Sebastian Wagner-carena
Flatiron Research Fellow
United States
Summary
👤
Senior🎓
Top SchoolSebastian Wagner-carena is a Flatiron Research Fellow and postdoctoral researcher who applies advanced machine learning to cutting-edge problems in cosmology and astrophysics. With eight years of experience spanning Google, DeepMind, NYU, and Stanford, he builds high-performance, differentiable simulators and explores theoretical limits of neural networks for strong lensing and other cosmological inference tasks. His work bridges research and engineering—producing JAX-powered simulators that run in milliseconds and contributions that catalyzed collaborations between industry and academia. Trained at Harvard (AB) and Stanford (PhD in Physics), he keeps code openly available on GitHub and maintains a growing publication record that emphasizes both practical tooling and foundational ML for the sciences.
8 years of coding experience
3 years of employment as a software developer
Bachelor’s Degree, Concentration in Physics/Mathematics with Secondary in Computer Science, Bachelor’s Degree, Concentration in Physics/Mathematics with Secondary in Computer Science at Harvard UniversityDoctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Stanford University
English, Spanish, French
Github Skills (33)
cosmology10
hierarchical10
autoencoder10
astronomy9
simulation9
astrophysics9
bayesian9
modeling9
inference8
probabilistic-graphical-models8
sublime-text8
pix7
neural-network7
sublime7
machine-learning6
Programming languages (3)
Github contributions (5)
swagnercarena/paltax
Apr 2024 - Feb 2025
Contributions:1 release, 12 reviews, 14 PRs in 10 months
swagnercarena/hgmca
Dec 2019 - Jan 2021
A hierarchical component separation algorithm based on sparsity in the wavelet basis.
Contributions:88 commits, 12 PRs, 74 pushes in 1 year 1 month
wavelethierarchicalsparsitybasisseparation
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