Dr. Aurora Schmidt is a senior staff scientist working in the fields of information, control, and signal processing. She has led projects focused on the evaluation of causal inference methods on synthetic social observations and the verification of reliability of artificial intelligence (AI) safety-critical systems. Her research interests include sensor networks, decentralized estimation and coordination problems, compressed sensing, optimization, multi-target tracking and smoothing, information and decision-making, multi-agent planning, formal verification of hybrid systems, machine learning, modeling of information spread in social and sensor networks, computational social science, and causal analysis of population phenomena. Additional areas of expertise include information diffusion, model integration and simulation, network analysis, social media analysis, social network analysis, and sparse signal processing.