Satya Sahoo, PhD, FAMIA

Our research is focused on developing artificial intelligence (AI) methods to analyze heterogeneous biomedical big data for translational applications. This ongoing work brings two foundational branches of AI—knowledge representation and reasoning, and machine learning to advance the characterization of brain network dynamics and derive clinically meaningful insights from electronic health records (EHRs). A cornerstone of our research lies in the use of ontology engineering not merely for data modeling, but as a functional component across multiple stages of machine learning pipelines, including feature engineering, data integration, and model evaluation. We have applied this hybrid AI framework to analyze multimodal brain connectivity in epilepsy and Parkinson’s disease, deploying both deep neural networks and traditional algorithms such as support vector machines (SVMs). To support scientific rigor and reproducibility, we have developed of ProvCaRe, a provenance metadata framework that leverages semantic web standards and natural language processing to assess the quality and reproducibility of biomedical research.
Webpage: https://bmhinformatics.case.edu/