Research & Innovation

Advancing Bioinformatics Through Computational Innovation

My research focuses on developing cutting-edge computational methods, machine learning models, and bioinformatics tools to analyze complex biological data, particularly in genomics, transcriptomics, epigenomics, and metagenomics. I am passionate about integrating multi-omics data to improve plant and animal health, leveraging AI-driven computational modeling, and exploring host-pathogen interactions through systems biology approaches. With over a decade of experience in bioinformatics, I have developed NGS data analysis pipelines, prediction tools, and databases while collaborating with researchers across institutions. At South Dakota State University, I aim to establish a strong, externally funded research program, foster interdisciplinary collaborations, and mentor students in computational biology and bioinformatics. My work is driven by the goal of bridging the gap between data and discovery, ultimately contributing to advancements in agriculture, medicine, and environmental science. I plan to seek funding from agencies such as NIH, NSF, USDA, DOE, and private foundations to support these initiatives.