Skip to main content

Talk Title: Understanding Success and Failure in Science and Technology

Talk Abstract: The 21st century society is largely driven by science and innovation, but our quantitative understanding of why, how, and when innovators and innovations succeed or fail remains limited. Despite the long-standing interest in this topic, current science of science research relies on citation and publication records as its major data sources. Yet science functions as a complex system that is much more than published papers, and ignorance of this multidimensional nature precludes a deeper examination of many fundamental elements of innovation lifecycles, from failure to scientific breakthrough, from public funding to broad impact. In this talk, I will touch on a few examples of success and failure across science and technology, hoping to illustrate a way for a better understating of the full innovation lifecycle. By combining various large-scale datasets and interdisciplinary analytical frameworks rooted in data mining, statistical physics, and computational social science, we discover a series of fundamental mechanisms and signals underlying the processes in which (1) individuals and organizations build on previous repeated failures towards ultimate victory or defeat in science, startups and security; (2) scientific elites produce breakthrough discoveries in their scientific careers; and (3) scientific research gets funded and used by the general public. The uncovered patterns in these studies not only unveil regularity and predictability underlying the often-noisy social systems, they also offer a new theoretical and empirical basis that is practically relevant for individual scientists, research institutes, and innovation policymakers.

Bio: Yian Yin is a Ph.D. candidate of Industrial Engineering & Management Sciences at Northwestern University, advised by Dashun Wang and Noshir Contractor. He also holds affiliations with Northwestern Institute on Complex Systems and Center for Science of Science and Innovation. Prior to joining Northwestern, he received his bachelor degrees in Statistics and Economics from Peking University in 2016.

Yian studies computational social science, with a particular focus on integrating theoretical insights in innovation studies, computational tools in data science, and modeling frameworks in complex systems to examine various fundamental elements of innovation lifecycles, from dynamics of failure to emergence of scientific breakthrough, from public funding for science to broad uses of science in public domains. His research has been published in multidisciplinary journals including Science, Nature, Nature Human Behaviour, and Nature Reviews Physics, and has been featured in Science, Lancet, Forbes, Washington Post, Scientific American, Harvard Business Review, MIT Technology Review, among other outlets.