Susu Xu, an assistant professor in the Department of Civil and Systems Engineering, focuses on research rooted in mobile sensing, machine learning, urban computing, smart infrastructure systems, and rapid disaster response. Her current projects include developing learning algorithms and incentive mechanisms to improve efficiency of urban crowdsensing networks and collaboration, physics-informed machine learning algorithms to enable smart and fairness-aware urban infrastructure systems, and multi-sourced, multi-modal sensing and learning to enable and enhance rapid disaster response systems.
Applications of Xu’s research target near-real-time disaster information systems for natural hazards (earthquakes, hurricanes, wildfires), spatio-temporal urban sensing and data mining (air pollution, traffic, noise), and large-scale infrastructure monitoring (buildings, bridges, and railway tracks).
Xu is a recipient of multiple awards and honors, including the American Society of Mechanical Engineers (ASME) Structural Health Monitoring (SHM) Best Journal Paper Award in 2022 and 2023, the International Conference on Machine Learning and Applications (ICMLA) Best Paper Award in 2018, the Champion of NeurIPS Adversarial Vision Challenge, and MIT’s Civil and Environmental Engineering Rising Star award. Her research has been sponsored by multiple agencies, including the National Science Foundation (NSF), the United States Geological Survey (USGS), the National Institute of Standards and Technology (NIST), and the Department of Transportation (DOT). Xu has also served as a technical committee member and an organizing committee member in multiple top-tier conferences, including the Association for Computing Machinery (ACM) SenSys, ACM’s BuildSys, Ubicomp, and the American Society of Civil Engineers (ASCE) Engineering Mechanics Institute (EMI) Structural Health Monitoring and Control (SHMC) Conference.
Prior to joining Hopkins faculty in 2024, Xu completed postdoctoral research at Stanford University, served as an assistant professor at Stony Brook University, and a machine learning researcher at Qualcomm AI Research. She holds a PhD in advanced infrastructure systems and an MS in machine learning from Carnegie Mellon University and a BS from Tsinghua University.