Ningjuan Dong

Papers

1

Total Citations

2

H-Index

1

About

Ningjuan Dong is a researcher focused on acoustic signal processing and its applications in intelligent environments. Her work centers on object identification and environmental sensing using sound field analysis, a critical area for advancing AI robotics, security surveillance, and human-computer interaction. Dong’s most notable contribution is the development of a spectral subtraction method applied to acoustic room impulse responses, enabling the identification of objects within a room by analyzing how they perturb the sound field. This technique offers a non-visual, passive approach to object recognition, which is particularly valuable in low-light or obstructed scenarios. While her highly cited paper, "Indoor Object Identification based on Spectral Subtraction of Acoustic Room Impulse Response" (2020), has garnered 2 citations, it represents a foundational step in a niche but growing field. Dong’s work bridges the gap between acoustics and practical engineering, providing a novel framework for robots to perceive their surroundings through sound. Her research holds promise for enhancing the autonomy and safety of AI-driven systems, making her a rising contributor to the intersection of audio processing and smart environment technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Indoor Object Identification based on Spectral Subtraction of Acoustic Room Impulse Response
2 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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