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About

Qiaozi Gao is a leading researcher in embodied AI, focusing on the intersection of language, vision, and robotic manipulation. Their work centers on enabling robots to understand and execute complex, language-guided tasks in real-world environments, with a particular emphasis on multi-agent collaboration and physical reasoning. Gao's most impactful contribution is **Embodied BERT (EmBERT)** (2021, 30 citations), a transformer model that grounds natural language instructions in visual observations to guide robots through home and office tasks, addressing a core challenge in embodied reasoning. They also pioneered research in naive physical action-effect prediction (2018, 17 citations), helping artificial agents understand basic cause-and-effect relationships in the physical world. Gao has made significant strides in multi-robot systems with **LEMMA** (2023, 8 citations), a benchmark for language-conditioned multi-robot manipulation, and **CH-MARL** (2022, 6 citations), a multimodal benchmark for cooperative heterogeneous multi-agent reinforcement learning. Notably, Gao led the development of **Alexa Arena** (2023, 3 citations), a user-centric simulation platform that democratizes embodied AI research, and played a key role in launching the first **Alexa Prize SimBot Challenge**, bridging conversational AI with physical robotics. Their work consistently pushes the boundaries of how robots perceive, reason, and act in human environments.