Susan Aliakbaryhosseinabadi
Papers
1
Total Citations
2
H-Index
1
About
Susan Aliakbaryhosseinabadi is a researcher whose work explores the dynamic interplay between human cognition and artificial intelligence, with a focus on bidirectional learning systems. Her seminal paper, "The Changing Brain: Bidirectional Learning Between Algorithm and User" (2015), lays foundational groundwork for understanding how algorithms and users co-adapt in real-time, a concept central to modern brain-computer interfaces and adaptive AI. Though early in her citation impact—with 2 citations to date—this work signals a novel perspective on neuroadaptive technology, emphasizing the plasticity of both human neural networks and machine learning models. Aliakbaryhosseinabadi’s contributions are particularly notable for bridging neuroscience and computational design, proposing frameworks where user feedback continuously refines algorithmic behavior, and vice versa. Her research holds promise for applications in personalized rehabilitation, cognitive enhancement, and human-AI collaboration. As a rising voice in this interdisciplinary field, she challenges static models of learning, advocating for a more fluid, reciprocal relationship between mind and machine. Her work invites further exploration into how our brains reshape technology even as technology reshapes us.
Research Focus
Key Achievements
Top Papers
- 1The Changing Brain: Bidirectional Learning Between Algorithm and User2 citations · 2015