Amin Rahimian

Broadly speaking, Dr. Rahimian’s works are at the intersection of networks, data, and decision sciences and have been published in the Proceedings of the National Academy of Sciences, Nature Human Behaviour, Nature Communications, the Operations Research journal, and the Automatica journal, among others. He borrows tools from applied probability, statistics, algorithms, as well as decision and game theory. Some of his current focus is on the challenges of inference and intervention design in complex, large-scale sociotechnical systems, with applications ranging from online social networks and e-commerce to public health and healthcare delivery. He is especially interested in the critical role that information plays in the operation of sociotechnical systems, particularly related to privacy, fair access, and information integrity (for example, issues of social learning and spread of online harms), in their complex societal contexts.

Dr. Rahimian joined the University of Pittsburgh in the fall of 2020, after a postdoctoral fellowship at MIT Institute for Data, Systems, and Society (IDSS) with a joint appointment at MIT Sloan School of Management. He received his PhD in Electrical and Systems Engineering from the University of Pennsylvania and a Master’s in Statistics from the Wharton School. At Pitt, he leads the Sociotechnical Systems Research Lab and is also affiliated with the Intelligent Systems Program (ISP) and the Institute for Cyber Law, Policy, and Security (Pitt Cyber).

The tools and methodologies developed in his lab address a variety of challenges, such as calibration and downscaling 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, the lab focuses 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 infectious disease immunization to online harm and malign influence campaigns.