World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
6642
World Ranking
12937
National Ranking
200

Overview

Ami Wiesel is affiliated with the Hebrew University of Jerusalem in Israel. Their research primarily intersects the fields of Computer Science and Engineering.

Their work focuses on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Computer Networks and Communications, and Control and Systems Engineering.

Key research topics covered by Ami Wiesel encompass:

  • Sparse and Compressive Sensing Techniques
  • Distributed Sensor Networks and Detection Algorithms
  • Machine Learning and Algorithms
  • Fault Detection and Control Systems
  • Image and Signal Denoising Methods
  • Anomaly Detection Techniques and Applications
  • Advanced Image Processing Techniques

Ami Wiesel has collaborated frequently with several coauthors, including:

  • Tzvi Diskin
  • Uri Okun
  • Yiftach Beer
  • Yonina C. Eldar
  • Itai Alon

Their publication record includes multiple recent papers such as:

  • CFARnet: Deep learning for target detection with constant false alarm rate, 2024, published in Signal Processing
  • Learning to Estimate Without Bias, 2023, published in IEEE Transactions on Signal Processing
  • PnP-Net: A hybrid Perspective-n-Point Network, 2020, published on arXiv (Cornell University)
  • Learning to Detect with Constant False Alarm Rate, 2022, presented at the 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)
  • Learning to Estimate Without Bias, 2021, published on arXiv (Cornell University)

Common venues where Ami Wiesel publishes include:

  • arXiv (Cornell University)
  • IEEE Signal Processing Letters
  • IEEE Transactions on Signal Processing
  • Signal Processing
  • 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)

Best Publications

  • Linear precoding via conic optimization for fixed MIMO receivers

    A. Wiesel;Y.C. Eldar;S. Shamai

  • Zero-Forcing Precoding and Generalized Inverses

    A. Wiesel;Y.C. Eldar;S. Shamai

  • Dynamic reconfiguration of the default mode network during narrative comprehension

    Erez Simony;Christopher J Honey;Janice Chen;Olga Lositsky

  • Shrinkage Algorithms for MMSE Covariance Estimation

    Yilun Chen;Ami Wiesel;Yonina C Eldar;Alfred O Hero

  • Learning to Detect

    Neev Samuel;Tzvi Diskin;Ami Wiesel

  • Deep MIMO detection

    Neev Samuel;Tzvi Diskin;Ami Wiesel

  • Robust Shrinkage Estimation of High-Dimensional Covariance Matrices

    Yilun Chen;A. Wiesel;A. O. Hero

  • On the Gaussian MIMO Wiretap Channel

    A. Khisti;G. Wornell;A. Wiesel;Y. Eldar

  • Semidefinite relaxation for detection of 16-QAM signaling in MIMO channels

    A. Wiesel;Y.C. Eldar;S. Shamai

  • Efficient implementation of sphere demodulation

    A. Wiesel;X. Mestre;A. Pages;J.R. Fonollosa

  • Non-data-aided signal-to-noise-ratio estimation

    A. Wiesel;J. Goldberg;H. Messer

  • Geodesic Convexity and Covariance Estimation

    A. Wiesel

  • SNR estimation in time-varying fading channels

    A. Wiesel;J. Goldberg;H. Messer-Yaron

  • Power System State Estimation Using PMUs With Imperfect Synchronization

    Peng Yang;Zhao Tan;Ami Wiesel;Arye Nehora

  • Unified Framework to Regularized Covariance Estimation in Scaled Gaussian Models

    A. Wiesel

  • Multivariate Generalized Gaussian Distribution: Convexity and Graphical Models

    Teng Zhang;Ami Wiesel;Maria Sabrina Greco

  • Linear Regression With Gaussian Model Uncertainty: Algorithms and Bounds

    A. Wiesel;Y.C. Eldar;A. Yeredor

  • Distributed Covariance Estimation in Gaussian Graphical Models

    A. Wiesel;A. O. Hero

  • Shrinkage estimation of high dimensional covariance matrices

    Yilun Chen;Ami Wiesel;Alfred O. Hero

  • Multidimensional Shrinkage-Thresholding Operator and Group LASSO Penalties

    A T Puig;A Wiesel;G Fleury;A O Hero

  • Decomposable Principal Component Analysis

    A. Wiesel;A.O. Hero

  • Time Varying Autoregressive Moving Average Models for Covariance Estimation

    Ami Wiesel;Ofir Bibi;Amir Globerson

Frequent Co-Authors

Alfred O. Hero
Alfred O. Hero University of Michigan–Ann Arbor
Yonina C. Eldar
Yonina C. Eldar Weizmann Institute of Science
Shlomo Shamai
Shlomo Shamai Technion – Israel Institute of Technology
Amir Globerson
Amir Globerson Tel Aviv University
Yossi Matias
Yossi Matias Google (United States)
Avinatan Hassidim
Avinatan Hassidim Bar-Ilan University
Arye Nehorai
Arye Nehorai Washington University in St. Louis
Rick S. Blum
Rick S. Blum Lehigh University
Maria Greco
Maria Greco University of Pisa
Jinhong Yuan
Jinhong Yuan University of New South Wales

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