Sherif Haggag

Papers

Total Citations

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About

Sherif Haggag is a researcher whose work sits at the intersection of computer vision, human-computer interaction, and biomedical engineering. His primary research areas include people detection, motion capture, and brain-computer interfaces (BCI), with a strong focus on practical, safety-critical applications. Haggag’s most impactful contribution is his work on body parts segmentation using RGB-D imaging, a method that enables robust detection of humans and their attached props in complex environments. This paper has garnered 22 citations, underscoring its relevance to fields like robotics, ergonomics, and gaming. He also advanced the use of affordable sensor technology, notably through his 2014 study on safety applications using the Microsoft Kinect, which demonstrated how low-cost motion capture systems could be leveraged for real-world safety monitoring—a work cited 19 times. In the domain of neural engineering, Haggag explored prosthetic motor imaginary task classification using single-channel EEG, pushing toward more accessible BCI systems. Collectively, his research bridges the gap between high-cost, specialized equipment and practical, deployable solutions, making him a notable figure in applied computer vision and assistive technology.