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Research.com Recognitions

  • 2009 - Hellman Fellow

Overview

Ery Arias-Castro is affiliated with the University of California, San Diego in the United States. Their research primarily lies within the field of Computer Science, with a focus on several subfields, including Artificial Intelligence, Statistics and Probability, Computational Theory and Mathematics, Signal Processing, and Control and Systems Engineering.

The main topics addressed in their work include:

  • Statistical Methods and Inference
  • Topological and Geometric Data Analysis
  • Advanced Clustering Algorithms Research
  • Control Systems and Identification
  • Anomaly Detection Techniques and Applications
  • Bayesian Methods and Mixture Models
  • Complex Network Analysis Techniques

Ery Arias-Castro has published extensively, with recent papers spanning several years and venues:

  • "Is It Easier to Count Communities Than Find Them?" (2023), published in Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • "On the estimation of latent distances using graph distances" (2021), Electronic Journal of Statistics
  • "The sparse variance contamination model" (2020), Statistics
  • "Template Matching and Change Point Detection by M-Estimation" (2021), IEEE Transactions on Information Theory
  • "A scan procedure for multiple testing: Beyond threshold-type procedures" (2020), Journal of Statistical Planning and Inference

Frequent co-authors collaborating with Arias-Castro include Wanli Qiao, Zheng Yan Lin, Clément Berenfeld, Phong Alain Chau, and Ivo V. Stoepker. These collaborations reflect a network of joint research within their fields of expertise.

Their work is commonly published in venues such as:

  • arXiv (Cornell University)
  • Electronic Journal of Statistics
  • SIAM Journal on Mathematics of Data Science
  • Information and Inference A Journal of the IMA
  • The Annals of Statistics

In addition to journal articles, Ery Arias-Castro has contributed to academic literature through book publications. Notably, they authored "Principles of Statistical Analysis" (2022), published by Cambridge University Press.

They have been recognized with the Hellman Fellow award in 2009.

Best Publications

  • Does median filtering truly preserve edges better than linear filtering

    Ery Arias-Castro;David L. Donoho

  • High-frequency irradiance fluctuations and geographic smoothing

    Matthew Lave;Jan Kleissl;Ery Arias-Castro

  • Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism

    Ery Arias-Castro;Emmanuel J. Candès;Yaniv Plan

  • Near-optimal detection of geometric objects by fast multiscale methods

    E. Arias-Castro;D.L. Donoho;Xiaoming Huo

  • Detection of an anomalous cluster in a network

    Ery Arias-Castro;Emmanuel J. Candès;Arnaud Durand

  • On the Fundamental Limits of Adaptive Sensing

    E. Arias-Castro;E. J. Candes;M. A. Davenport

  • Community detection in dense random networks

    Ery Arias-Castro;Nicolas Verzelen

  • Searching for a trail of evidence in a maze

    Ery Arias-Castro;Emmanuel J. Candès;Hannes Helgason;Ofer Zeitouni

  • On the estimation of the gradient lines of a density and the consistency of the mean-shift algorithm

    Ery Arias-Castro;David Mason;Bruno Pelletier

  • Spectral clustering based on local linear approximations

    Ery Arias-Castro;Guangliang Chen;Gilad Lerman

  • A super-class walk on upper-triangular matrices

    Ery Arias-Castro;Persi Diaconis;Richard Stanley

  • Spectral clustering based on local PCA

    Ery Arias-Castro;Gilad Lerman;Teng Zhang

  • Discrete False-Discovery Rate Improves Identification of Differentially Abundant Microbes

    Lingjing Jiang;Amnon Amir;James T. Morton;Ruth Heller

  • Community detection in sparse random networks

    Nicolas Verzelen;Ery Arias-Castro

  • A Poisson model for anisotropic solar ramp rate correlations

    Ery Arias-Castro;Jan Kleissl;Matthew Lave

  • Distribution-free multiple testing

    Ery Arias-Castro;Shiyun Chen

  • Detection of correlations

    Ery Arias-Castro;Sébastien Bubeck;Gábor Lugosi

  • Adaptive multiscale detection of filamentary structures embedded in a background of uniform random points

    Ery Arias-Castro;David L. Donoho;Xiaoming Huo

  • Community Detection in Random Networks

    Ery Arias-Castro;Nicolas Verzelen

  • Community Detection in Sparse Random Networks

    Ery Arias-Castro;Nicolas Verzelen

Frequent Co-Authors

Gábor Lugosi
Gábor Lugosi Pompeu Fabra University
Emmanuel J. Candès
Emmanuel J. Candès Stanford University
David L. Donoho
David L. Donoho Stanford University
Sébastien Bubeck
Sébastien Bubeck Microsoft (United States)
Rui Castro
Rui Castro Eindhoven University of Technology
Mark A. Davenport
Mark A. Davenport Georgia Institute of Technology
Rebecca Willett
Rebecca Willett University of Chicago
Venkatesh Saligrama
Venkatesh Saligrama Boston University
Jan Kleissl
Jan Kleissl University of California, San Diego
Yonina C. Eldar
Yonina C. Eldar Weizmann Institute of Science

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