1st WideHealth Seminar: Nina Reščič: XPrize Pandemic Response Challenge (04/05/2021)

The first public online seminar organized by the EU-funded WideHealth project.
The project aims to conduct research on pervasive eHealth and establish a sustainable network of research and dissemination across Europe.

The seminar will be held on May 4th, 2021 – 16:00 CET
Registration link: http://bit.ly/3voYs5M
Registration is free (zoom link shared before the session to those who register)
Title: XPrize Pandemic Response Challenge
Speaker: Nina Reščič, Jožef Stefan Institute

Short bio:Nina Reščič graduated in Applied Mathematics from the University of Ljubljana, Faculty of Mathematics and Physics in 2012. After working in the industry (Aviation and Aerospace Engineering) she began working at the Jožef Stefan Institute in 2017. She is working as a researcher and is a PhD student at the Jožef Stefan International Postgraduate School. Her research interests involve activity recognition, nutrition monitoring and mathematical modelling. She was a member of SHL Activity Recognition competition winning team in 2018, 2019 and 2020, member of the Cooking recognition challenge competition winning team and a member of the XPRIZE Response Challenge 2nd place winning team JSIvsCovid, where she was responsible for epidemiological modelling. She is a musician, receiving her BA in jazz flute at the Gustav Mahler Private Universität Klagenfurt in 2020.

Abstract:XPrize Foundation organizes high-profile competitions to develop technologies that solve the world’s grand challenges. The competitors of the XPrize Pandemic Response Challenge were tasked with predicting how COVID-19 infections respond to various interventions (such as lockdowns and mask usage), and to propose effective plans of such interventions for different epidemiological situations. In this talk, we will describe the solution developed by the team from the Department of Intelligent Systems at Jožef Stefan Institute, which placed second in the competition. The solution combined a classical epidemiological model with machine learning to predict future infections. Then it used algorithms inspired by biological evolution to find intervention plans with optimal trade-offs between the impact on the infections and the socio-economic cost.
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The EU-funded WideHealth project aims to conduct research on pervasive eHealth and establish a sustainable network of research and dissemination across Europe.

Web: https://widehealth.eu/ 

Twitter: https://twitter.com/EuWidehealth

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