Salah Saleh
Papers
13
Total Citations
81
H-Index
5
About
Salah Saleh is a versatile researcher whose work spans two deeply interconnected domains: social robotics and autonomous mobile robot navigation. His early contributions focused on enabling robots to perceive and respond to human behavior, with notable work on nonverbal communication through head gesture recognition, robust depth-based human detection, and the embodiment of human personality traits in emotionally intelligent robots. His 2016 study on action unit-based facial expression recognition using deep learning remains his most cited work, reflecting his commitment to advancing human-robot interaction through sophisticated perception systems. In recent years, Saleh has shifted considerable focus toward autonomous mobile robot path planning, producing a prolific body of research on bio-inspired optimization algorithms. His investigations into Grasshopper Optimization, Red Fox Optimization, and adaptive probabilistic methods have addressed complex challenges in static and dynamic environments. His 2022 paper on Grasshopper-based path planning has already garnered 11 citations, while his 2023 review of bio-inspired methods offers the field a valuable synthesis of current approaches. Collectively accumulating over 70 citations, Saleh's research consistently bridges intelligent perception and efficient autonomous navigation, positioning him as a growing contributor to the robotics and artificial intelligence communities.
Research Focus
Key Achievements
Top Papers
- 1Action Unit Based Facial Expression Recognition Using Deep Learning16 citations · 2016
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- 4Nonverbal communication with a humanoid robot via head gestures9 citations · 2015
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- 7Robust Perception of an Interaction Partner Using Depth Information5 citations · 2013
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