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X-WR-CALDESC:Events for Australian Data Science
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DTSTART:20200101T000000
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DTSTART;TZID=Australia/Brisbane:20241203T170000
DTEND;TZID=Australia/Brisbane:20241203T181500
DTSTAMP:20241114T202822Z
CREATED:20241114T202118Z
LAST-MODIFIED:20241114T202822Z
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SUMMARY:AMSI BioInfoSummer 2024 Public Lecture: Preparing for the age of genomic medicine
DESCRIPTION:Join us for an engaging public lecture by Professor Daniel MacArthur\, a leader in the field of genomic medicine\, as part of the AMSI BioInfoSummer 2024 program. Suitable for a general audience\, this talk is accessible to Year 10 students and above. Light refreshments will be served from 5pm. \nWhether you’re a researcher\, student\, or simply interested in the latest scientific advancements\, this hybrid event is not to be missed! \nWe are currently living through an unprecedented transformation of medicine\, driven by rapid technological change across multiple fields. Three fields have been particularly impactful: \n\ngenomics\, which allows us to understand the human at unprecedented resolution;\ndata science\, which uses tools including AI to make sense of the vast amounts of data emerging from genomics and other measurements\, and to make predictions about current and future disease risk; and\ntherapeutics\, which allows us to make precise molecular changes to cure or prevent disease.\n\nThe intersection of these three fields\, genomic medicine\, has already profoundly changed the diagnosis of genetic diseases and the treatment of cancer\, and over the next decade will reshape many aspects of healthcare. \nProfessor Daniel MacArthur will give an accessible summary of what the new field of genomic medicine will mean for the future of health\, and what Australia needs to do to ensure that all of our citizens can benefit from these powerful new technologies. \n\nFree and open to the public (Registration required)\nLight refreshments from 5pm AEDT for those attending in person
URL:https://australiandatascience.net/event/amsi-bioinfosummer-2024-public-lecture-preparing-for-the-age-of-genomic-medicine/
LOCATION:The University of Melbourne\, Parkville\, Victoria\, 3010\, Australia
CATEGORIES:Event,Seminar
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BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20230816T113000
DTEND;TZID=Australia/Brisbane:20230816T130000
DTSTAMP:20230724T032541Z
CREATED:20230724T032541Z
LAST-MODIFIED:20230724T032541Z
UID:4854-1692185400-1692190800@australiandatascience.net
SUMMARY:University of Wollongong 2023 Data Science & Statistics Lecture: Professor Antonietta Mira
DESCRIPTION:The School of Mathematics and Applied Statistics (SMAS) at the University of Wollongong is hosting the 2023 Data Science and Statistics (DSS) Lecture \nLecturer: Antonietta Mira  \n\nProfessor of Statistics and Director of the Data Science Lab\, Università della Svizzera Italiana\, Lugano\, Switzerland\nProfessor of Statistics\, Insubria University\, Como\, Italy\n\nTitle: Data science for public health: Risk mapping of Out of Hospital Cardiac Arrest and the optimal deployment of defibrillators \n(Further details about this and past DSS Lectures can be found at https://uow.info/smas-ssl) \nDate: Wednesday\, 16 August 2023 \nTime: 11:30am in-person-only lecture\, with refreshments to follow\nVenue: Building 6\, Room 210\, University of Wollongong \nAbstract: Out of Hospital Cardiac Arrest (OHCA) is a major public-health problem that affects approximately 1:1000 people in developed countries. This lecture describes my collaborative peer-reviewed research with cardiologists in Switzerland since 2018\, to map and forecast OHCA risk\, and to use this to optimise Automatic External Defibrillator (AED) deployment in Canton Ticino\, Switzerland. Flexible location models were found to increase overall OHCA coverage and decrease the distance to nearby AEDs\, so saving lives and at the same time reducing public-health expenditure. For every minute lost in response time\, the AED success rate decreases by 7-10%. Geospatial models of OHCA and AED accessibility with uncertainty quantified\, were used to identify communities with the greatest gap between demand and supply for allocating AEDs\, which were then used to evaluate models