my work with Tim Bailey on the task of exploiting the phylogenetic information in comparative gene sequence alignments to try and improve the prediction of transcription factor binding site prediction.
April 07, 2008
Talk, Institution Presentation for the Institute for Molecular Bioscience, Brisbane, Australia
In this presentation for the Institute for Molecular Bioscience at Queensland University I summarised some of the observations and conclusions that Tim Bailey and I had come to in working on the task of using information from gene sequence alignments to try and improve our ability to identify transcription factor binding sites.
March 30, 2008
Talk, RECOMB: Research in Computational Molecular Biology, Singapore
In this talk I presented the results of the research paper completed with Tim Bailey on the task of exploiting the phylogenetic information in comparative gene sequence alignments to try and improve the prediction of transcription factor binding site prediction.
July 20, 2006
Talk, Congress on Evolutionary Computation, Vancouver, Canada
In this talk I presented the work done with Mikael Boden on the task of designing evolutioning algorithms to create regular expression like motifs to distinguish proteins that carry the PTS2 motif. This is a difficult classification task due to the absence of large data sets and highly variable sequences in the signalling section of the proteins.
July 12, 2006
Talk, ACB Bionformatics Student Symposium, Auckland, New Zealand
In this talk I presented initial work done with Mikael Boden on the task of building machine learning systems to classify proteins that are bound for the nucleus after transcription. It involves the creation of new datasets, and evaluating a range of existing techniques.
February 10, 2006
Talk, AARES: Australasian Agricultural and Resource Economics Society, Sydney, Australia
In this talk I presented the work done with Rodney Beard and Stuart McDonald on developing a multi-agent simualtion system for iterated game theory models of behaviour for coral reef fisheries.
Paper
December 03, 2005
Talk, University of Mexico City, Mexico City, Mexico
Talk given for the students of the complex systems masters course at the University of Mexico City.
November 03, 2005
Talk, School of ITEE, Unviversity of Queensland, Brisbane, Australia
In this talk I summarised the content delivered at the workshop I attended on Evolutionary Game Theory with G-functions. The workshop was given by Tom Vincent at the University of Adelaide. Based on his book Evolutionary Game Theory, Natural Selection, and Darwinian Dynamics
