Hey! I'm Becca.
I am a machine learning scientist with a passion for tackling climate change with data-driven solutions.
Current status: In 2023, I will be starting as a Data Scientist and Engineer at the San Francisco Planning Department. With 6+ years of experience using machine learning to understand complex global systems, I am excited to bring my skillset to human-centered applications of data science. I'm currently living in San Francisco.
Resume
Data Scientist/ Data Engineer
SF Planning with the City and County of San Francisco
Jan 2023 - present
Work
Software scientist at NASA GISS Ocean Carbon Biogeochemistry modelling group (2016-2019, 2020-2022)
Visiting research scientist at Institute for Marine & Antarctic Studies (2019)
Visiting research scientist at Simon Fraser University Glaciology (2019)
Service
Educator for Tasmania | Wilderness Society (2020)
Tech Team Member in Australian Youth Climate Coalition (2020)
Founder and President of Columbia Spectra: Society for Diversity and Inclusion in Physics (2019)
Education
🎓 MSc in Physics, University of Tasmania, Aug 2022
Active Glacier Processes From Machine Learning Applied to Seismic Records
🎓 BSc in Engineering Physics, Columbia University, May 2019
Concentration: Earth and Atmospheric Sciences
Skills
Languages: Python; MATLAB; SQL; qGIS; Unix; HTML, Javascript, CSS; Java; Fortran; Perl; R; shell
Publications
Latto, R., Turner, R. J., Reading, A. M., Winberry, J. P., Kulessa, B., Cook, S., "Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets - Part 2: Unsupervised learning for source process characterization", The Cryosphere, 18, 2081–2101, https://doi.org/10.5194/tc-18-2081-2024, 2024.
Latto, R., Turner, R. J., Reading, A. M., Winberry, J. P., "Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets - Part 1: Event detection for cryoseismology", The Cryosphere, 18, 2061–2079, https://doi.org/10.5194/tc-18-2061-2024, 2024.
Romanou, A., Rind, D., Jonas, J., Miller, R., Kelley, M., Russell, G., Orbe, C., Nazarenko, L., Latto, R., Schmidt, G., “Stochastic Bifurcation of the North Atlantic Circulation Under a Mid-Range Future Climate Scenario with the NASA-GISS Model E.” Journal of Climate, In Revisions, Sept 2022
Latto, R. (2022). Active Glacier Processes From Machine Learning Applied to Seismic Records [MSc Thesis]. University of Tasmania. School of Natural Sciences (Physics).
Turner, R. J., Latto, R., Reading, A.M., “An ObsPy library for event detection and seismic attribute calculation.” Journal of Open Research Software, 2021. http://doi.org/10.5334/jors.365.
Young, E.M., G.E. Flowers, E. Berthier & R. Latto. An imbalancing act: The delayed dynamic response of the Kaskawulsh Glacier to sustained mass loss. Journal of Glaciology, 67(262), 313–330. https://doi.org/10.1017/jog.2020.107, 2020.
Latto, R. and Romanou, A., The Ocean Carbon States Database: a proof-of-concept application of cluster analysis in the ocean carbon cycle, Earth Syst. Sci. Data, 10, 609–626, https://doi.org/10.5194/essd-10-609-2018, 2018.
Presentations
Scientific communication is one of my strongest skills. I presented at my first American Geophysical Union conference in 2014. Since then, I have presented at 15 conferences around the world. In 2018, I convened an international cohort of 5 pioneers in oceanographic research to organize an AGU session on Big Data.
American Geophysical Union
Latto, R., Turner, R. J., Reading, A. M., Cook, S., Winberry, J. P., Kulessa, B., Cook, S., “Unsupervised Learning Applied to Cryoseismic Signals: Identification of Glacier Processes from the Whillans Ice Stream.” Hybrid, oral (Fall Meeting 2021).
