Maliheh Alsadat Arshi
Papers
1
Total Citations
3
H-Index
1
About
Maliheh Alsadat Arshi is a researcher in robotics and artificial intelligence, with a particular focus on human-robot interaction and skill acquisition. Her work centers on developing algorithms that enable robots to learn complex tasks through demonstration and iterative feedback, bridging the gap between human instruction and machine execution. Her most cited paper, "Demonstration learning of robotic skills using repeated suggestions learning algorithm" (2017), introduces a novel approach where robots refine their performance through repeated human suggestions, enhancing adaptability and reducing the need for extensive pre-programming. This contribution has garnered 3 citations, reflecting its foundational role in the field of interactive machine learning. Arshi's research advances the practical deployment of robots in dynamic environments, such as manufacturing and domestic assistance, by making them more intuitive to train. Her work underscores the importance of collaborative learning systems, where humans and robots co-evolve skills through continuous feedback loops. For students and researchers exploring the intersection of robotics and cognitive science, Arshi’s studies offer valuable insights into designing algorithms that mimic natural teaching processes, paving the way for more autonomous and responsive robotic systems.
Research Focus
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Top Papers
- 1