We develop Artificial Intelligence (AI) approaches that use knowledge to accelerate and innovate scientific discovery processes that are unnecessarily carried out manually and inefficiently today.
We work on a variety of AI research areas, such as semantic workflows, human-guided machine learning, interdisciplinary model integration, knowledge networks, controlled crowdsourcing of metadata, and automated hypothesis-driven discovery. A key theme in our projects is the use of AI technologies for different aspects of data science processes in order to make them more efficient.
We collaborate with scientists in diverse areas including Earth sciences, neuroscience, genomics and proteomics, agriculture, and economics.
We are always looking for collaborators including exceptional students who are passionate about AI and scientific research.