Prof. B. Ian Hutchins
September 29 @ 12:30 pm - 1:30 pm
Reshaping the Research Enterprise
Research has entered a phase of “hypercompetition”; current organizations and policies are straining under this pressure. Scientists seeking to remain competitive depend on publishing in artificially scarce space in prestigious journals. I transitioned from biomedical research into data-driven decision-making in order to build analytical tools that can be used to inform evidence-based policy responses to these challenges, and designed my methods such that they can also be used by scientists to communicate the impact of their work regardless of publication venue. I will discuss the network science behind my measure of scientific influence, and the machine learning system I developed to predict early stages of bench-to-bedside translation – a crucial goal of applied biomedical research. These metrics provide researchers with two additional ways to showcase their work’s influence, and are increasingly driving policy-making discussions at federal agencies as the research enterprise responds to modern pressures. Since starting my lab at UW-Madison in 2020, I have continued my research into policy-relevant analytical approaches. I will also discuss my new work analyzing the causality of information flow, the reliability of data reported in preprints, and avenues to improve scientific knowledge dissemination.