High Performance Computing Center

I am a researcher and educator with a specialization in computational chemistry, specifically molecular modeling of condensed phase systems. I am currently an Associate Professor and the Interim Department Chair of Chemistry at Oklahoma State University, the Director of Science for the National Science Foundation funded OAK region high-performance computing initiative, and a member of the NSF ACCESS resource allocation committee.

Research Interests:

Research directions in the Fennell lab span molecular force field development, solvation and transfer free energy method development, molecular mechanics calculations of biomolecular diffusion and polymer interfaces, and quantum mechanical calculations of molecular clusters, itemization of intermolecular interactions, and excited state systems. The specific research projects have been and are currently funded under grants from both the National Science Foundation and the National Institutes for Health.

BIO & RESEARCH INTERESTS

I am a bioinformatics research scientist focused on the analysis and interpretation of high-throughput biological data, with an emphasis on genomics, transcriptomics, and multi-omics integration. My work aims to translate complex molecular data into biologically meaningful insights, with applications in health and microbial systems.

I develop and apply reproducible computational pipelines for RNA-seq analysis, variant interpretation, genome assembly, and pathway-level modeling. My approach combines statistical methods with machine learning to identify patterns and support robust, data-driven conclusions.

I collaborate with researchers and clinicians on study design, data analysis, and interpretation, and I contribute to training efforts that bridge computational methods with biological and biomedical research.

 

Research Interests:

• RNA-seq and differential expression analysis
• Variant analysis and genomics
• Genome assembly, annotation, and quality assessment
• Pathway and systems-level analysis
• Machine learning in biological data analysis
• Multi-omics integration