2026 Peter Gerstoft: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	51	5371	5219	2458	2373	413	9789

Peter Gerstoft publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Peter Gerstoft sits on this spectrum.

32 publications 991+

This scientist: 413 publications — 88th percentile

88% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Peter Gerstoft D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Peter Gerstoft sits on this spectrum.

30 D-Index 131+

This scientist: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Peter Gerstoft is affiliated with the University of California, San Diego in the United States. Their research spans multiple disciplines, primarily within Computer Science, Earth and Planetary Sciences, and Engineering. Within these fields, Gerstoft's work focuses on subfields such as Signal Processing, Oceanography, Geophysics, Artificial Intelligence, and Electrical and Electronic Engineering.

Their scientific contributions involve numerous topics, including:

Underwater Acoustics Research
Speech and Audio Processing
Direction-of-Arrival Estimation Techniques
Seismic Waves and Analysis
Blind Source Separation Techniques
Underwater Vehicles and Communication Systems
Indoor and Outdoor Localization Technologies

Gerstoft's recent publications demonstrate a focus on acoustic signal processing and direction-of-arrival (DOA) estimation methods. Selected examples include:

Gridless DOA Estimation and Root-MUSIC for Non-Uniform Linear Arrays, 2021, published in IEEE Transactions on Signal Processing
A feedforward neural network for direction-of-arrival estimation, 2020, published in The Journal of the Acoustical Society of America
Gaussian processes for sound field reconstruction, 2021, published in The Journal of the Acoustical Society of America
Deep transfer learning for underwater direction of arrival using one vector sensor, 2021, published in The Journal of the Acoustical Society of America
Three-dimensional source localization using sparse Bayesian learning on a spherical microphone array, 2020, published in The Journal of the Acoustical Society of America

Their collaborations include frequent co-authors such as Yongsung Park, Michael J. Bianco, William F. Jenkins, Efrén Fernández-Grande, and Zoi-Heleni Michalopoulou. Gerstoft has maintained a substantial publication record in venues focused on acoustics and signal processing, including:

The Journal of the Acoustical Society of America
arXiv (Cornell University)
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
JASA Express Letters
IEEE Transactions on Signal Processing

Best Publications

Extracting time-domain Green's function estimates from ambient seismic noise

Karim G. Sabra;Peter Gerstoft;Philippe Roux;W. A. Kuperman

729
Citations
Machine learning in acoustics: Theory and applications

Michael J. Bianco;Peter Gerstoft;James Traer;Emma Ozanich

572
Citations
Machine Learning in Seismology: Turning Data into Insights

Qingkai Kong;Daniel T. Trugman;Zachary E. Ross;Michael J. Bianco

492
Citations
Inversion of seismoacoustic data using genetic algorithms and a posteriori probability distributions

Peter Gerstoft

438
Citations
Compressive beamforming.

Unknown

356
Citations
Multisnapshot Sparse Bayesian Learning for DOA

Peter Gerstoft;Christoph F. Mecklenbrauker;Angeliki Xenaki;Santosh Nannuru

241
Citations
Ocean acoustic inversion with estimation of a posteriori probability distributions

Peter Gerstoft;Christoph F. Mecklenbräuker

238
Citations
Inversion for refractivity parameters from radar sea clutter

Peter Gerstoft;L. Ted Rogers;Jeffrey L. Krolik;William S. Hodgkiss

231
Citations
Source localization in an ocean waveguide using supervised machine learning.

Haiqiang Niu;Emma Reeves;Peter Gerstoft

192
Citations
Compressive sensing of the Tohoku-Oki Mw 9.0 earthquake: Frequency-dependent rupture modes

Huajian Yao;Peter Gerstoft;Peter M. Shearer;Christoph Mecklenbräuker

191
Citations
A sparse equivalent source method for near-field acoustic holography

Efren Fernandez-Grande;Angeliki Xenaki;Peter Gerstoft

163
Citations
Ship localization in Santa Barbara Channel using machine learning classifiers.

Haiqiang Niu;Emma Ozanich;Peter Gerstoft

162
Citations
Grid-free compressive beamforming

Angeliki Xenaki;Peter Gerstoft

156
Citations
The seismic traffic footprint: Tracking trains, aircraft, and cars seismically

Nima Riahi;Peter Gerstoft

156
Citations
Gridless DOA Estimation and Root-MUSIC for Non-Uniform Linear Arrays

Mark Wagner;Yongsung Park;Peter Gerstoft

155
Citations
Inversion of acoustic data using a combination of genetic algorithms and the Gauss–Newton approach

Peter Gerstoft

144
Citations
Refractivity estimation from sea clutter: An invited review

Ali Karimian;Caglar Yardim;Peter Gerstoft;William S. Hodgkiss

144
Citations
Tracking Refractivity from Clutter Using Kalman and Particle Filters

C. Yardim;P. Gerstoft;W.S. Hodgkiss

143
Citations
Pelagic and coastal sources of P‐wave microseisms: Generation under tropical cyclones

Jian Zhang;Peter Gerstoft;Peter D. Bromirski

137
Citations
Multiple and single snapshot compressive beamforming

Peter Gerstoft;Angeliki Xenaki;Christoph F. Mecklenbräuker

133
Citations
Multi-frequency sparse Bayesian learning for robust matched field processing.

Kay L. Gemba;Santosh Nannuru;Peter Gerstoft;William S. Hodgkiss

126
Citations
Estimation of radio refractivity from Radar clutter using Bayesian Monte Carlo analysis

C. Yardim;P. Gerstoft;W.S. Hodgkiss

114
Citations
Deep-learning source localization using multi-frequency magnitude-only data

Haiqiang Niu;Zaixiao Gong;Emma Ozanich;Peter Gerstoft

110
Citations
A feedforward neural network for direction-of-arrival estimation

Emma Ozanich;Peter Gerstoft;Haiqiang Niu

107
Citations
Multi Snapshot Sparse Bayesian Learning for DOA Estimation

Peter Gerstoft;Christoph F. Mecklenbräuker;Angeliki Xenaki

21
Citations

Frequent Co-Authors

William S. Hodgkiss University of California, San Diego

Peter D. Bromirski University of California, San Diego

Christoph F. Mecklenbrauker TU Wien

Ralph A. Stephen Woods Hole Oceanographic Institution

Richard C. Aster Colorado State University

William A. Kuperman University of California, San Diego

Peter M. Shearer University of California, San Diego

Andrew A. Nyblade Pennsylvania State University

Douglas A. Wiens Washington University in St. Louis

Heechun Song Scripps Institution of Oceanography

External Links

Personal website of Peter Gerstoft

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