Qianwen Chao

Harvard University, Chinese University of Hong Kong

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About

Qianwen Chao is a researcher whose work bridges the frontiers of crowd simulation and micro-robotic swarm control. Her key research areas include data-driven optimization for dynamic systems and the actuation of micro-scale robotic collectives. In her most-cited work, "Velocity-based dynamic crowd simulation by data-driven optimization" (2022, 11 citations), she introduced a novel approach that leverages real-world data to generate realistic, collision-free pedestrian flows, significantly advancing the realism and efficiency of virtual crowd modeling. Her earlier seminal contribution, "Steering micro-robotic swarm by dynamic actuating fields" (2016, 9 citations), presents a general solution for controlling the motion of micro-robots through time-varying actuating fields. This work automatically computes the optimal sequence of field directions, enabling precise, coordinated swarm movement—a breakthrough with implications for targeted drug delivery and micro-assembly. Chao’s research demonstrates a unique ability to apply optimization principles across vastly different scales, from macroscopic crowds to microscopic swarms. Her work has earned recognition for its interdisciplinary impact, influencing both computer graphics and robotics communities.