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X-WR-CALDESC:Events for Australian Data Science Network
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DTSTART:20200101T000000
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BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210901T120000
DTEND;TZID=Australia/Brisbane:20210901T130000
DTSTAMP:20210812T223224Z
CREATED:20210812T221534Z
LAST-MODIFIED:20210812T223224Z
UID:2400-1630497600-1630501200@australiandatascience.net
SUMMARY:ACEMS Virtual Public Lecture - The Origami of Data Science
DESCRIPTION:ACEMS Virtual Public Lecture – The Origami of Data Science\nMany of us know about origami – where a flat square of paper is folded into a sculpture that inspires appreciation and imagination. In the same way\, we might think about origami (or perhaps more accurately ‘oridēta’) in the context of data science\, whereby a data analysis method or computational algorithm is folded into a software product that inspires interpretation and implementation.\nIn this public lecture\, Professor Mengersen will discuss our attempts at the origami of data science. These include folding new methods and computational approaches into products such as an online atlas of cancer (atlas.cancer.org.au)\, a virtual Great Barrier Reef (virtualreef.org.au)\, an ethical social discourse platform (betterbeliefs.com.au)\, and a personalised learning program (qutschoolofmaths.shinyapps.io/uncoursetoolapp/). \nRegister now \nAlthough the foundations are statistical\, our sculptures require a broad team of experts from the mathematical\, statistical\, and computer sciences\, and they need to be appreciated\, interpreted\, imagined\, and implemented by domain experts and users. \nThis lecture is 45-minute presentation followed by Q & A. \nThis lecture is part of the ACEMS Virtual Public Lecture Series – click here to view other lectures in the series. \nAbout the speaker\nKerrie Mengersen is a Distinguished Professor of Statistics at QUT\, a Deputy Director of ACEMS\, and a Director of the QUT Centre for Data Science. \nKerrie is an elected Fellow of the Australian Academy of Science and the Academy of Social Sciences\, as well as the Queensland Academy of the Arts and Sciences. Her research focuses on Bayesian models and computational methods\, and their application to challenging problems in health\, the environment\, and industry.
URL:https://australiandatascience.net/event/acems-virtual-public-lecture-the-origami-of-data-science/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210908T100000
DTEND;TZID=Australia/Brisbane:20210908T104500
DTSTAMP:20211012T024454Z
CREATED:20211012T024406Z
LAST-MODIFIED:20211012T024454Z
UID:2722-1631095200-1631097900@australiandatascience.net
SUMMARY:AI4Pandemics Talk #5: Peter Frazier\, Cornell University
DESCRIPTION:Title: Fighting COVID-19 at Cornell University \nYouTube Recording \n\n\nAbstract\nUniversities around the world faced a challenging decision during the summer of 2020: whether to reopen for in-person instruction despite the pandemic and how to protect campus populations if they did. Operations research and data science were a fundamental part of these decisions at Cornell University in the USA. First\, models developed by Cornell’s COVID-19 Mathematical Modeling Team were used to design the testing interventions that are a cornerstone of Cornell’s COVID-19 control strategy: targeted asymptomatic screening that tests all undergraduates twice per week and an adaptive testing program that goes beyond traditional contact tracing to test the full social circle of positive cases. Second\, these same models were the basis for Cornell’s decision to reopen for a fall semester with in-person instruction. They showed that reopening with aggressive mandatory testing was surprisingly less risky than virtual instruction. Data suggested that thousands of students would return to the area whether in-person instruction was offered or not\, and a weaker ability to enforce mandatory testing for these students risked being unable to control clusters in that population. Reopening with asymptomatic screening was successful\, with only 0.5% of students\, staff and faculty infected over the semester. This talk will share insights from this experience and explain practical tools that supported this work.
