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What if you could look at the source code behind any online visualization, understand how it works, run it to check the results using the latest data and modify the parameters to explore different aspects that you are interested in?
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May Yong is a Research Engineer at the Alan Turing Institute. She works across multiple research domains, collaborating with scientists to turn interesting ideas into useable software. Past projects include machine learning on neonatal intensive care data, creation of data standards for antibody therapy experiments and amalgamation of heterogeneous multiple sclerosis data. May is interested in data interpretation, specifically in ways of providing information in perspective in order to see the bigger picture. She is building tools to minimize data ambiguity so that data is interpreted and used the way the data collectors intended.