for precise AED-location deployment. These were further used to evaluate strategies for deployment of Lay First Responders (LFRs) in relation to the OHCA and AED locations. A Bayesian spatio-temporal model with a dynamic temporal component was used to predict future OHCAs. Model-based risk maps adjusted for demographic covariates were used to explain and forecast the spatial distribution of OHCAs in Canton Ticino. The lecture will conclude with new work on using neural networks in the Bayesian spatio-temporal model\, which allows current and future detection of high-risk areas of OHCA with uncertainty quantified. \nThe lecture and refreshments that follow are open to all. For space availability and catering purposes\, please click here to register \nAntonietta has a strong commitment to STEM in Switzerland and Italy. She has won awards for excellence in both research and teaching. She has been involved in public engagement (such as EXPO Milano 2015) and has delivered public lectures (such as Festival of the Swiss Academy of Sciences 200 Year Anniversary). She is often interviewed in the media on topics related to Data Science and Big Data\, and she has created an exhibit\, Numbed by Numbers!\, which is a 3D tour between Digits (maths)\, Dice (probability)\, and Data (stats)\, aimed at children aged from 6 – 18. Antonietta is also winner of the 2022 G. Dosi national prize for popularising science for STEM students\, with publication of her book\, The Data Pandemic. Here is the Vaccine (2020\, Mondadori). In her free time\, she is a practicing magician with a special interest in mathematical magic\, which is presented in her book\, Matemagica (2012\, Aboca).
URL:https://australiandatascience.net/event/uow-data-science-stats-lecture/
LOCATION:University of Wollongong\, Northfields Ave\, Wollongong\, NSW\, 2522\, Australia
CATEGORIES:Event,Seminar
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BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20230803T160000
DTEND;TZID=Australia/Brisbane:20230803T170000
DTSTAMP:20230727T234952Z
CREATED:20230727T234849Z
LAST-MODIFIED:20230727T234952Z
UID:4882-1691078400-1691082000@australiandatascience.net
SUMMARY:Doing an Ultrasound Scan of the Sun with AI
DESCRIPTION:This lecture is part of the Monash Conversations on AI and Data Science series\, which focuses on the impactful AI/data science research being done by Monash University researchers. The series is run by the Monash Data Futures Institute. \nSpeaker: Dr Alina Donea\, School of Mathematics\, Monash University \nAbstract \nIn the scenario of a strong solar coronal mass ejection\, we would only receive a mere 30-minute warning before an immense solar event\, which could have devastating consequences for our satellite technology and society. Regrettably\, this limited timeframe does not allow for the activation of emergency protocols or the implementation of practical measures. \nTo enhance our preparedness and minimize the potential impact\, it is imperative to strive for significantly longer warning periods. It is essential that we lend our ears to the Sun’s messages. In this session\, Dr Alina Donea will demonstrate the utilization of solar images (generated by AI and a deep neural network\, referring to conditional Generative Adversarial Network (sGAN)) to enhance predictions of solar activity from the side of the Sun that is not visible\, leading to significant advancements in space weather forecasting. \nREGISTER: https://www.eventbrite.com.au/e/doing-an-ultrasound-scan-of-the-sun-with-ai-tickets-681265502457
URL:https://australiandatascience.net/event/doing-an-ultrasound-scan-of-the-sun-with-ai/
LOCATION:Monash University\, 27 Chancellors Walk\, Clayton\, Victoria\, 3168\, Australia
CATEGORIES:Event,Seminar
ORGANIZER;CN="Monash Data Futures Institute":MAILTO:datafutures@monash.edu
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BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20230502T160000
DTEND;TZID=Australia/Brisbane:20230502T180000
DTSTAMP:20230426T233131Z
CREATED:20230426T233131Z
LAST-MODIFIED:20230426T233131Z
UID:4721-1683043200-1683050400@australiandatascience.net
SUMMARY:DARE Seminar: How remote sensing and big data are changing our view of the coast
