Joshua Vogelstein receives NSF CAREER Award

/ February 20, 2020

Joshua T. Vogelstein, assistant professor in the Department of Biomedical Engineering and a member of the Institute for Computational Medicine, Center for Imaging Science, and the Kavli Neuroscience Discovery Institute, is a recipient of the National Science Foundation’s Early CAREER Award, which recognizes early stage scholars with high levels of promise

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JHU launches new institute dedicated to supporting the ‘fourth industrial revolution’ of data science

/ November 18, 2019

TRIPODS Institute brings together mathematicians, statisticians, theoretical computer scientists, and engineers to further the next generation of data analysis Lisa Ercolano / Published Nov 18, 2019 Using a $1.5 million, three-year grant from the National Science Foundation, a multi-disciplinary team of researchers at the Johns Hopkins Mathematical Institute of Data Science has created a new institute

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Vladimir Braverman received a Best Paper Award at FAST ’19

/ February 28, 2019

Load balancing is critical for distributed storage to meet strict service-level objectives (SLOs). It has been shown that a fast cache can guarantee load balancing for a clustered storage system. However, when the system scales out to multiple clusters, the fast cache itself would become the bottleneck. Traditional mechanisms like cache

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Carey Priebe’s paper “On a `Two Truths’ Phenomenon in Spectral Graph Clustering” has been accepted for publication at PNAS

/ February 11, 2019

Clustering is concerned with coherently grouping observations without any explicit concept of true groupings. Spectral graph clustering – clustering the vertices of a graph based on their spectral embedding – is commonly approached via K-means (or, more generally, Gaussian mixture model) clustering composed with either Laplacian or Adjacency spectral embedding (LSE

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QnAs with Donald Geman

/ May 8, 2018

With the proliferation of “omics” technologies, personalized medicine—which tailors treatment to an individual’s genomic profile—promised a revolution in care. That revolution, says applied mathematician Donald Geman, has been slow to arrive. Geman has spent nearly four decades devising statistical methods for a variety of applications. He recently teamed up with an

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