Nuruzzaman Faruqui

Jahangirnagar University, Daffodil International University

Papers

Total Citations

H-Index

About

Nuruzzaman Faruqui is a rising researcher at the intersection of robotics, computer vision, and the Internet of Things (IoT), whose work seeks to bridge the gap between two-dimensional perception and three-dimensional reality. His primary research focuses on enabling machines to understand and interact with human attention and physical space. In a key contribution, Faruqui explored how robots can computationally assess a person’s visual focus of attention, a foundational step for more intuitive human-robot collaboration. His most cited work, “How Can a Robot Calculate the Level of Visual Focus of Human’s Attention” (2020), has garnered 16 citations for tackling this nuanced problem. Building on this, Faruqui addresses a fundamental limitation of conventional imaging: the loss of depth information in 2D pixel matrices. His paper “Trackez: An IoT-Based 3D-Object Tracking From 2D Pixel Matrix Using Mez and FSL Algorithm” (2023) introduces a novel algorithmic approach to extract 3D spatial data from standard 2D sensors, a breakthrough for object tracking in dynamic environments. With 12 citations, this work demonstrates his ability to solve practical, real-world challenges in automation and surveillance. Faruqui’s research is steadily shaping how machines perceive depth and attention, marking him as an innovator to watch in intelligent systems.