Dr. Givanna Putri is a data scientist with keen interest in single cell omics and computational biology.
During her PhD at the University of Sydney, she used temporal clustering and tracking algorithms to reveal the development of immune response over time. She developed machine learning techniques to explicitly cluster and track cellular populations development in time-course high dimensional cytometry data. This included the TrackSOM algorithm which was recently used to profile SARS-CoV-2/COVID-19 patients, and the ChronoClust algorithm which publication on the Knowledge Based System journal won the Dolby scientific paper competition in 2019. In 2019, she was awarded The Student Travel Award from the International Society for Advancement of Cytometry (ISAC) and The Postgraduate Research Support Scheme from The University of Sydney to present ChronoClust at the 34th Congress of the International Society for Advancement of Cytometry (CYTO) conference. Additionally, she also developed a novel benchmarking methodology 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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