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About

Gelareh Mohammadi is a leading researcher at the intersection of human-computer interaction, cognitive science, and embodied AI, whose work focuses on making robots and virtual agents more natural communicators. Her primary research areas include speech-driven gesture generation, cognitive load measurement in interface design, and nonverbal behavior synthesis for embodied agents. Mohammadi’s most significant contribution is her pioneering work on generating realistic, speech-coordinated gestures for social robots and virtual agents. Her 2021 scoping review on speech-based gesture generation (29 citations) established a comprehensive framework for the field, while her 2023 Speech-Gesture GAN paper introduced a novel generative adversarial network approach that enables agents to produce human-like gestures synchronized with speech—a breakthrough for natural human-robot interaction. In her 2024 work on cognitive load measurement (8 citations), she developed practical guidelines and a framework for using cognitive load metrics to evaluate interface usability, bridging cognitive science and HCI design. Mohammadi’s research has direct implications for assistive robotics, virtual assistants, and interactive AI systems, and her work is increasingly cited by researchers in both robotics and human-computer interaction communities. Her innovative combination of deep learning, cognitive psychology, and robotics positions her as a rising authority in creating more intuitive, human-like embodied agents.