URL:https://australiandatascience.net/event/ai4pandemics-talk-5-peter-frazier-cornell-university/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210910T130000
DTEND;TZID=Australia/Brisbane:20210910T150000
DTSTAMP:20210909T004715Z
CREATED:20210902T230619Z
LAST-MODIFIED:20210909T004715Z
UID:2598-1631278800-1631286000@australiandatascience.net
SUMMARY:ADSN Workshop: Synthetic Data
DESCRIPTION:ADSN Workshop: Synthetic Data\nWe’ve had recent interest from industry about simulating realistic data from complex systems. There are many situations where sensitivities of real data make synthetic data safer to handle. We (QUT) would like to convene a workshop to engage researchers with capabilities and interests in synthetic data and open up possibilities for further connection and collaboration. \nPlease contact us if you would like to receive an invitation to this online workshop \n\n\n\n\n\n\n1:00PM – 1:10PM\nWelcome & overview of workshop\nPurpose of workshop and quick introductions\nDistinguish Professor Kerrie Mengersen \nQUT Centre for Data Science\n\n\n1:10PM – 1:20PM\nOverview of synthetic data generation \nIn this overview\, Connor will provide a short literature review and summary of main features when it comes to synthetic data generation.\nConor Hassan\nQUT Centre for Data Science\n\n\n1:20PM – 1:35PM\nGRATIS: GeneRAting TIme Series with diverse and controllable characteristics \nDescription: Synthetic time series are useful for benchmarking and testing methods for forecasting\, clustering\, classification and other tasks. I will discuss an approach to this where we can generate time series with diverse and controllable characteristics using mixture autoregressive (MAR) models. This can be done with the gratis package for R.\nProfessor Rob Hyndman\nMonash University \n\n\n1:35PM – 1:50PM\nDeep Learning Techniques for Dealing with Lack of Data\nIn this talk\, we will present progressive transfer learning methods to deal the data problems such as the lack of labelled data and data shifts. We present an alternative approach to complement the datasets available.\nAssociate Professor Richi Nayak\nQUT Centre for Data Science\n\n\n\n Opportunity for Spotlight Talks \n\n\n\n2:00PM – 2:15PM\nSynthetic data generation using moment-based density estimation \nIn this talk\, we introduce a new synthetic data generation method based on estimated multivariate density function\, which is constructed from the sample moments information of the original data.\nBradley Wakefield\nUniversity of Wollongong (NIASRA) \n\n\n2:15PM – 2:30 PM\nGenerating artificial video data to train machine learning algorithms\nThis talk will present early work on the creation of synthetic video data using motion capture and CGI for use in training of human action recognition models.\nAnthony Paproki\nQUT Centre for Data Science\n\n\n\n Opportunity for discussion\nLearnings & where to from here?
URL:https://australiandatascience.net/event/adsn-workshop-synthetic-data/
CATEGORIES:Online workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210915T120000
DTEND;TZID=Australia/Brisbane:20210915T130000
DTSTAMP:20210903T051044Z
CREATED:20210902T231200Z
LAST-MODIFIED:20210903T051044Z
UID:2600-1631707200-1631710800@australiandatascience.net
SUMMARY:ACEMS Virtual Public Lecture - Hypocrisy ++
DESCRIPTION:ACEMS Virtual Public Lecture – Hypocrisy ++\nThere are two popular\, but competing\, philosophical theories which attempt to answer this question\, usually referred to as the ‘subjective’ and the ‘frequency’ approaches. These theories are often claimed to form the foundations\, respectively\, of the Bayesian and frequentist interpretations of statistics. In this public lecture\, Professor Burdzy will explain why this is not actually the case\, and will outline logical contradictions with both these philosophical theories. \nRegister now
URL:https://australiandatascience.net/event/acems-virtual-public-lecture-hypocrisy/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210917T120000
DTEND;TZID=Australia/Brisbane:20210917T130000
DTSTAMP:20210916T002825Z
CREATED:20210916T002759Z
LAST-MODIFIED:20210916T002825Z
UID:2660-1631880000-1631883600@australiandatascience.net
SUMMARY:QUT Data Science in the News: Monitoring the nation's pulse
DESCRIPTION:Monitoring the nation’s pulse: The what\, who\, how and why of the Census\nIn this Data Science in the News webinar\, we will explore the important role data science plays in the Australian Census. \nRegister now \nModerator:\nProfessor David Lovell – Deputy Director\, QUT Centre for Data Science \nPanellists:\nMr Mark Harding – Program Manager\, 2021 Census Data Operations \nMs Caroline Deans – Director\, 2021 Census Dissemination \nDr Gentry White – Associate Professor in Data Science and Government Statistics Chair \nDr Aiden Price – Research Associate School of Mathematical Sciences QUT\, Project Manager AusEnHealth \n  \nMore about the Panel Session Topics\nWhat’s new in the 2021 Census – the “what” – Mark Harding \nThe 2021 Census design has been guided by its overarching objectives: smooth-running Census\, garners strong support from the community\, and produces high quality data. Mark Harding will talk through what is new about the 2021 Census\, and in particular how the ABS has adopted a user-centred design approach to delivering the Census. This year the ABS has faced the added challenge of running a Census during the pandemic. Mark will describe how the ABS has responded to