Liana Manukyan
Papers
1
Total Citations
28
H-Index
1
About
Liana Manukyan is a leading researcher at the intersection of computer vision, robotics, and developmental biology, with a primary focus on high-throughput quantitative phenotyping. Her most influential work centers on engineering novel, automated imaging systems to bridge the critical gap between molecular-scale observations and macroscopic morphological complexity. Manukyan is best known for developing R2OBBIE-3D, a fast, robotic high-resolution platform for quantitatively phenotyping surface geometry and colour-texture. This system, detailed in her highly cited 2015 paper (28 citations), provides a transformative tool for investigating the biophysical mechanisms that generate complex skin structures, enabling researchers to capture and analyze 3D morphological data with unprecedented speed and precision. By creating robust, automated solutions for large-scale phenotyping, Manukyan’s contributions are instrumental in advancing our understanding of how genetic and mechanical forces shape organismal form, making her work essential for researchers in morphogenesis, evolutionary developmental biology, and bioengineering.
Research Focus
Key Achievements
Top Papers
- 1