Philip A. Etter, Ph.D.

Research Scientist, Meta Reality Labs

Hi! 👋 I'm a computational mathematician working at Meta. I use data science and AI techniques to accelerate high-fidelity computational models. Applications of my research run the gamut from real-time interactive elasticity to extreme multilabel ranking!

About ->

See my work history, research publications, and educational credentials.

Blog ->

See my blog about research in data science, computational mathematics, and other topics.

Tutorials ->

See my collection of mathematics tutorials and explainers.

GitHub ->

See my GitHub projects and experiments.

Education

Stanford University

Ph.D., Computational and Mathematical Engineering

2017 — 2022

Thesis ->

Princeton University

B.A., Mathematics
Minor: Computer Science, Applied Mathematics

2013 — 2017

Thesis ->

Work Experience

Meta

Research Scientist Intern

Summer 2021

Amazon

Applied Data Scientist Intern

Summer 2020

Sandia National Laboratories

Data Scientist Intern

Summer 2018

Google

Software Engineering Intern

Summer 2014

Publications

Operator Shifting for General Noisy Matrix Systems

Philip A. Etter, Lexing Ying

SIAM Journal on Mathematics of Data Science

Blog Post ->Paper Link ->

Operator Shifting for Noisy Elliptic Systems

Philip A. Etter, Lexing Ying

Research in the Mathematical Sciences

Blog Post ->Paper Link ->

Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees

Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Injerjit Dhillon

Proceedings of the ACM Web Conference

Blog Post ->Paper Link ->

Online Adaptive Basis Refinement and Compression for Reduced-Order Models via Vector-Space Sieving

Philip A. Etter, Kevin Carlberg

Computer Methods in Applied Mechanics and Engineering

Blog Post ->Paper Link ->

Coarse-Proxy Reduced Basis Methods for Integral Equations

Philip A. Etter, Yuwei Fan, Lexing Ying

Journal of Computational Physics

Blog Post ->Paper Link ->

Programming Languages