About
Ian Hutchins uses quantitative analysis of information networks and machine learning to find ways to improve the research enterprise and accelerate biomedical research advances. His work studies how scientific ideas move through citation networks, how basic discoveries translate into clinical and technological impact, and how funders can use evidence to understand risks and opportunities in research portfolios.
Before joining UW-Madison, he worked as a data scientist at NIH, where he developed the iCite bibliometrics dashboard, the Relative Citation Ratio and related quantitative metrics, and the NIH Open Citation Collection. He also spearheaded development of the NIH COVID-19 Portfolio to track and disseminate COVID-19 research in real time. Ian is a returning Badger with a PhD in Neuroscience from UW-Madison.
Research Areas
- Scientific portfolio analysis for funders and research agencies
- Biomedical knowledge flow and translational progress
- Causal and substantive citation prediction
- Preprints, peer review, and evidence stability
- Open citation data, iCite, RCR, and responsible article-level metrics