Brandon M. Wood

Research Scientist, FAIR at Meta

I’m a research scientist on the FAIR chemistry team in San Francisco. My research lies at the intersection of deep learning, chemistry/physics, and large scale computing. Lately, I have been working on generalizable machine learning potentials and generative models for molecules and materials. Prior to joining FAIR, I was a postdoctoral fellow at NERSC and I completed my PhD with Kristin Persson at UC Berkeley. If you would like to get in touch you can reach me at bmwood@meta.com.

Research

(Selected Publications)

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models

Luis Barroso-Luque, Muhammed Shuaibi, Xiang Fu, Brandon M. Wood, Misko Dzamba, Meng Gao, Ammar Rizvi, C. Lawrence Zitnick, Zachary W. Ulissi

Preprint 2024

Paper Dataset Models Code

FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions

Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood

NeurIPS 2024

Paper Code

FlowMM: Generating Materials with Riemannian Flow Matching

Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M. Wood

ICML 2024

Paper Code

From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction

Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary W. Ulissi, C. Lawrence Zitnick, Brandon M. Wood

ICLR 2024

Paper Code

EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Yi-Lun Liao, Brandon M. Wood, Abhishek Das, Tess Smidt

ICLR 2024

Paper Code

AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials

Janice Lan, Aini Palizhati, Muhammed Shuaibi, Brandon M. Wood, Brook Wander, Abhishek Das, Matt Uyttendaele, C. Lawrence Zitnick, Zachary W. Ulissi

npj Comput. Mater. 2023

Paper Code

The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts

Richard Tran, Janice Lan, Muhammed Shuaibi, Brandon M. Wood, Siddharth Goyal, Abhishek Das, Javier Heras-Domingo, Adeesh Kolluru, Ammar Rizvi, Nima Shoghi, Anuroop Sriram, Felix Therrien, Jehad Abed, Oleksandr Voznyy, Edward H. Sargent, Zachary Ulissi, C. Lawrence Zitnick

ACS Catalysis 2023

Paper Dataset Code

Spherical Channels for Modeling Atomic Interactions

C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary Ulissi, Brandon M. Wood

NeurIPS 2022

Paper Code

Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations

Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick

ICLR 2022

Paper Code

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

Lowik Chanussot, Abhishek Das, Siddharth Goyal, Thibaut Lavril, Muhammed Shuaibi, Morgane Riviere, Kevin Tran, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Aini Palizhati, Anuroop Sriram, Brandon M. Wood, Junwoong Yoon, Devi Parikh, C. Lawrence Zitnick, Zachary Ulissi

ACS Catalysis 2021

Paper Dataset Code