Samama Tahir

University of Engineering and Technology Taxila

Papers

Total Citations

H-Index

About

Samama Tahir is a researcher whose work sits at the intersection of wearable computing and human-activity understanding. Her primary research areas include human-object interaction (HOI) recognition, inertial sensing, and context-aware systems. Her most cited paper, “Recognizing Human-Object Interaction (HOI) Using Wrist-Mounted Inertial Sensors” (2020, 6 citations), introduces a novel approach to detecting and classifying interactions by leveraging data from wrist-worn sensors—a method that avoids the privacy and lighting limitations of camera-based systems. This contribution is particularly significant for applications in security, surveillance, robotics, and health monitoring, where unobtrusive and continuous sensing is critical. While still early in her career, Tahir’s work demonstrates a clear focus on practical, deployable solutions for real-world sensing challenges. Her research bridges the gap between low-cost hardware and high-level semantic understanding, offering a pathway toward more intuitive human-machine interfaces. As wearable technology continues to proliferate, Tahir’s contributions to inertial-based HOI recognition position her as a promising voice in the future of ubiquitous and context-aware computing.