Katia Smirnova, Ph.D., joins the department as an assistant professor. Her primary research interests lie in the area of microbiome research and activity monitoring using wearable devices. Besides these areas, Dr. Smirnova is working on anomaly detection problems in financial networks, forest conservation environmental applications, and examining protein modifications in lung cancer cell lines.
Her projects span multiple methodological research areas including longitudinal variability modeling for sequencing count data, multi-omics data integration, topological network analysis, longitudinal modeling for functional data, and development of visualization tools for protein interaction networks.
Dr. Smirnova enjoys working with students and collaborators, and promoting a dynamic atmosphere where work-in-progress and future ideas are shared among the members of research groups with common interests. Her future directions include methodology development for merging complex high dimensional data from heterogeneous sources, and building data analytic and software tools, together with thorough documentation and training materials to provide easy-to understand and use statistical methods to the scientific community.