COVID-19 and the impacts on Census field operations. \nValue of the Census Data – the “who\, how and why” – Caroline Deans \nCensus data is used to inform important decisions about transport\, schools\, health care\, infrastructure and business. While many people are aware of how the Government uses the data\, the Census is also heavily relied on by community groups and small businesses to improve the lives of individuals. Caroline Deans will cover some case study examples on the varying uses of Census data. \nCaroline will also talk through what happens to the information collected\, from when the data is collected through to when it is transformed into meaningful statistics. The 2021 Census is being conducted at a most interesting time and the data from this Census will be very important to show how the pandemic is affecting our economy and society. \nPartners in Data Science – Dr Gentry White \nDr. White will speak briefly on the unique partnership between QUT\, the CDS and the ABS outlining their current program of research and plans for the future. \nAusEnHealth Project: Climate and Air Quality Vulnerability Index Development – Dr Aiden Price \nThe changing nature of many hazards\, coupled with growing and ageing populations and infrastructure in exposed areas is leading to increased vulnerability across Australia and internationally. AusEnHealth is a multi-agency funded project with the aim to provide tools to support the assessment of population vulnerability through an environmental health lens. This has been achieved by combining air quality and climate data with demographics data\, the latter being comprised almost entirely of Census data from the Australian Bureau of Statistics. \n  \nMore about the Moderator and Panellists\nMr Mark Harding’s career at the ABS spans over two decades\, commencing in 2000. During this time\, Mr Harding has been involved in a number of Censuses and also led the ABS Population Survey Operations. He is currently the Program Manager for 2021 Census Data Operations and is responsible for the end-to-end processes from after the data is collected through to when the data is released. \nMr Harding is based in Sydney where he is currently working from home in his third month of lockdown with his wife and two children. \nMs Caroline Deans commenced her career at the ABS in 2005\, although has been interested in statistics and their importance in decision making well before then. Ms Deans has a wealth of knowledge about the Census\, having worked on the last three Censuses. She was responsible for managing the South Australia Census count in 2011\, the Queensland count in 2016\, and is now responsible for releasing the data for the 2021 Census. \nMs Deans grew up in Adelaide and moved to Brisbane in 2016 where she currently resides. \nDr. Gentry White is the current Associate Professor in Data Science and the Australia Bureau of Statistics Co-Chair in the QUT Centre for Data Science. Dr. White has been at QUT since 2013 and prior was a Research Fellow at the ARC Center for Excellence in Policing and Security and the Institute for Social Science Research at The University of Queensland since 2009. \nDr Aiden Price is a research associate in the Centre for Data Science\, working as a project manager on the AusEnHealth Project: a national environmental health strategic planning digital twin. Aiden’s research is currently focused on spatial and temporal analyses of environmental and population health data\, identifying the impact of bushfires on human health\, and conservation-focused work through the lens of aesthetics in the Antarctic Peninsula. \nProfessor David Lovell is a Professor in the QUT School of Computer Science\, Deputy Director of QUT’s Centre for Data Science\, and leader of the Centre’s Data-Focused Decision-Making Program. David’s research interests lie at the intersection of humanity\, science and technology\, particularly data science. We humans are the ones who stand to benefit (or suffer) from systems that use data to make or inform decisions that affect our lives. David wants to ensure that science and technology are developed\, designed and delivered with this in mind so that our world is better as a result.
URL:https://australiandatascience.net/event/qut-data-science-in-the-news-monitoring-the-nations-pulse/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210921
DTEND;VALUE=DATE:20210924
DTSTAMP:20210903T045102Z
CREATED:20210903T044703Z
LAST-MODIFIED:20210903T045102Z
UID:2604-1632182400-1632441599@australiandatascience.net
SUMMARY:Data-driven queueing challenges
DESCRIPTION:Data-driven queueing challenges\nThe increasing availability of data in the operation of large computer networks and the management of human service systems creates new problems in queueing theory. To respond\, ACEMS and NETWORKS are co-sponsoring an on-line workshop on `Data-driven queueing challenges’\, in association with The Alan Turing Institute. \nThe workshop brings together researchers from statistics\, stochastic modelling and data science to consider research directions in modelling and controlling queues\, and in dealing with parameter uncertainty\, when there is access to operational data. \nThe program contains 16 speakers and 2 panel discussions. \nRegister now
URL:https://australiandatascience.net/event/data-driven-queueing-challenges/
CATEGORIES:Online workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210921T110000
DTEND;TZID=Australia/Brisbane:20210921T120000
