AI4PFAS
Deep learning workflow and dataset for toxicity prediction.

Cost-aware computing
Automating cost-aware profiling, prediction, and provisioning of cloud and HPC resources.

Clouds
Self-supervised data-driven methods for the application on big satellite clouds imagery

CODAR
We develop methods for online data analysis and reduction on exascale computers

Colmena
Machine Learning-Based Steering of Ensemble Simulations

Flows
We are developing methods to automate the scientific data lifecycle.

Foundry
An open source machine learning platform for scientists

funcX
funcX is a Function as a Service platform for scientific computing.

Garden
Garden turns researchers' AI models into citable APIs that run on scientific computing infrastructure.

Gladier
Globus Automation for Data-Intensive Experimental Research

Scientific Language Modeling and Information Extraction
Data mining from literature with a foundational science-focused language model

KAISA: Scalable Second-Order Deep Neural Network Training
KAISA is a novel distributed framework for training large models with K-FAC at scale.

The Materials Data Facility
We are creating data services to help materials scientists publish and discover data

Parsl
Parallel programming library for Python

ProxyStore
A data fabric for high-performance, multi-site workloads facilited by transparent object proxies.

SZ3 Compression
We develop a series of prediction-based lossy compression algorithms for scientific simulations.

Whole Tale
Whole Tale is a cloud-hosted platform for conducting and sharing reproducible science