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title: Givanna Putri - Profile | ||
permalink: /givanna-putri/ | ||
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<a href="#"> | ||
<img src="https://avatars.githubusercontent.com/u/5366317?s=460&u=ac0322d285310461de6ad2a4b938252b6ea2d948&v=4" alt="icon" width="180" align="right" style="padding-left: 10px; padding-right: 0px; padding-top: 10px; padding-bottom: 10px"> | ||
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Givanna Putri is a post-doctoral researcher at Walter and Eliza Hall Institute of Medical Research (WEHI). | ||
She is a computer scientist, and has extensive experience in developing and applying machine learning (ML) algorithms to analyse multi-omics data. | ||
Her work focuses heavily on developing and applying ML algorithms to uncover biological insights from multi-omics datasets, including cytometry, scRNAseq, and spatial transcriptomics. | ||
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Givanna was awarded her PhD in Computer Science in 2021 from the University of Sydney. | ||
During her PhD, she developed algorithms to cluster and track cellular populations development in time-course high dimensional cytometry data. | ||
This included the TrackSOM algorithm which was used to profile [SARS-CoV-2/COVID-19](https://immunedynamics.io/research/disease) patients, and the [ChronoClust](https://github.com/ghar1821/Chronoclust) algorithm which publication on the Knowledge Based System journal won the Dolby scientific paper competition in 2019. | ||
She also developed a novel benchmarking methodology [ParetoBench](https://github.com/ghar1821/ParetoBench) which uses the Pareto Front framework to fairly compare the performances of clustering algorithms using several performance metrics. | ||
Her PhD research was funded by The Australian Government Research Training Program Scholarship and The University of Sydney Alumni Scholarship. | ||
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In her current role as a postdoc at WEHI, she developed an R package [SuperCellCyto](https://phipsonlab.github.io/SuperCellCyto/) to reduce the size of cytometry data while minimising the loss in biological heterogeneity. | ||
She was awarded a travel award by the CASS foundation to present SuperCellCyto at the recent CYTO 2024 conference. | ||
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**Sites and academic profiles** | ||
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<img src="https://raw.githubusercontent.com/tomashhurst/tomashhurst.github.io/2a9877aba13f6f7b46b11728a68d7047debb0f36/custom_SVG/Google_Scholar_logo.svg" alt="Logo" width="25"> [Google Scholar](http://scholar.google.com/citations?user=S-sNLPIAAAAJ&hl=en) <br/> | ||
<img src="https://raw.githubusercontent.com/tomashhurst/tomashhurst.github.io/2a9877aba13f6f7b46b11728a68d7047debb0f36/custom_SVG/GithubSVG.svg" alt="Github logo" width="25"> [Github](https://github.com/ghar1821) <br/> |