Prof. Latha Chakravarthy is a Mathematics instructor at Central State University, with a Masters in Electrical Engineering from Wright State University. Prof. Chakravarthy’s research interests include signal processing, bioinformatics and machine learning. She has worked on developing the modeling and simulation of the pulsed signal processor in a radar receiver for airborne applications in the Advanced Anti-Radiation Guided Missile (AARGM) program funded by the US Navy.
While working on contracts with AFRL, she has implemented advanced change detection algorithms including Anomaly Detection and Signature based Matched Filter techniques for detecting specific targets in Hyperspectral image (HSI) data, based on realistic temporal changes between successive observations, as well as tested layered sensing algorithms using Covariance Subspace Matched Filter (Second-order) Detectors on Hyperspectral Digital Imagery Collection Experiment (HYDICE) remote sensing data. She has also been involved in analysis of human physiological signals, and was awarded a patent for developing a model and diagnostic process for detecting atrial fibrillation.
She is currently pursuing research in bioinformatics with a focus on developing a diagnostic process for disease detection using gene expression based Multi-Layer Principal Component Analysis (PCA) machine learning classifier. The multi-layer PCA machine learning classifier application can also be extended to discern chemical components and composition of soil and water for agronomical purposes.