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About

Jennifer Leaf is a robotics and human-robot interaction researcher whose work spans two interconnected domains: swarm robotics and assistive technology. She has made notable contributions to understanding how human operators collaborate with robotic collectives — biologically inspired multi-robot systems capable of emergent, decentralized intelligence — with a particular focus on transparency and visualization design. Her research investigates how interface design and system transparency influence the effectiveness of human-collective teams in high-stakes applications such as environmental monitoring, disaster response, and infrastructure support. Her most-cited work, "Human-collective visualization transparency" (2021, 8 citations), reflects her sustained commitment to making complex collective robotic systems more interpretable and accessible to human partners. Beyond swarm robotics, Leaf has championed socially impactful engineering education, leading an undergraduate service learning project (2018, 5 citations) that deployed humanoid robots to enhance therapy for children with autism spectrum disorder — broadening engineering students' perspectives beyond traditional industrial applications. Her continued investigation into site layout effects on collective decision-making further demonstrates her evolving research agenda. Leaf's work collectively bridges technical rigor with human-centered design, positioning her as a thoughtful voice in the future of human-robot teaming.