DESCRIPTION:Join the ARC DARE Centre for in-person seminar at UNSW\, followed by networking and nibbles! \nBig Data\, Big Dreams: How Remote Sensing and Big Data are Changing Our View of the Coast \nCoastal science and engineering is a relatively young field and historically has lacked sufficient data to be able to understand how this complex earth system works at both large temporal and spatial scales. Yet\, with a large portion of the world’s population living within 50km of the coastline\, we are being asked to provide advice and understanding on how coastlines will change into the future. \nThis talk will first provide a bit of context on just how data sparse our field is\, and how we are now engaging and rapidly trying to catch up to our hydrological colleagues. We will discuss how we are applying basic machine learning techniques to improve our ability to predict coastal change at a variety of timescales of interest to the public\, from individual storms\, to where the coast might be by 2100. \nThe talk will be aimed at a broadscale (non-expert) audience\, discussing the challenges associated with trying to model the coastline\, and the techniques we have so far applied\, and we’d love thoughts and ideas from the audience as well. \nSpeakers: Associate Professor Kristen Splinter and Patrick ‘Kit’ Calcraft \nKristen is an ARC Future Fellow and Deputy Director of the Water Research Laboratory at UNSW Sydney. Her work encompasses a wide range of coastal topics examining sandy beach evolution from storms to multiple decades. She has developed a number of behavioural type numerical models to predict sandbar and shoreline evolution and the focus of her Fellowship will be to develop regional scale models for long-term shoreline prediction\, along the embayed coastlines of NSW. She’s been dipping her toes into machine learning since about 2015 but her students are the real experts. \nKit is a DARE affiliated PhD candidate in his first year working on machine learning methods for shoreline prediction\, including bridging the gap between physics and ML. He is co-supervised by Associate Professor Kristen Splinter\, Dr Josh Simmons (DARE) and Professor Lucy Marshall. He will present an overview of what he’s been up to in year 1 of his PhD.
URL:https://australiandatascience.net/event/dare-seminar-how-remote-sensing-and-big-data-are-changing-our-view-of-the-coast/
LOCATION:UNSW School of Civil and Environmental Engineering\, Oval Lane\, Room 501\, Kensington\, NSW\, 2052\, Australia
CATEGORIES:Event,Seminar
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BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210714T100000
DTEND;TZID=Australia/Brisbane:20210719T104500
DTSTAMP:20211026T024210Z
CREATED:20210709T023716Z
LAST-MODIFIED:20211026T024210Z
UID:2221-1626256800-1626691500@australiandatascience.net
SUMMARY:AI4Pandemics Talk #1: Chris Rackauckas\, MIT
DESCRIPTION:The first AI4PAN seminar speaker will be Chris Rackauckas (MIT) \nYouTube Recording \nTitle: \nLearning Epidemic Models That Extrapolate. \nAbstract: \nModern techniques of machine learning are uncanny in their ability to automatically learn predictive models directly from data. However\, they do not tend to work beyond their original training dataset. Mechanistic models utilize characteristics of the problem to ensure accurate qualitative extrapolation but can lack in predictive power. How can we build techniques which integrate the best of both approaches? In this talk we will discuss the body of work around universal differential equations\, a technique which mixes traditional differential equation modeling with machine learning for accurate extrapolation from small data. We will showcase how incorporating different variations of the technique\, such as Bayesian symbolic regression and optimizing the choice of architectures\, can lead to the recovery of predictive epidemic models in a robust way. The numerical difficulties of learning potentially stiff and chaotic models will highlight how most of the adjoint techniques used throughout machine learning are inappropriate for learning scientific models\, and techniques which mitigate these numerical ills will be demonstrated. We end by showing how these improved stability techniques have been automated and optimized by the software of the SciML organization\, allowing practitioners to quickly scale these techniques to real-world applications. \n\n 
URL:https://australiandatascience.net/event/ai4pan-seminar-series-with-chris-rackauckas-mit/
LOCATION:Zoom
CATEGORIES:Seminar
ORGANIZER;CN="Hamid Khataee":MAILTO:h.khataee@uq.edu.au
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