Ariane Ducellier

Ariane Ducellier

Research scientist

Ariane Ducellier

I am interested in statistical analysis and time series forecasting, and more broadly data science using complex data across space and time.

Currently, I am developing mathematical and statistical methods and codes for population health statistical surveys at the Institute for Health Metrics and Evaluation (IHME).

Previously, I was working on forecasting housing market indicators at Zillow.

Before that, I worked on low-frequency seismic data and numerical inversion of earthquake models at University of Washington and the French Geological Survey (BRGM).

News

  • Fall 2025: I am teaching a course on Data Visualization with R in the Department of Statistics at University of Washington.

  • August 2025: The version 0.2.0 of the raking package is now available on PyPI.

  • July 2025: I presented my work on raking methods and applications to health metrics at the International Conference on Continuous Optimization (ICCOPT) in Los Angeles, California, USA, and at the SIAM Annual Meeting in Montreal, Quebec, Canada.

  • December 2025: I presented my work on raking with inequality constraints at the IMS International Conference on Statistics and Data Science (ICSDS) in Nice, France.

  • November 2024: The version 0.1.0 of the new raking package is now available on PyPI.

  • Fall 2024: I am teaching a course on Data Visualization with R in the Department of Statistics at University of Washington.

  • August 2024: I presented my work on the uncertainty quantification of survey calibration at the Joint Statistical Meetings (JSM) in Portland, Oregon, USA.

  • May 2024: I received a travel award from the American Statistical Association to attend the 2024 Joint Statistical Meetings (JSM) in Portland, Oregon, USA.

  • March 2024. I was awarded a University of Washington Data Science Postdoctoral Fellowship from the eScience Institute.

  • Fall 2023: I have taught a course on Data Visualization with R in the Department of Statistics at University of Washington.

  • July 2023: I have participated in the Causal Inference with Observational Data program of the Summer Institute in Statistics for Clinical & Epidemiological Research (SISCER).

  • August 2022: My research paper “Detection of slow slip events using wavelet analysis of GNSS recordings”, co-authored with Kenneth Creager and David Schmidt, was published in Bulletin of the Seismological Society of America.

  • July 13th 2022: I presented my work on “Long-range dependence in low-frequency earthquake catalogs” at SIAM Conference on Mathematics of Planet Earth (slides).

  • June 8th 2022: I presented my work on “Long-range dependence in low-frequency earthquake catalogs” at the American Statistical Association Symposium on Data Science and Statistics in Pittsburgh, PA, USA (abstract and poster).

  • May 20th 2022: I presented my work on “Long-range dependence in earthquake occurrence rates” at the SIAM Pacific Northwest Biennal Meeting in Vancouver, WA, USA (slides).

  • April 22nd 2022: I presented my work on “Statistical analysis of low-frequency earthquake catalogs” at the SSA Annual Meeting in Bellevue, WA, USA (slides).

  • April 2022: My research paper “An eight-year-long low-frequency earthquake catalog for Southern Cascadia”, co-authored with Kenneth Creager, was published in Journal of Geophysical Research: Solid Earth.

  • January 28th 2022: I defended my PhD thesis on “Slow earthquakes: Tremor, low-frequency earthquakes and slow slip events” in the Department of Earth and Space Sciences at University of Washington.

  • January 2022: My research paper “Depth and thickness of tectonic tremor in the northeastern Olympic Peninsula”, co-authored with Kenneth Creager, was published in Journal of Geophysical Research: Solid Earth.

  • December 2021: I graduated with a Master of Science from the Department of Statistics at University of Washington.