Papers

17

Total Citations

360

H-Index

9

About

Md. Zia Uddin is a prominent researcher specializing in assistive technologies, human activity recognition, and intelligent care systems, with a particular focus on leveraging sensor technologies and deep learning to support elderly populations. His most-cited work, a 2018 survey on ambient sensors for elderly care and independent living (164 citations), established him as a leading voice in smart home healthcare technology, comprehensively mapping how sensor-based systems can enhance the safety and autonomy of older adults. Building on this foundation, Uddin has pioneered the application of ultra-wideband radar sensing and deep learning for activity recognition and in-home emergency detection, offering non-invasive alternatives to camera-based surveillance. His research portfolio also encompasses gait recognition, smartphone-based activity monitoring using recurrent neural networks, and semi-autonomous rescue robotics for disaster scenarios. In recent years, Uddin has turned his attention to the critical intersection of privacy and human-robot interaction, contributing datasets and frameworks that balance monitoring utility with user privacy in care robotics. His work also thoughtfully engages with ethical dimensions of robot-assisted elder care. Collectively, his contributions reflect a coherent and socially conscious research agenda that bridges machine learning innovation with real-world humanitarian impact.

Research Focus

Key Achievements

9
H-Index
17
Papers
360
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Ambient Sensors for Elderly Care and Independent Living: A Survey
164 citations · 2018
📈 Most Prolific Year: 2018 (4 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: University of Oslo, SINTEF, International Islamic University Chittagong, Sungkyunkwan University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago