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About

Kiana Ehsani is a leading researcher in embodied AI and robotics, whose work bridges the critical gap between simulated training and real-world deployment. Her key contributions center on developing robust, generalizable robot policies that can operate effectively in chaotic, unstructured human environments. Ehsani’s most influential work, *Phone2Proc* (2023, 9 citations), introduces a practical method for creating realistic simulation environments from a simple smartphone scan, enabling embodied agents to train in simulation and then transfer seamlessly to the physical world. She further advanced the field with *ManipulaTHOR* (2021, 7 citations), a foundational framework for visual object manipulation that set new standards for interactive agent tasks. Her recent innovations include *Promptable Behaviors* (2024, 6 citations), which personalizes multi-objective robot rewards from human preferences, and *Manipulate-Anything* (2024, 5 citations), which leverages vision-language models to automate real-world robot control. Ehsani’s work on *FLaRe* (2025, 6 citations) demonstrates how large-scale reinforcement learning fine-tuning can achieve masterful, adaptive robot policies. Through these contributions, she has established herself as a pivotal figure in making robots truly capable of navigating and manipulating our everyday world.