Shah Limon, a Slippery Rock University associate professor of engineering, recently published two research articles in academic journals.
Limon’s article, titled “Integrating Decision Trees and Clustering for Efficient Optimization of Bioink Rheology and 3D Bioprinted Construct Microenvironments,” was published in the Journal of Manufacturing Science and Engineering. The article explores the integration of supervised and unsupervised machine learning-based computational tools, allowing researchers to optimize bioink formulations and printing parameters more efficiently.
Limon’s other article, titled “All-Terminal Network Reliability Estimation Using a Link Degradation Prediction Model,” was published in IEEE Xplore. The article presents a machine learning approach to predict the degradation of network components, aiming to improve reliability and support future research in network health monitoring.