About

Professional Timeline Link to heading

  • Nov. 2020 - Present: Signal Analysis Engineer @ JPL, working on OPERA and ARIA, with David Bekaert’s group and Radar Science
  • Dec. 2017 - Nov. 2020: Postdoctoral Fellow @ JPL, supervised by Marc Simard
  • Jan. 2017 - Nov. 2017: Data Scientist @ Operam, measuring online engagement for film and television
  • 2010 - 2017: Applied Mathematics Ph.D. @ UCLA, supervised by Andrea Bertozzi and Mason Porter
  • 2006 - 2010: Mathematics B.A. @ UC Berkeley

Professional Summary Link to heading

I am a Signal Analysis Engineer at Jet Propulsion Laboratory (JPL) witin the Radar Science and Engineering section. As a Signal Analysis engineer, I work as a geospatial data scientist, applying tools coming from varied disciplines including deep learning, network science, statistics, and computer vision to design algorithms for and to analyze signals from Syntehtic Aperture Radar (SAR) imagery. I currently work on the JPL projects Observational Products for End-Users from Remote Sensing Analysis (OPERA) and Advanced Rapid Imaging and Analysis (ARIA). It is a privilege to be apart of these projects, supporting the generation of products to help delineate hazards, identify surface water, and quantify surface displacement.

On OPERA, I currently support the Disturbance from Sentinel-1 product (DIST-S1), which is part of the SAR and optical disturbance suite. We identify generic surface disturbances with deep learning by comparing a recent set of Sentinel-1 acquisitions to a baseline of historical imagery. The input imagery comes from the OPERA Radiometrically and Terrain corrected imagery which corrects for geometric effects associated with process of SAR image formation. The disturbance product is a powerful tool to help delineate hazards such as fires and floods after a Sentinel-1 pass. The open-source software for DIST-S1 surface disturbance can be found here. I have also supported validation activities, documenting requirements for the project and writing software to verify the requirements were met. I worked on the latter for the Dynamic Surface Water Extent (DSWx) products. Validation entails ensuring that the OPERA products meet minimum accuracy and quality requirements using independent datasets and measurements. The open-source software for the DSWx product suite can be found here.

On ARIA, I support the cloud processing that generates the ARIA-S1-GUNW geocoded interferograms and related products for tectonically active areas. These intefergorams can provide centimeter-scale information about surface displacement after landslides, earthquakes or volcanoes. We have developed many open-source tools to better enable such processing in the cloud. We effectively wrap ISCE2 to process Sentinel-1 TOPS imagery and RAiDER to perform tropospheric corrections, generating these products at scale. These interferometric products can be searched and downloaded from the Alaska Satellite Facility data page. I worked closely with David Bekaert, who served as the ARIA project scientist until 2025 to grow the archive from just over 200,000 products to nearly 1.1 million. This accomplishment was facilitated by the NASA ACCESS Grant that permitted a highly productive collaboration between JPL and ASF, including Joseph Kennedy and Andrew Johnston. You can now even request the generation of the ARIA-S1-GUNW products on-demand from recent Sentinel-1 acquisitions (instructions here).

Before becoming a signal analysis engineer, I was a JPL postdoctoral fellow working under the supervision of Marc Simard using airborne and satellite SAR imagery to estimate biomass in dense tropical forests, map mangrove extents, generate river networks to support hydrological discharge analyses, and detect forest disturbances for L-band imagery (in preparation for NISAR) using data from ALOS-1, ALOS-2, and UAVSAR. In addition, we created remote sensing tutorials for NASA’s Land-Cover and Land-Use Change program to foster international remote sensing collaborations.

I earned my Ph.D. at UCLA under the supervision of Andrea Bertozzi and Mason Porter in applied and computational mathematics. I also worked closely with Puck Rombach during that time. I modeled processes in education, ecology, and organized crime using tools from network science. Additionally, I interned with Igor Yanovsky in the summer of 2016 applying Le-Vese segmentation to MISR images. Before coming to JPL as a postdoc, I worked at the advertising startup Operam as a data scientist measuring online engagement for clients in film and television.

Postdocs and Internships Supervised Link to heading