Navid Sarhangnejad

University of Toronto

Papers

1

Total Citations

20

H-Index

1

About

Navid Sarhangnejad is a leading innovator in computational imaging and CMOS image sensor design, whose work is reshaping how cameras capture and process visual information. His research centers on advanced pixel architectures for single-frame computational photography, with key contributions to coded-exposure imaging and 3D sensing technologies. Sarhangnejad’s most cited work, “5.5 Dual-Tap Pipelined-Code-Memory Coded-Exposure-Pixel CMOS Image Sensor for Multi-Exposure Single-Frame Computational Imaging” (2019, 20 citations), introduces a groundbreaking dual-tap pixel design with pipelined code memory that enables programmable, multi-exposure capture within a single frame. This innovation directly addresses the growing demands of modern applications such as 3D sensing, gesture analysis, and robotic navigation, where conventional cameras fall short. By allowing individual-pixel-level exposure coding, his sensor architecture achieves unprecedented flexibility for computational photography without sacrificing speed or resolution. Sarhangnejad’s work bridges the gap between hardware and algorithms, providing the foundational sensor technology that makes real-time, multi-exposure computational imaging practical. His contributions are pivotal for advancing autonomous systems and interactive technologies, positioning him as a key figure in the next generation of intelligent imaging solutions.

Research Focus

Key Achievements

1
H-Index
1
Papers
20
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
5.5 Dual-Tap Pipelined-Code-Memory Coded-Exposure-Pixel CMOS Image Sensor for Multi-Exposure Single-Frame Computational Imaging
20 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Toronto

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago