معرفی
Ritambhara Singh is the John E. Savage Assistant Professor of Computer Science and Data Science at Brown University, affiliated with the Center for Computational Molecular Biology. Her research focuses on developing interpretable machine learning methods for biomedical and genomic applications. Prior to Brown, she was a postdoctoral researcher in the Noble Lab at the University of Washington, and earned her Ph.D. in 2018 from the University of Virginia under Dr. Yanjun Qi.
Key research areas include machine learning, computational biology, health sciences, and genomics. She has pioneered methods like SCOT for single-cell multi-omics integration and developed tools such as LUNAR for glioma recurrence prediction. Her work bridges theoretical advancements in deep learning with practical biomedical applications.
Awards include the NHGRI Genomic Innovator Award (2025), Brown’s Richard B. Salomon Research Award, and a teaching excellence award. Her lab emphasizes ethical AI in genomics and interpretable models for clinical decision support.
Publications span topics like graph neural networks, multimodal learning, and optimal transport methods applied to genomics. Her research also addresses privacy risks in single-cell data and evolutionary signatures in olfactory systems.
