The Center for Artificial Intelligence Foundations and Scientific Applications (CENSAI) aims to foster collaborative, interdisciplinary research across Penn State and beyond aimed at addressing the AI grand challenge of accelerating scientific progress through synergistic advances across multiple areas of AI, including:
- Literature-based discovery, e.g., extraction, annotation, reconciliation, integration, and validation of scientific claims, hypotheses, and supporting and opposing evidence from the literature
- Scientific knowledge representation, e.g., frameworks for encoding, communicating, and reasoning with models or abstractions of scientific domains, scientific artifacts (data, experiments, hypotheses, models, scientific arguments, etc.);
- Experiment planning and optimization, e.g., based on the scientific goals, cost of experiments, expected value of information, etc.
- Machine learning and causal inference, including methods that incorporate prior knowledge, e.g., from physics, explain the learned models and their predictions,
- Human-AI collaboration needed for AI-enabled collaborative science, using algorithmic abstractions as the medium for interdisciplinary collaboration.
View the CENSAI announcement video:
CENSAI is based in the Institute for Computational and Data Sciences (ICDS) and is part of Penn State’s University-wide AI initiative coordinated by ICDS.