Kamal Nasrollahi
Papers
5
Total Citations
91
H-Index
4
About
Kamal Nasrollahi is a leading researcher at the intersection of computer vision, human-robot interaction, and affective computing, with a focus on automating critical infrastructure inspection and enhancing human-robot communication. His work spans two impactful domains: first, he revolutionized sewer inspection by introducing 3D sensors and deep learning to automate the labor-intensive manual review of video footage, as detailed in his highly cited 2021 paper (38 citations). Second, he pioneered emotion recognition systems that integrate upper body movements with facial expressions, achieving 32 citations for his 2021 model that enables robots to interpret human emotions more naturally. Notably, Nasrollahi extended this capability to assist traumatic brain injury (TBI) patients by teaching the Pepper robot to recognize their emotional states through deep neural networks (2019, 11 citations), a breakthrough for non-intrusive rehabilitation. His contributions also include deep transfer learning for cognitive and physical rehabilitation (2021, 7 citations) and statistical machine learning for human behavior analysis (2020). With a cumulative citation count exceeding 90, Nasrollahi’s work is driving safer infrastructure management and more empathetic robotic systems, making him a key figure in applied AI for societal benefit.
Research Focus
Key Achievements
Top Papers
- 13D Sensors for Sewer Inspection: A Quantitative Review and Analysis38 citations · 2021
- 2Deep Emotion Recognition through Upper Body Movements and Facial Expression32 citations · 2021
- 3
- 4
- 5Statistical Machine Learning for Human Behaviour Analysis3 citations · 2020