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Dr. Sahoo's research is focused on developing artificial intelligence (AI) methods to analyze heterogeneous biomedical big data for translational applications. This ongoing work brings together two branches of AI: knowledge representation reasoning and machine learning algorithms to characterize brain network dynamics and electronic health records (EHR) data.

Knowledge representation and reasoning involves development of knowledge models or ontologies. He has led the development of new methods to use ontology engineering principles across multiple stages of machine learning workflows, including feature engineering and model validation. This involves the development of deep neural network (DNN) models and the use of classical machine learning algorithms such as support vector machines (SVM) for integrative analysis of multi-modal brain connectivity data in neurological disorders such as epilepsy and Parkinson's Disease. 

To address the challenges of data quality and scientific reproducibility, Dr. Sahoo has led the development of a provenance metadata framework called ProvCaRe using ontology engineering and natural language processing techniques.