Atomic architect. Wrangler of neural nets. Geometry junkie. blondegeek.

Resume / CV

Past Talks

Mischief

Upcoming Travel and Talks

• Center for Computing Research Seminar, Sandia National Laboratory, March 11, 2020, Albuquerque, NM

• Applied Artificial Intelligence Initiative Seminar, UC Santa Cruz, April 1, 2020, Santa Cruz, CA

• Physics Informed Machine Learning Minisymposium, SIAM Conference on Mathematics of Data Science, May 6, 2020, Cincinnati, OH

Code

• e3nn_tutorial: Tutorial on Euclidean symmetry equivariant neural networks

  This tutorial uses a combination of slides and interactive jupyter notebooks using the se3cnn framework to present fundamental concepts about Euclidean equivariant neural networks: data types, equivariant operations, how symmetry effects simple tasks, and how to construct the building blocks of se3cnn. This tutorial was originally presented at IPAM at UCLA on November 14, 2019.

• Euclidean Neural Networks

  Convolutional neural networks for point clouds and voxels with Euclidean symmetries (3D translation and 3D rotation). The current code (on the point branch) is a merger of the work from Tensor field networks and 3D Steerable CNNs.

Recent publications

• Tensor Field Networks

  code: paper repo / recent – se3cnn

• An Automatically Curated First-Principles Database of Ferroelectrics (under review)

  code:
  pymatgen.analysis.ferroelectricity /
  atomate…workflow…ferroelectric
  
  data:
  ferroelectric_search_site
  figshare data deposit