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Alan S. Willsky

Alan S. Willsky

D-Index & Metrics

Computer Science

D-Index
106
Citations
52318
World Ranking
273
National Ranking
150

Research.com Recognitions

  • 2019 - Jack S. Kilby Signal Processing Medal For contributions to stochastic modeling
  • 2010 - Member of the National Academy of Engineering For contributions to model-based signal processing and statistical inference.
  • 1986 - IEEE Fellow For contributions to the theory of estimation and detection in stochastic systems and their application.

Overview

Alan S. Willsky is affiliated with the Massachusetts Institute of Technology (MIT) in the United States. They have established a career centered primarily on model-based signal processing and statistical inference within stochastic systems.

Throughout their career, Willsky has received several notable recognitions. In 1986, they were named an IEEE Fellow for contributions to the theory of estimation and detection in stochastic systems and their application. Additionally, they became a Member of the National Academy of Engineering in 2010 for their work in model-based signal processing and statistical inference. More recently, in 2019, Willsky was awarded the Jack S. Kilby Signal Processing Medal for contributions to stochastic modeling.

While comprehensive details about their publication record, frequent collaborators, specific fields and subfields of study, and topics explored in their research are not provided, the available awards and affiliations indicate a focus on advanced theoretical and applied aspects of stochastic systems and signal processing methodologies.

Best Publications

  • Paper: A survey of design methods for failure detection in dynamic systems

    Alan S. Willsky

  • A sparse signal reconstruction perspective for source localization with sensor arrays

    D. Malioutov;M. Cetin;A.S. Willsky

  • Analytical redundancy and the design of robust failure detection systems

    E. Chow;A. Willsky

  • A survey of design methods for failure detection in dynamic systems

    A. S. Willsky

  • The Convex Geometry of Linear Inverse Problems

    Venkat Chandrasekaran;Benjamin Recht;Pablo A. Parrilo;Alan S. Willsky

  • Rank-Sparsity Incoherence for Matrix Decomposition

    Venkat Chandrasekaran;Sujay Sanghavi;Pablo A. Parrilo;Alan S. Willsky

  • Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification

    A. Tsai;A. Yezzi;A.S. Willsky

  • A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems

    A. Willsky;H. Jones

  • A shape-based approach to the segmentation of medical imagery using level sets

    A. Tsai;A. Yezzi;W. Wells;C. Tempany

  • MAP estimation via agreement on trees: message-passing and linear programming

    M.J. Wainwright;T.S. Jaakkola;A.S. Willsky

  • Nonparametric belief propagation for self-localization of sensor networks

    A.T. Ihler;J.W. Fisher;R.L. Moses;A.S. Willsky

  • Nonparametric belief propagation

    Erik B. Sudderth;Alexander T. Ihler;Michael Isard;William T. Freeman

  • Failure detection and identification

    M.-A. Massoumnia;G.C. Verghese;A.S. Willsky

  • Kalman filtering and Riccati equations for descriptor systems

    R. Nikoukhah;A.S. Willsky;B.C. Levy

  • Nonparametric belief propagation

    E.B. Sudderth;A.T. Ihler;W.T. Freeman;A.S. Willsky

  • A new class of upper bounds on the log partition function

    M.J. Wainwright;T.S. Jaakkola;A.S. Willsky

  • Latent variable graphical model selection via convex optimization

    Venkat Chandrasekaran;Pablo A. Parrilo;Alan S. Willsky

  • A Sticky HDP-HMM With Application to Speaker Diarization

    Emily B. Fox;Erik B. Sudderth;Michael I. Jordan;Alan S. Willsky

  • Optimally robust redundancy relations for failure detection in uncertain systems

    X C Lou;A S Willsky;G C Verghese

  • The stochastic control of the F-8C aircraft using a multiple model adaptive control (MMAC) method--Part I: Equilibrium flight

    M. Athans;D. Castanon;K. Dunn;C. Greene

  • Modeling and estimation of multiresolution stochastic processes

    M. Basseville;A. Benveniste;K.C. Chou;S.A. Golden

Frequent Co-Authors

William Clement Karl
William Clement Karl Boston University
Bernard C. Levy
Bernard C. Levy University of California, Davis
Mujdat Cetin
Mujdat Cetin University of Rochester
Vincent Y. F. Tan
Vincent Y. F. Tan National University of Singapore
Erik B. Sudderth
Erik B. Sudderth University of California, Irvine
Alexander T. Ihler
Alexander T. Ihler University of California, Irvine

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