Raman Arora, assistant professor in the Department of Computer Science, is a recipient of the National Science Foundation’s Early CAREER Award, which recognizes early stage scholars with high levels of promise and excellence. Raman’s research focuses on algorithmic and computational aspects of machine learning. Raman’s five-year CAREER award will support his
Mauro Maggioni: 2020 Simons Fellows in Mathematics
Bloomberg Distinguished Professor Mauro Maggioni, Professor of Mathematics, Applied Mathematics and Statistics, and a member of the Mathematical Institute for Data Science (MINDS), has been elected as a 2020 Simons Fellow in Mathematics. The Simons Foundation congratulates the outstanding mathematicians and theoretical physicists who have been awarded Simons Fellowships in 2020.
Joshua Vogelstein receives NSF CAREER Award
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
JHU launches new institute dedicated to supporting the ‘fourth industrial revolution’ of data science
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
TRIPODS Institute for the Foundations of Graph and Deep Learning at Johns Hopkins University
Using a $1.5 million, three-year Transdisciplinary Research in Principles of Data Science (TRIPODS) grant from the National Science Foundation, a multi-disciplinary team of researchers at Johns Hopkins’ Mathematical Institute of Data Science (MINDS) has created the TRIPODS Institute for the Foundations of Graph and Deep Learning at Johns Hopkins University to
Archana Venkataraman named to MIT Technology Review’s 2019 list of 35 Innovators under 35
Archana Venkataraman, member of the MINDS faculty and a John C. Malone Assistant Professor in the Department of Electrical and Computer Engineering, has been named to MIT Technology Review’s 2019 list of 35 Innovators under 35. The annual list recognizes outstanding innovators from a wide range of fields whose work promises
Vishal Patel and Rene Vidal join partnership to advance machine learning, artificial intelligence
Vishal Patel, an ECE Assistant Professor and a member of Johns Hopkins University’s Mathematical Institute for Data Science (MINDS), and Rene Vidal, the Herschel L. Seder Professor in JHU’s Department of Biomedical Engineering (with a secondary appointment in ECE) and the director of MINDS, have joined a new interdisciplinary research consortium
Vladimir Braverman received a Best Paper Award at FAST ’19
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
Carey Priebe’s paper “On a `Two Truths’ Phenomenon in Spectral Graph Clustering” has been accepted for publication at PNAS
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