Sumaira Manzoor

Sungkyunkwan University

Papers

10

Total Citations

174

H-Index

7

About

Sumaira Manzoor is a leading researcher at the intersection of robotics, artificial intelligence, and cognitive systems, whose work is fundamentally reshaping how autonomous machines perceive, reason, and interact with their environments. Her primary contributions lie in ontology-based knowledge representation for robotic systems, where she has pioneered frameworks that enable robots to process semantic knowledge for more efficient task assistance in domestic, hospital, and industrial settings. Her highly cited survey on ontology-based knowledge representation (54 citations) has become a foundational reference in the field, while her neuro-inspired cognitive navigation framework (41 citations) addresses the longstanding challenge of robotic environment modeling and planning. Manzoor has also made significant advances in edge deployment of deep learning models, developing practical solutions for real-time face mask recognition and pedestrian tracking using Siamese networks. Her comparative studies of traditional machine vision versus modern deep learning approaches for mobile robot object recognition have provided crucial guidance for practitioners. With over 170 total citations across her publications, Manzoor’s work on 3D recognition, human-robot interaction, and adaptive learning control continues to push the boundaries of what autonomous systems can achieve in dynamic, real-world environments.

Research Focus

Key Achievements

7
H-Index
10
Papers
174
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Ontology-Based Knowledge Representation in Robotic Systems: A Survey Oriented toward Applications
54 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Sungkyunkwan University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago