Peter Gerstoft

Peter Gerstoft is an acoustics and geophysics researcher whose work applies machine learning to physical signals. He earned engineering degrees in Denmark and Canada, developed the SAGA inversion code for ocean acoustics, and joined UC San Diego's Marine Physical Laboratory in 1997. He later served with the Comprehensive Nuclear-Test-Ban Treaty Organization, taught machine learning at UC San Diego, and coauthored reviews of machine learning in seismology and acoustics. He became an IEEE Fellow in 2023 and received the Acoustical Society of America Silver Award in Signal Processing in June 2026. As of October 2026, he is a professor at DTU and coauthors a paper on ocean sound-speed forecasting with a diffusion model and a multi-output Gaussian process.

Now at: Technical University of Denmark and University of California, San Diego
Works: 781
Citations: 15,754
h-index: 64
Badges: Bridge
Boomerang
Wayfarer
Loyal

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

1983–1997

Degrees and SAGA inversion

He earns M.Sc. and Ph.D. degrees in structural engineering at the Technical University of Denmark in 1983 and 1986, and an M.Sc. at the University of Western Ontario in 1984. From 1987 to 1992, he works on seismic exploration modeling and inversion at Ødegaard and Danneskiold-Samsøe. From 1992 to 1997, he is a senior scientist at SACLANT Undersea Research Centre and develops the SAGA inversion code for ocean acoustic and electromagnetic signals.
1997

Joining UC San Diego

In 1997, he joins UC San Diego's Marine Physical Laboratory and researches signal processing to extract information from noise in acoustic, electromagnetic, and seismic media.
1999–2000

A CTBTO appointment

From 1999 to 2000, he serves as a Senior Seismic Acoustic Officer with the Comprehensive Nuclear-Test-Ban Treaty Organization.
2013

Teaching machine learning

In 2013, he begins an adjunct faculty position in Electrical and Computer Engineering at UC San Diego, teaching courses in seismology, data assimilation, and machine learning for physical systems.
2018–2019

Machine learning across disciplines

In 2018, he coauthors “Machine Learning in Seismology: Turning Data into Insights,” a survey of machine-learning applications in seismology. In 2019, he coauthors “Machine learning in acoustics: theory and applications,” surveying machine learning, including deep learning, across acoustics.
2023

An IEEE Fellowship

In 2023, he becomes an IEEE Fellow for contributions to environmental signal processing and geoacoustic array processing.
June 2026

An ASA Silver Award

In June 2026, he receives the Acoustical Society of America Silver Award in Signal Processing.
As of October 2026

Professor at DTU

As of October 2026, he is a Professor in the Department of Electrical and Photonics Engineering at DTU. In 2026, he coauthors “Continuous forecasting of range-dependent ocean sound speed field: Diffusion model meets multi-output Gaussian process.”

Career

Since 1986Technical University of DenmarkProfessor
1999–2000Comprehensive Nuclear-Test-Ban Treaty OrganizationSenior Seismic Acoustic Officer
1997–2026University of California, San DiegoAdjunct Faculty
1993–1997North Atlantic Treaty Organization
1992–1997SACLANT Undersea Research CentreSenior Scientist
1987–1992Ødegaard and Danneskiold-Samsøe