Shuang Bai

Tianjin University, PolarOnyx (United States)

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About

Shuang Bai’s research bridges the frontiers of robotics and biomedical instrumentation, with a focus on multi-robot systems for environmental sensing and the development of intelligent surgical tools. In the domain of chemical plume tracing, Bai pioneered the use of a Probability-PSO algorithm for multi-robot odor source localization in ventilated indoor environments—a foundational contribution that has garnered 28 citations and demonstrated how swarm intelligence can solve real-world gas detection challenges. Bai further advanced this field by introducing a three-step odor source declaration method using multiple robots, which integrates robot convergence, concentration persistence, and mass throughput analysis (15 citations), and by proposing the concept of a virtual odor-source-probability sensor to maximize the utility of wind and concentration data (2 citations). Equally innovative is Bai’s work on a laser-induced breakdown spectroscopy (LIBS) guided smart surgical tool (21 citations), which employs a femtosecond fiber laser and real-time atomic emission analysis for material identification during surgery—a breakthrough that promises to enhance precision in operating rooms. Through these contributions, Bai has demonstrated a remarkable ability to apply probabilistic algorithms and spectroscopic sensing across distinct fields, earning recognition for both theoretical depth and practical impact.