About

Our research team aims at building data-driven experimental computer systems to improve Cybersecurity, User Privacy, and Sustainability of Cyber-Physical Systems (CPS) and the Internet of Things (IoT).

• Our work has also been spanning multiple technical fields, including AI@Edge, Tiny Machine Learning, Federated/Split Learning, and Multi-Agent Reinforcement Learning.
• Recently, we have been looking into  research problems spanning different scales, from the IoT and Edge Computing devices ⇨ smart homes/buildings ⇨ renewable energy systems ⇨ smart grids ⇨ smart cities.
• Our research has been applied into multiple CPS/IoT application domains, including Smart and Connected Communities, Maritime Transportation System, Underwater Cyberinfrastructure, and Personal Home Health Monitoring.
• We open-source all the systems (including their evaluation datasets) we build.

Our research lies at the intersection of Cyber-Physical Systems (CPS), the Internet of Things (IoT), AI@Edge, Distributed Machine Learning, and Security and User privacy. Our research has been published in top-tier CPS/IoT conferences and journals, including IPSN, BuildSys, ICDCS, PerCom, IoTDI, CNS, BigData, SECON, MASS, ICCCN, etc. We  are the recipient of the Best Paper Award at ACM BuildSys’20. Our lab members have served as the organizing committee and technical program committee member for multiple ACM/IEEE CPS/IoT leading conferences and the organizing chair for two IEEE CPS workshops. Our recent research has been supported by NSF CSR Program, NSA, Cyber Florida Seed Program, NSF RET Program, Google Education, NOAA, and NEXUS Seed Grants.