DTSTAMP:20210916T020334Z
CREATED:20210916T020333Z
LAST-MODIFIED:20210916T020334Z
UID:2666-1632222000-1632225600@australiandatascience.net
SUMMARY:Distinguished Visitor Seminar - Assistant Professor Linda Tan
DESCRIPTION:Distinguished Visitor Seminar – Assistant Professor Linda Tan\nThe Centre for Data Science Distinguished Visitor Seminar Series has been created to provide a platform for our esteemed colleagues from across the nation and the globe to share their research\, knowledge and expertise in the field of data science. \nRegister now \nThe next seminar will be presented by Linda S. L. Tan. Linda is an Assistant Professor in the Department of Statistics and Data Science at the National University of Singapore. Her research interests are in variational approximation methods and improving the accuracy and rate of convergence of Bayesian computational algorithms. In this seminar\, Linda will present: \nEfficient data augmentation techniques for state space models\nWe propose a data augmentation scheme for improving the rate of convergence of the EM algorithm in estimating Gaussian state space models. The scheme considers a linear transformation of the latent states in which two working parameters are introduced for rescaling and recentering. We derive optimal values of the working parameters by minimizing the fraction of missing information and study their large sample properties and dependence on the persistence and signal-to-noise ratio. An alternating expectation-conditional maximization (AECM) algorithm is designed to take advantage of the proposed scheme and shown to be a more attractive alternative to the centered parametrization (CP) or noncentered parametrization (NCP). We extend earlier results to Bayesian Markov chain Monte Carlo (MCMC) algorithms for non-Gaussian state space models\, focusing on the stochastic volatility and stochastic conditional duration models. A block-specific reparametrization (BSR) strategy for multi-block MCMC samplers is proposed which enables the EM data augmentation scheme to be applied to non-Gaussian models via a mixture of normals approximation. Applications on simulated data and benchmark real data sets indicate that the BSR strategy can yield improvements in simulation efficiency compared with the CP or NCP\, and sometimes even over ASIS (which interweaves the CP and NCP). \n*** This will be an online event only. A Zoom link will be emailed to registrants on the day of the event. ***
URL:https://australiandatascience.net/event/distinguished-visitor-seminar-assistant-professor-linda-tan/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210924T120000
DTEND;TZID=Australia/Brisbane:20210924T133000
DTSTAMP:20210917T054829Z
CREATED:20210917T054829Z
LAST-MODIFIED:20210917T054829Z
UID:2691-1632484800-1632490200@australiandatascience.net
SUMMARY:ADSN Centre Spotlight #5
DESCRIPTION:ADSN Centre Spotlight #5\nJoin us for our fifth ADSN Centre Spotlight as we hear from four partners about what’s happening in their organisation when it comes to data science. \n\nDonna Burnett\, School Manager\, La Trobe Business School\, Centre for Data Analytics and Cognition (CDAC)\nProfessor Ravinesh Deo – The University of Southern Queensland (USQ)’s Advanced Data Analytics Research Group\nProfessor Zahid Islam\, Director\, Charles Sturt Data Science Research Unit (DSRU)\nDistinguished Professor Matt Wand\, Group Leader\, UTS Statistics and Data Science Group\n\nPartner and communications contacts have been sent a Zoom calendar invitation\, but if you would like to join us\, please send us an email.
URL:https://australiandatascience.net/event/adsn-centre-spotlight-5/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210930T163000
DTEND;TZID=Australia/Brisbane:20210930T180000
DTSTAMP:20210909T065257Z
CREATED:20210909T065257Z
LAST-MODIFIED:20210909T065257Z
UID:2636-1633019400-1633024800@australiandatascience.net
SUMMARY:EC Bayes Seminar: Francesca Crucinio\, University of Warwick - A particle method for Fredholm Integral Equations of the First Kind
DESCRIPTION:EC Bayes Seminar: Francesca Crucinio\, University of Warwick – A particle method for Fredholm Integral Equations of the First Kind\nWe present a novel method for the solution of Fredholm integral equations of the first kind\, a set of ill-posed inverse problems which model\, among others\, reconstruction of images from distorted noisy observations and indirect density estimation. This novel method is based upon a non-standard sequential Monte Carlo (SMC) algorithm which provides a stochastic discretisation of a smoothed expectation maximisation scheme (EMS) usually implemented under the assumption of piecewise constant solutions. The stochastic discretisation provided by SMC does not assume piecewise constant signals and results in smooth approximate solutions. We analyse the theoretical properties of the EMS iteration\, showing existence of a fixed point\, and of the corresponding SMC algorithms. We compare the novel method with alternatives using a simulation study and present results for realistic systems\, including motion deblurring and reconstruction of cross-section images of the brain from positron emission tomography. \nRegister now
URL:https://australiandatascience.net/event/ec-bayes-seminar-francesca-crucinio-university-of-warwick-a-particle-method-for-fredholm-integral-equations-of-the-first-kind/
CATEGORIES:Event,Webinar
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