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@ICESAT-2HackWeek @ODINN-SciML @geostacks @PolarWandering @Machine-Learning-in-Glaciology-Workshop @UCB-stat-159-s23 @Fermat-distance @CryoInTheCloud

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facusapienza21/README.md

Hello, I'm Facundo (Facu) Sapienza πŸ‘‹!

I am a postdoctoral researcher at the Standord Icy Physics Group wotrking with Ching-Yao Lai. Previosly I completed my PhD in the Department of Statistics at the University of California Berkeley working under the supervision of Fernando PΓ©rez and Jonathan Taylor. I finished my Bsc/Msc (Licenciatura) in Physics and Mathematics in the University of Buenos Aires πŸ‡¦πŸ‡·.

  • πŸ”­ I’m currently working on:
    • 🧊 ODINN.jl: Global glacier model using Universal Differential Equations for climate-glacier interactions. Integrating the Julia differential programming tools with the Open Global Glacier Model (OGGM) in Python.
    • 🌎 PolarWandering: Statistical modelling of Paleomagnetic data.
  • 🌱 I’m currently learning about sensitivity methods for differential equations. Interested in participating? Check out our review paper!
  • πŸ‘¨β€πŸ« I am interested in teaching machine learning for geophysisc and good practices fordeveloping open, reproducible and collaborative scientific software.
  • πŸ‘― I’m looking to collaborate with people interested in the intersection between machine learning, geophysics and scientific computing.
  • πŸ“« How to reach me: feel free to send me an email to sapienza@stanford.edu.
  • πŸ˜„ Pronouns: He/Him

Pinned Loading

  1. ODINN-SciML/ODINN.jl ODINN-SciML/ODINN.jl Public

    Global glacier model using Universal Differential Equations for climate-glacier interactions

    Julia 70 11

  2. PolarWandering/PaleoSampling PolarWandering/PaleoSampling Public

    Quantitative Analysis of Paleomagnetic Sampling Strategies

    Jupyter Notebook 7 3

  3. ODINN-SciML/DiffEqSensitivity-Review ODINN-SciML/DiffEqSensitivity-Review Public

    A Review of Sensitivity Methods for Differential Equations

    TeX 29 14

  4. optimaladj optimaladj Public

    This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.

    Python 11 1

  5. Fermat-distance Fermat-distance Public

    We propose a density-based estimator for weighted geodesic distances suitable for data lying on a manifold of lower dimension than ambient space and sampled from a possibly nonuniform distribution

    Python 15 3

  6. ODINN-SciML/SphereUDE.jl ODINN-SciML/SphereUDE.jl Public

    A Julia package for regression in the sphere based on Universal Differential Equations

    Julia 2 3