Papers

3

Total Citations

188

H-Index

3

About

Sheikh Badar ud din Tahir is a leading researcher in wearable sensor technologies and human activity recognition, with a focus on developing intelligent systems for healthcare and human-computer interaction. His most cited work, "Wearable Inertial Sensors for Daily Activity Analysis Based on Adam Optimization and the Maximum Entropy Markov Model" (2020, 118 citations), introduced a novel machine learning framework that significantly improved the accuracy of daily activity monitoring for elderly care. Building on this, his 2021 paper on "Monitoring Real-Time Personal Locomotion Behaviors Over Smart Indoor-Outdoor Environments Via Body-Worn Sensors" (66 citations) advanced the field by enabling seamless tracking of physical activities across diverse environments, with applications in health tracking, surveillance, and assistive robotics. His recent work on "Hand gesture recognition via deep data optimization and 3D reconstruction" (2023) extends his expertise into gesture-based interaction, promising impacts in virtual reality and medical diagnostics. Through his innovative integration of optimization algorithms and probabilistic models, Tahir has established himself as a key contributor to the development of smart, wearable systems that enhance independent living and human-machine communication.

Research Focus

Key Achievements

3
H-Index
3
Papers
188
Total Citations
63
Avg Citations/Paper
🏆 Most Cited Paper
Wearable Inertial Sensors for Daily Activity Analysis Based on Adam Optimization and the Maximum Entropy Markov Model
118 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Air University, Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago