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About

Mahdi TaherAhmadi is a robotics and artificial intelligence researcher whose work sits at the intersection of human motion prediction, autonomous robot navigation, and human-robot interaction. His most recognized contribution is the development of STPOTR (Simultaneous Trajectory and Pose Transformer), a novel non-autoregressive transformer architecture designed to simultaneously predict human trajectory and pose, enabling robots to anticipate and follow human movement with greater accuracy and speed. This work, which has accumulated 25 citations since its 2023 publication, represents a significant advancement in the robot follow-ahead problem — a challenging task requiring real-time, accurate forecasting of where a person is headed. TaherAhmadi has also contributed to the field through the creation of SFU-Store-Nav, a multimodal dataset capturing human gestures, movements, and navigation behaviors in indoor environments, providing the research community with valuable data for training and evaluating human-robot interaction systems. His body of work reflects a consistent focus on bridging the gap between human behavior understanding and practical robotic deployment, making robots more intuitive and responsive companions in everyday environments. His research has meaningful implications for assistive robotics, autonomous navigation, and intelligent systems design.