Projects

Creating the AI-enabled lab for a new era of reproducible and collaborative experimentation

Leveraging AI foundation models and multi-cloud computing to usher in a new era of reproducible and collaborative experimentation for scientific discovery.

A library that provides high-speed training of popular machine learning models on modern CPU/GPU computing systems.

An automated explainable bioinformatics and AI workflow for multi-omic, climate and environmental data, applied to sustainability problems e.g., nature-based carbon capture.

AutoML for incremental machine learning algorithms for big time-series data.

Developing AI and analytics to understand the drivers of study or clinical trial efficiency.

Analyzing and visualizing differences in blood flow patterns, made visible with fluorescent dyes and multispectral imaging.

Using Logical Neural Networks to demonstrate the benefit of incorporating knowledge and reasoning into neural network learning