Germán Prieto received the 2010 Keiiti Aki Young Scientist Award at the 2010 AGU Fall Meeting, held 13–17 December in San Francisco, Calif. The award recognizes the scientific accom-plishments of a young scientist who makes outstanding contributions to the advancement of seismology.
Germán Prieto is an outstanding young seismologist of exceptional ability. Germán went to graduate school at the Scripps Institution of Oceanography, San Diego, Calif., and earned his Ph.D. in 2007. He was at Stanford University, Stanford, Calif., through 2008 as the Thompson Postdoctoral Fellow and is now on the faculty at the Universidad de los Andes, in Bogotá, Colombia. Germán’s work is consistently innovative and is characterized by a powerful combination of theoretical and practical insight.
Germán’s thesis research work with Peter Shearer and Frank Vernon focused on the earthquake source, and he developed a new approach for analyzing large waveform data sets that led to source parameter estimates for an order of magnitude more earthquakes than any previous study. This work provides some of the strongest evidence extant for self-similarity in the earthquake source.
During his postdoc, Germán’s research took a different direction. He used deconvolution to recover Green’s functions from the ambient field in a way that preserves amplitude, and he predicted basin response for a moderate earthquake in Southern California based on these Green’s functions. This opens a new approach to seismic hazard analysis at long periods that will see widespread application in the future.
In 2009, Germán developed the first technique to recover anelastic structure from the ambient field, which creates new opportunities in structural seismology. It is particularly fitting that he receive this award, because in developing this method he went back to the original spatial autocorrelation formulation developed by Kei Aki himself in 1957. Most recently, Germán and Jesse Lawrence have used attenuation measurements from the ambient field as the foundation for attenuation tomography of the western United States with spectacular results.
In his short career, Germán has pioneered new techniques to address important research problems spanning an increasingly broad range of topics. We can expect great things from him in the future.—Gregory C. Beroza, Geophysics Department, Stanford University, Stanford, Calif.
I am very honored to receive this prestigious award named after one the great seismologists of our time. It is almost inescapable that Kei Aki would have an early reference in most topics that young seismologists would dive into. For example, self-similarity was a term often used in Aki’s early papers. Use of the ambient seismic field, one of Aki’s early achievements, was first presented in 1957.
I am grateful to many people for this award: to my research advisors and mentors Peter Shearer and Frank Vernon at University of California, San Diego (UCSD) and Greg Beroza at Stanford University, as well as collaborator Jesse Lawrence. All of them gave me the opportunity to work on these very interesting research topics, sharing their insights and ideas, and providing the most exciting atmosphere to explore beyond their own expertise and to collaborate with other researchers. I would like to acknowledge nonseismologists Bob Parker (UCSD) and Dave Thomson (Queen’s University, Canada), who over the years have shared a different point of view on how to analyze seismological data; and my wife, Carolina, who has had to listen about earthquakes and noise every night.
As previous awardees David Shelly and Florent Brenguier have demonstrated, the large amount of freely available geophysical data is one of the most important assets seismologists have, but it is also important to develop fast, clever, and accurate signal processing methods in order to extract as much information as possible from these data.
I look forward to continuing to try to solve outstanding questions in seismology and geophysics, many of them likely to have been studied by Aki himself.—Germán Prieto , Universidad de los Andes, Bogotá, Colombia