Research integrity
How can we identify manipulation and evaluate the reliability of the scientific record? We study image and data tampering, questionable journals, and integrity in AI-generated scientific content.
Explore integrity researchPeer review & computational discovery
We develop and study computational methods for scientific peer review, recommendation, and knowledge extraction, including language models, reinforcement learning, and multimodal representations.
Explore peer review & discoveryThe science of science
We examine how funding, mentorship, collaboration, and socioeconomic diversity shape science and innovation, and how biases enter the research ecosystem and artificial intelligence.
Explore the science of scienceFunding sources
Our research has been supported by the following organizations and programs.
National Science Foundation
The impact of socioeconomic diversity on science and innovation
Venture Partners at CU Boulder & OEDIT Advanced Industries Program
ReviewerZero.ai—An artificial intelligence technology suite to ensure research integrity in scientific publications
Sloan Foundation
Does Government Funding Change What You Do? The Effects of Funding on the Direction and Impact of Academic Energy Research
Office of Research Integrity, DHHS
Computational Research Integrity Conference (CRI-CON), conference grant
Office of Research Integrity, DHHS
Human-centered automatic tracing, detection, and evaluation of image and data tampering
Office of Research Integrity, DHHS
Methods and tools for scalable figure reuse detection with statistical certainty reporting
National Science Foundation
Collaborative proposal: Social dynamics of knowledge transfer through scientific mentorship and publication
National Science Foundation
Optimizing scientific peer review
National Science Foundation
EAGER: Improving scientific innovation by linking funding and scholarly literature
DARPA
SCORE project (subcontractor)