Mukesh Makwana
Papers
1
Total Citations
2
H-Index
1
About
Mukesh Makwana is a researcher at the intersection of cognitive neuroscience and robotics, with a primary focus on understanding the neural mechanisms that guide goal-directed action. His work explores how prior experience—termed "selection history"—shapes target selection biases, operating independently of top-down goals and bottom-up saliency. In his most-cited paper, "Neurobiologically inspired robotics model: Underlying mechanisms for target selection biases from a recent experience of goal-directed action" (2022, 2 citations), Makwana investigates the distinct roles of target facilitation and distractor inhibition in reaching movements. By developing a neurobiologically inspired computational model, he clarifies how these processes contribute to behavioral performance, offering a framework that bridges cognitive psychology and robotic control. Though early in his citation impact, this work represents a foundational step toward more adaptive, human-like robotic systems. Makwana’s contributions are notable for their interdisciplinary approach, merging insights from neuroscience with practical robotics applications. His research holds promise for advancing both our understanding of human motor cognition and the design of autonomous systems that learn from experience.
Research Focus
Key Achievements
Top Papers
- 1