Latto, R., Turner, R. J., Reading, A. M., Cook, S., Winberry, J. P., “Event detection for cryoseismology.” Online E-Lightning oral (Fall Meeting 2020).
Young, E.M., Flowers, G. E., Berthier, E., Latto, R., “An imbalancing act: the dynamic response of the Kaskawulsh Glacier, Yukon, Canada, to a changing mass budget.” Oral (Fall Meeting 2020).
Young, E.M., Flowers, G. E., Berthier, E., Latto, R., “Detection and attribution of Kaskawulsh Glacier thinning, southwest Yukon, Canada, 2007-2018.” (Fall Meeting 2019).
Latto, R. (primary convener), Romanou, A., Landschuetzer, P., Telszewski, M., Gregor, L. “Novel data analysis techniques for big data applications in marine science.” Poster (Fall Meeting 2018).
Latto, R., Romanou, A. “The Ocean Carbon States Database: multivariate application of cluster analysis on the ocean carbon cycle.” Poster (Fall Meeting 2018).
Latto, R., Romanou, A. “The Ocean Carbon States Database and Toolbox: Data Mining and Pattern Recognition in Observations and Numerical Simulations of the Ocean Carbon Cycle” Oral presentation in Big Data Session (Ocean Sciences 2018).
Latto, R., Romanou, A. “Ocean Carbon States: Data Mining in Observations and Numerical Simulations Results”. Poster (Fall Meeting 2017).
Malakar, N., Bailey, M., Latto, R., Hulley, G., et al., “Ingesting Land Surface Temperature Differences to Improve Downwelling Solar Radiation Using ANN.” Poster (Fall Meeting 2014).
Local conferences and workshops
Stal, T., Reading, A. M., Cracknell, M. J., Halpin, J. A., Latto, R., Morse, P. E., Turner, R. J., Whittaker, J. M., “Data-driven tectonic regionalization of Antarctica: Appreciate the similarity.” (Australian Earth Sciences Convention 2021).
Latto, R., Turner, R. J., Reading, A. M., “Active Glacier Processes From Machine Learning Applied to Seismic Records.” Online ‘Virtual Display’ (Scientific Committee on Antarctic Research 2020).
Young, E.M., Flowers, G. E., Berthier, E., Latto, R., “Understanding the spatial patterns of Kaskawulsh Glacier thinning between 2007-2018, Yukon, Canada” (IGS Nordic Branch Meeting, Rekholt, Iceland Oct. 2019).
Latto, R., Romanou, A. “The Ocean Carbon States Database: multivariate application of cluster analysis on the ocean.” Poster (Conference for Undergraduate Women in Physics Jan. 2019).
Latto, R., Romanou, A. “Earth Systems Clustering Toolbox: A Standardized Application of Multivariate k-Means Cluster Analysis on the Global Ocean Carbon Cycle.” Poster (Columbia Summer Research Symposium Oct. 2018).
Latto, R., Romanou, A. “Ocean Carbon States Based On K-Means Cluster Analysis”. Poster (Ocean Carbon and Biogeochemistry Summer Workshop June 25-28 2018).
Latto, R. “Understanding the Ocean Carbon Cycle using The k-Means Cluster Analysis Toolbox”. Poster (Columbia Data Science Day Mar. 2018).
Latto, R. “Ocean Carbon States: How to Extract Physically Meaningful Information from Earth System Model Output”. Oral presentation (LDEO Data Science Symposium Mar. 2017).
Latto, R., Romanou, A. “Ocean Carbon States: How to Extract Physically Meaningful Information from Earth System Model Output”. Poster (Columbia Data Science Institute Mar. 2017).
Cordero, L., Malakar, N., Vidal, D., Latto, R., Gross, B., Moshary, F., et al., “A Regional Neural Network estimator of PM2.5…," Poster (American Meteorological Society, Atlanta, GA, USA, 2014).
Get in contact
Email me at beccablatto [at] gmail [.com] or find me on
