World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
17742
World Ranking
3760
National Ranking
1796

Electronics and Electrical Engineering

D-Index
54
Citations
16658
World Ranking
2236
National Ranking
876

Research.com Recognitions

  • 2014 - IEEE Fellow For contributions to signal processing in communications

Overview

Philip Schniter is affiliated with The Ohio State University in the United States and has contributed extensively to research spanning engineering, medicine, and computer science. Their work intersects several specialized fields, including radiology, nuclear medicine and imaging, artificial intelligence, computer vision and pattern recognition, computational mechanics, and biomedical engineering.

The main topics of Schniter's research include advanced MRI techniques and applications, medical imaging techniques and applications, sparse and compressive sensing techniques, stochastic gradient optimization techniques, numerical methods in inverse problems, photoacoustic and ultrasonic imaging, and image and signal denoising methods.

They have published in a variety of highly specialized venues, with frequent publications appearing in:

  • arXiv (Cornell University)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • IEEE Signal Processing Magazine
  • IEEE Journal on Selected Areas in Information Theory
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Among notable recent papers authored or coauthored by Schniter are:

  • Plug-and-Play Methods for Magnetic Resonance Imaging: Using Denoisers for Image Recovery (2020, IEEE Signal Processing Magazine)
  • OCMR (v1.0)--Open-Access Multi-Coil k-Space Dataset for Cardiovascular Magnetic Resonance Imaging (2020, arXiv (Cornell University))
  • Sketching Data Sets for Large-Scale Learning: Keeping only what you need (2021, IEEE Signal Processing Magazine)
  • Inference With Deep Generative Priors in High Dimensions (2020, IEEE Journal on Selected Areas in Information Theory)
  • Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery (2022, IEEE Journal on Selected Areas in Information Theory)

Schniter's frequent collaborators include Rizwan Ahmad, R. Badlishah Ahmad, Sizhuo Liu, Saurav K. Shastri, and Xuan Lei. These coauthors have contributed to a significant portion of the body of work in signal processing and medical imaging techniques associated with Schniter.

In 2014, Philip Schniter was recognized as an IEEE Fellow for contributions to signal processing in communications. This accolade reflects the standing within the engineering and signal processing community.

Best Publications

  • In-Band Full-Duplex Wireless: Challenges and Opportunities

    Ashutosh Sabharwal;Philip Schniter;Dongning Guo;Daniel W. Bliss

  • On the achievable diversity-multiplexing tradeoff in half-duplex cooperative channels

    K. Azarian;H. El Gamal;P. Schniter

  • Blind equalization using the constant modulus criterion: a review

    R. Johnson;P. Schniter;T.J. Endres;J.D. Behm

  • Vector Approximate Message Passing

    Sundeep Rangan;Philip Schniter;Alyson K. Fletcher

  • Low-complexity equalization of OFDM in doubly selective channels

    P. Schniter

  • Expectation-Maximization Gaussian-Mixture Approximate Message Passing

    Jeremy P. Vila;Philip Schniter

  • Full-Duplex Bidirectional MIMO: Achievable Rates Under Limited Dynamic Range

    B. P. Day;A. R. Margetts;D. W. Bliss;P. Schniter

  • AMP-Inspired Deep Networks for Sparse Linear Inverse Problems

    Mark Borgerding;Philip Schniter;Sundeep Rangan

  • Compressive phase retrieval via generalized approximate message passing

    Philip Schniter;Sundeep Rangan

  • Full-duplex MIMO relaying: Achievable rates under limited dynamic range

    Brian P. Day;Adam R. Margetts;Daniel W. Bliss;Philip Schniter

  • Channel Estimation in Broadband Millimeter Wave MIMO Systems With Few-Bit ADCs

    Jianhua Mo;Philip Schniter;Robert W. Heath

  • Full-duplex bidirectional MIMO: Achievable rates under limited dynamic range

    Unknown

  • Channel estimation in millimeter wave MIMO systems with one-bit quantization

    Jianhua Mo;Philip Schniter;Nuria Gonzalez Prelcic;Robert W. Heath

  • Compressive imaging using approximate message passing and a Markov-tree prior

    Subhojit Som;Lee C. Potter;Philip Schniter

  • Bilinear Generalized Approximate Message Passing—Part I: Derivation

    Jason T. Parker;Philip Schniter;Volkan Cevher

  • Fast bayesian matching pursuit

    P. Schniter;L.C. Potter;J. Ziniel

  • Regularization by Denoising: Clarifications and New Interpretations

    Edward T. Reehorst;Philip Schniter

  • On the Convergence of Approximate Message Passing With Arbitrary Matrices

    Sundeep Rangan;Philip Schniter;Alyson K. Fletcher;Subrata Sarkar

  • Channel estimation and precoder design for millimeter-wave communications: The sparse way

    Philip Schniter;Akbar Sayeed

  • Fast Bayesian Matching Pursuit: Model Uncertainty and Parameter Estimation for Sparse Linear Models

    Philip Schniter;Justin Ziniel

  • Plug-and-Play Methods for Magnetic Resonance Imaging: Using Denoisers for Image Recovery

    Rizwan Ahmad;Charles A. Bouman;Gregery T. Buzzard;Stanley Chan

  • On the convergence of approximate message passing with arbitrary matrices

    Sundeep Rangan;Philip Schniter;Alyson K. Fletcher

  • Hybrid Approximate Message Passing

    Sundeep Rangan;Alyson K. Fletcher;Vivek K. Goyal;Evan Byrne

  • On the Achievable Diversity-Multiplexing Tradeoffs in Half-Duplex Cooperative Channels

    Kambiz Azarian;Hesham El Gamal;Philip Schniter

Frequent Co-Authors

Sundeep Rangan
Sundeep Rangan New York University
Alyson K. Fletcher
Alyson K. Fletcher University of California, Los Angeles
Richard G. Baraniuk
Richard G. Baraniuk Rice University
Daniel W. Bliss
Daniel W. Bliss Arizona State University
Volkan Cevher
Volkan Cevher École Polytechnique Fédérale de Lausanne
H. El Gamal
H. El Gamal University of Sydney
Robert W. Heath
Robert W. Heath University of California, San Diego
Vivek K. Goyal
Vivek K. Goyal Boston University
Ashok Veeraraghavan
Ashok Veeraraghavan Rice University
Ness B. Shroff
Ness B. Shroff The Ohio State University

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