Papers
7
Total Citations
138
H-Index
6
About
Zainab Khan is a pioneering biomedical engineer whose research sits at the intersection of 3D bioprinting, tissue engineering, and regenerative medicine. Her work has made significant strides in developing sophisticated biological models that replicate complex human tissues and disease environments. Khan's most influential contribution — a 3D bioprinted Parkinson's disease model using dopaminergic neurons within biomimetic peptide scaffolds (39 citations) — demonstrates her innovative use of ultrashort self-assembling peptides as bioinks, a recurring theme across her portfolio. Her foundational 2018 paper on optimizing bioprinting processes with these peptide bioinks (23 citations) helped establish key principles still referenced in the field today. Beyond neurological applications, Khan has tackled volumetric muscle loss, acute myeloid leukemia modeling, and hybrid fabrication approaches, reflecting the remarkable breadth of her expertise. Her development of robotic and microfluidic bioprinting systems — including the dual-arm TwinPrint platform enhanced by machine learning flow-rate prediction — highlights her commitment to automation and precision in biofabrication. With nearly 140 cumulative citations across just seven papers, Khan's research is rapidly gaining recognition, positioning her as an emerging leader shaping the future of personalized medicine and disease modeling.
Research Focus
Key Achievements
Top Papers
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- 2Optimization of a 3D bioprinting process using ultrashort peptide bioinks23 citations · 2018
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