Mary Scott
Data Scientist
Mary joined IDDO in January 2025 as a Data Scientist to perform large-scale individual patient data meta-analyses, methods development, and statistical modelling to optimise the treatment of infectious disease. Her research will focus on improving the diagnosis and triage of patients with suspected severe malaria.
In February 2024, Mary defended her PhD thesis, titled “Differentially Private Methods for Releasing Aggregated Multi-Dimensional Messages”. She holds a Bachelor of Science in Mathematics from the University of Warwick.
Recent publications
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Distributed, communication-efficient, and differentially private
estimation of KL divergence
Scott M. et al, (2024)
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Towards Robust Federated Analytics via Differentially Private
Measurements of Statistical Heterogeneity
Scott M. et al, (2024)
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Aggregation and Transformation of Vector-Valued Messages in the Shuffle
Model of Differential Privacy
Scott M. et al, (2022)
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Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy
Scott M. et al, (2022), IEEE Transactions on Information Forensics and Security, 17, 612 - 627
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Applying the Shuffle Model of Differential Privacy to Vector Aggregation
Scott M. et al, (2021)