Dr. Smita Krishnaswamy

Biography

Smita Krishnaswamy is an Associate Professor in the Department of Genetics at Yale School of Medicine and is affiliated with the Department of Computer Science. Her research primarily focuses on the development of machine learning techniques to analyze high-dimensional, high-throughput biomedical data. Specifically, she is interested in unsupervised machine learning methods, including manifold learning and deep learning techniques for detecting structures and patterns in data. Smita has developed algorithms for non-linear dimensionality reduction, visualization, learning data geometry, denoising, imputation, and inference of multi-granular structures, along with feature networks from large datasets. Her work spans various data types such as single-cell RNA-sequencing, mass cytometry, and electronic health records, with specific applications in immunology, immunotherapy, cancer, neuroscience, developmental biology, and health outcomes. Smita holds a Ph.D. in Computer Science Engineering from the University of Michigan, earned in 2008, and has completed postdoctoral training at Columbia University. She has received the Early-Career Investigator Award from the Federation of American Societies for Experimental Biology (FASEB) for her contributions to the field.

Research Interests