- Associate Professor, Department of Genetics, Yale School of Medicine, Yale University
- Associate Professor, Department of Computer Science, Yale School of Engineering and Applied Science, Yale University
Dr. Smita Krishnaswamy is an Associate Professor of Genetics and of Computer Science at Yale University, with affiliations in the Applied Math Program, the Computational Biology Program, the Yale Center for Biomedical Data Science, and the Yale Cancer Center. She received her PhD in Computer Science and Engineering from the University of Michigan.
Dr. Krishnaswamy’s laboratory focuses on the development of machine learning techniques to analyze high-dimensional, high-throughput biomedical data. Her work centers on unsupervised machine learning methods — specifically manifold learning and deep learning — for detecting structure and patterns in complex datasets. She has developed algorithms for nonlinear dimensionality reduction and visualization, data geometry learning, denoising, imputation, inference of multi-granular structure, and feature network inference from large-scale data.
Her group has applied these techniques across a broad range of data types, including single-cell RNA sequencing, mass cytometry, electronic health records, and connectomic data, with applications spanning immunology, immunotherapy, cancer, neuroscience, developmental biology, and health outcomes. Her recent work includes ImmunoStruct, a multimodal deep learning framework for immunogenicity prediction.