At the Sociotechnical Systems Research lab, we target questions that help society navigate the age of data. On the one hand, the landscape for scientific research is itself changing: The combined force of high-end data analytics and high-performance computing opens new ways for scientific discovery; more and more data from various sources and in novel forms are available to facilitate scientific inquiries. On the other hand, to overcome the trust barriers and embrace the increasing role of data and algorithms in our lives, we need a scientific understanding of the algorithmic, data-driven and platform-based economies that algorithms enable. The lab’s research into large scale sociotechnical systems should help society in this transition by deepening an understanding of the emerging, data-enabled infrastructure within their societal context.

On the methodological side, we face a variety of challenges such as calibration and down-scaling of massive models with costly data for granular predictions, optimizing and locally targeting large-scale interventions, and making inferences about local interactions and micro mechanisms from observation of meso-scale behaviors and macro trends. With ongoing support from NSF, DOD and HHS, we focus our efforts on pressing societal problems and issues of national concern, ranging from interventions to improve education, health and welfare among vulnerable populations, human-machine teaming in mission critical applications, the opioid epidemic and COVID-19 pandemic to misinformation and malign influence campaigns.