Ali Sharifara

The University of Texas at Arlington

Papers

1

Total Citations

2

H-Index

1

About

Ali Sharifara is a researcher whose work lies at the intersection of cognitive science and robotics, with a primary focus on developing innovative assessment models for human cognition. His most notable contribution is the creation of a robot-based cognitive assessment framework that evaluates visual working memory and attention levels—a novel approach that bridges artificial intelligence with neuropsychological testing. This work, published in 2018, has garnered 2 citations, reflecting its early-stage but promising impact in the field of human-robot interaction and cognitive diagnostics. Sharifara’s research aims to automate and enhance traditional cognitive assessments, offering potential applications in early detection of cognitive decline, rehabilitation, and educational technology. By integrating robotic systems with psychological metrics, he addresses the growing need for scalable, objective, and engaging evaluation tools. His contributions are particularly relevant for researchers exploring assistive robotics, cognitive aging, and adaptive learning systems. Sharifara’s work exemplifies how interdisciplinary approaches can yield novel solutions for understanding and supporting human cognitive function, paving the way for future advancements in personalized cognitive health monitoring.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A Robot-Based Cognitive Assessment Model Based on Visual Working Memory and Attention Level
2 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: The University of Texas at Arlington

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago