EnBiSys Laboratory

Developing systematic approaches to modeling, analyzing, and eventually controlling the underlying mechanisms and resulting behavior of biological systems to solve current agricultural, health, and environmental challenges.
Many of the current problems facing the global community are complex and often transcend the scope of a single discipline. They often require integrative and collaborative approaches to identify and implement potential solutions. The EnBiSys Lab is a highly collaborative and interdisciplinary research group that aims to tackle some of these challenges. We are based in the Department of Electrical and Computer Engineering at NC State University and collaborate with researchers in fields such as plant and microbial biology, forestry, chemical engineering, and others. Our goal is to use theories and methodologies from traditional electrical engineering areas, such as:
  • Machine learning
  • Digital signal processing
  • Control theory
  • Computer vision and image processing
  • Nonlinear systems analysis

to develop techniques for understanding and influencing biological systems.

Current Projects

Regulation and Modeling of Lignin Biosynthesis

Lignin is a phenylpropanoid polymer that is entangled with the cellulose in the secondary cell walls of all vascular plants. The accumulation of lignin plays several important roles in vascular plants and trees… Read More 


INSPIRE: Dynamic Modeling of the Iron Deficiency Induced Genetic Interactions in Arabidopsis thaliana

This National Science Foundation-funded INSPIRE project is an interdisciplinary effort that aims to further our understanding of the underlying molecular processes involved in the model plant, Arabidopsis thaliana’s, response to iron deprivation stress…Read More

Biological Data Acquisition and Analysis of Microscopy Images using Computer Vision and Machine Learning

This project focuses on automating the extraction of data from spatial and temporal gene expression observations in microscopy images using computer vision and analyzing the data using machine learning approaches…Read More

Efficient and Accurate Real Time Detection of QRS Complex in an ECG Signal

Detection of the QRS complex in Electrocardiogram (ECG) signals is an important topic of research in biomedical signal processing, especially for the development of in-patient heart devices… Read More

Mapping Transcriptional and Translational Response of Hormones in Arabidopsis thaliana and Tomato Seedlings

Plants are sessile organisms that have evolved a complex cascade of regulatory processes to manage all aspects of growth and development, particularly in the presence of changing environmental conditions… Read More

A Computational Model for the Metabolism of Myo-inositol Hexakisphosphate

Phosphate is an important mineral with respect to plant growth. Understanding how plants absorb and release inorganic phosphate is an important step to being able to control these processes… Read More