What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Optics
His primary scientific interests are in Seismology, Algorithm, Seismic noise, Inversion and Acoustics.
Peter Gerstoft is interested in Microseism, which is a field of Seismology.
His Algorithm research is multidisciplinary, relying on both Clutter, Beamforming, Mathematical optimization, Wave equation and Posterior probability.
His work carried out in the field of Seismic noise brings together such families of science as Cross-correlation, Surface wave and Noise.
In his study, Bayesian probability and Applied mathematics is strongly linked to Monte Carlo method, which falls under the umbrella field of Inversion.
The concepts of his Acoustics study are interwoven with issues in Estimation theory, Underwater acoustics and Waves and shallow water.
His most cited work include:
- Surface wave tomography from microseisms in Southern California (462 citations)
- Extracting time-domain Green's function estimates from ambient seismic noise (402 citations)
- Seismic interferometry-turning noise into signal (278 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Acoustics, Algorithm, Inversion, Seismology and Noise.
His research integrates issues of Underwater acoustics, Seabed, Waves and shallow water and Signal processing in his study of Acoustics.
His studies in Algorithm integrate themes in fields like Sensor array, Beamforming, Mathematical optimization and Bayesian inference.
His work deals with themes such as Remote sensing, Speed of sound, Broadband and Inverse problem, which intersect with Inversion.
His study in Seismology is interdisciplinary in nature, drawing from both Geophysics, Wind wave and Noise.
His biological study spans a wide range of topics, including Gaussian noise and Cross-correlation.
He most often published in these fields:
- Acoustics (29.75%)
- Algorithm (27.22%)
- Inversion (17.72%)
What were the highlights of his more recent work (between 2018-2021)?
- Algorithm (27.22%)
- Artificial intelligence (9.07%)
- Bayesian inference (8.02%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Algorithm, Artificial intelligence, Bayesian inference, Acoustics and Pattern recognition.
Peter Gerstoft interconnects Heteroscedasticity, Direction of arrival, Bayesian probability and Beamforming in the investigation of issues within Algorithm.
His Artificial intelligence research includes elements of Machine learning, Bioacoustics and Ranging.
Peter Gerstoft focuses mostly in the field of Bayesian inference, narrowing it down to topics relating to Process and, in certain cases, Noise.
Peter Gerstoft is interested in Ambient noise level, which is a branch of Acoustics.
Peter Gerstoft studied Coral reef and Cluster analysis that intersect with Seismology.
Between 2018 and 2021, his most popular works were:
- Machine Learning in Seismology: Turning Data into Insights (118 citations)
- Machine learning in acoustics: Theory and applications (34 citations)
- Robust Ocean Acoustic Localization With Sparse Bayesian Learning (15 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Optics
Peter Gerstoft mainly focuses on Artificial intelligence, Algorithm, Acoustics, Pattern recognition and Direction of arrival.
His Artificial intelligence study combines topics in areas such as Machine learning and Ranging.
His research on Algorithm focuses in particular on Optimization problem.
A large part of his Acoustics studies is devoted to Speed of sound.
His Pattern recognition study also includes fields such as
- Transfer function and related Semi-supervised learning,
- Supervised learning, which have a strong connection to Hyperparameter, Inverse problem, Beamforming, Support vector machine and Nonlinear system.
His Direction of arrival study which covers Amplitude that intersects with Principal component analysis, Microphone array and Angular displacement.
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