Allan Wang

Carnegie Mellon University, National Museum of Emerging Science and Innovation

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About

Allan Wang is a researcher at the intersection of social robotics, human-robot interaction, and assistive technology. His work spans two interconnected themes: improving how robots understand and navigate human environments, and designing robot systems that meaningfully empower people with visual impairments. Wang's early contributions focused on predicting pedestrian group dynamics — specifically, how groups split and merge in crowds — using 3D convolutional networks. This work, his most-cited with 17 citations, directly advances mobile robot navigation in complex social settings. He has also contributed to large-scale pedestrian data collection infrastructure, recognizing that richer datasets are foundational to progress in social navigation research. More recently, Wang has turned toward accessibility, developing WanderGuide, a map-less indoor robotic guide that enables blind users to recreationally explore environments through conversational image descriptions — a system that has already garnered 12 citations since its 2025 publication. Complementing this, his work on shared control challenges the "omakase" paradigm in assistive robotics, advocating for greater user agency rather than passive reliance on automation. Together, Wang's research advances a vision of robots that are not only socially intelligent but genuinely inclusive.