Research

VERITAS Mission

In November 2024, I joined the German Aerospace Center (DLR) as a staff researcher at the Remote Sensing Technology Institute in Oberpfaffenhofen, Germany. There, my role is to work on the ground processing software of the radar instrument of the upcoming VERITAS mission to Venus.

Simulations of Earthquake Sequences

My PhD thesis, advised by Mark Simons, focused on probabilistic inversions of geodetic datasets to constrain the rheological properties of subduction zones. The main innovations compared to the existing literature are the reliance on a probabilistic inversion (compared to trial-and-error runs) and the modeling of the entire earthquake cycle (compared to only modeling the postseismic phase). This work showed that such geodetic inversions are now computationally feasible, revealed the first GNSS-constrained estimates of rate-depedent frictional parameters for Northern Japan, and demonstrated important nuances when using kinematic coupling as a proxy for seismic hazard.

I presented preliminary findings at various conferences: AGU’s Fall Meeting in 2022 (poster), EGU’s General Assembly in 2023 poster, and AGU’s Fall Meeting in 2023 (poster).

A paper describing our approach and some 2D tests has been published in Earths, Planets and Space here and our coauthor Rishav Mallick gave a presentation with the latest update at AGU’s Fall Meeting in December 2024. A final paper incorporating more realistic elastic structure of the fault zone than what is in the dissertation is currently in the works.

GNSS Network Timeseries Analysis

One part of my PhD with Mark Simons was about timeseries analysis of large-scale Global Navigation Satellite Systems (GNSS) networks (e.g., GEONET or NOTA). GNSS networks allow researchers to monitor ground motion and deformation (e.g., due to tectonic plate movement, earthquakes, or volcanic activity) through the decomposition of the observed timeseries into different components (secular plate motion, seasonal oscillations, etc.). My work included the creation of a Python software package that allows users to quickly and easily do all of this, with current best practices already included.

For more information, check out the published study in Computers & Geosciences, the accepted preprint, the GitHub project, or the poster I made for AGU’s Fall Meeting 2021.

Machine Learning for Damage Proxy Mapping

Together with Oliver Stephenson, Zach Ross, Mark Simons, and others, I was also part of an investigation into using Interferometric Synthetic Aperture Radar (InSAR) image timeseries to map damage caused by natural disasters using coherence changes and machine learning.

For more information, check out our paper published in IEEE Transactions on Geoscience and Remote Sensing (or the preprint on arXiv).

Excursion into Planetary Sciences: About Retrograde Trojan Asteroids

As part of my first-year research projects at Caltech, I looked into the possible origins of the quite fascinating retrograde Trojan asteroid 514107 Ka’epaoka’awela using numerical simulations with Konstantin Batygin. You can read our paper on arXiv or published in Celestial Mechanics and Dynamical Astronomy.