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About

Peishan Cong is pioneering the integration of 3D vision and natural language for real-world, dynamic environments. Her research centers on two transformative areas: non-intrusive biometric identification and multi-modal 3D scene understanding. Cong’s seminal work on LiDAR-based gait recognition, published in 2022, demonstrates how single-sensor depth data can reliably identify individuals by their walking patterns, achieving 10 citations and laying the groundwork for privacy-preserving security and healthcare monitoring. More recently, she introduced **WildRefer**, a groundbreaking framework for 3D object localization in large-scale, dynamic scenes using natural language descriptions alongside multi-modal data (2D images and 3D LiDAR point clouds). This work, presented in 2023 and 2024, tackles the immense challenge of grounding objects in unconstrained outdoor settings, earning a combined 7 citations. By fusing rich appearance cues from images with precise spatial information from LiDAR, Cong enables machines to understand complex environments through human-like queries. Her contributions are vital for advancing autonomous navigation, augmented reality, and interactive AI systems, positioning her as a rising leader in embodied vision and language-guided perception.