<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Christl Ann Donnelly | Global Pathogen Analysis Platform (GPAP) AI Research</title><link>https://gpap-project.github.io/author/christl-ann-donnelly/</link><atom:link href="https://gpap-project.github.io/author/christl-ann-donnelly/index.xml" rel="self" type="application/rss+xml"/><description>Christl Ann Donnelly</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Oct 2025 00:00:00 +0000</lastBuildDate><image><url>https://gpap-project.github.io/media/logo.svg</url><title>Christl Ann Donnelly</title><link>https://gpap-project.github.io/author/christl-ann-donnelly/</link></image><item><title>Continuous football player tracking from discrete broadcast data</title><link>https://gpap-project.github.io/publication/j-2023-continuous/</link><pubDate>Wed, 01 Oct 2025 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/j-2023-continuous/</guid><description/></item><item><title>Deep learning from videography as a tool for measuring E. coli infection in poultry</title><link>https://gpap-project.github.io/publication/scheidwasser-2025-deep/</link><pubDate>Wed, 01 Oct 2025 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/scheidwasser-2025-deep/</guid><description/></item><item><title>Artificial intelligence for modelling infectious disease epidemics</title><link>https://gpap-project.github.io/publication/kraemer-2025-artificial/</link><pubDate>Wed, 19 Feb 2025 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/kraemer-2025-artificial/</guid><description/></item><item><title>Generalised Bayesian distance-based phylogenetics for the genomics era</title><link>https://gpap-project.github.io/publication/j-2025-generalised/</link><pubDate>Thu, 06 Feb 2025 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/j-2025-generalised/</guid><description/></item><item><title>Bayesian Inference of Phylogenetic Distances: Revisiting the Eigenvalue Approach</title><link>https://gpap-project.github.io/publication/penn-2025-bayesian/</link><pubDate>Thu, 23 Jan 2025 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/penn-2025-bayesian/</guid><description/></item><item><title>Phylo2Vec: A Vector Representation for Binary Trees</title><link>https://gpap-project.github.io/publication/penn-2024-phylo2vec/</link><pubDate>Wed, 26 Jun 2024 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/penn-2024-phylo2vec/</guid><description/></item><item><title>Leaping through Tree Space: Continuous Phylogenetic Inference for Rooted and Unrooted Trees</title><link>https://gpap-project.github.io/publication/penn-2023-leaping/</link><pubDate>Fri, 01 Dec 2023 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/penn-2023-leaping/</guid><description/></item><item><title>Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings</title><link>https://gpap-project.github.io/publication/murphy-2023-effectiveness/</link><pubDate>Wed, 23 Aug 2023 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/murphy-2023-effectiveness/</guid><description/></item><item><title>Intrinsic Randomness in Epidemic Modelling Beyond Statistical Uncertainty</title><link>https://gpap-project.github.io/publication/penn-2022-intrinsic/</link><pubDate>Thu, 01 Jun 2023 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/penn-2022-intrinsic/</guid><description/></item><item><title>Global, regional, and national minimum estimates of children affected by COVID-19-associated orphanhood and caregiver death, by age and family circumstance up to Oct 31, 2021: an updated modelling study</title><link>https://gpap-project.github.io/publication/unwin-2022-global/</link><pubDate>Thu, 24 Feb 2022 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/unwin-2022-global/</guid><description/></item><item><title>Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling</title><link>https://gpap-project.github.io/publication/mishra-2021-comparing/</link><pubDate>Wed, 11 Aug 2021 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/mishra-2021-comparing/</guid><description/></item><item><title>Global minimum estimates of children affected by COVID-19-associated orphanhood and deaths of caregivers: a modelling study</title><link>https://gpap-project.github.io/publication/hillis-2021-global/</link><pubDate>Thu, 01 Jul 2021 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/hillis-2021-global/</guid><description/></item><item><title>Leveraging 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