Sudipta Lahiri is a Senior Data Scientist / Computational Biologist at the Core for Computational Biomedicine at Harvard Medical School. Operating at the unique intersection of wet-lab experimental science and computational biology, Sudipta brings a dual perspective to biomedical discovery bridging rigorous mechanistic bench research with scalable data analysis and software development.
Sudipta completed his PhD in Molecular Biophysics at Wesleyan University, focusing on the biophysical and biochemical mechanisms of DNA recombination and repair. He pursued postdoctoral research at Yale School of Medicine and NYU Grossman School of Medicine, where he was associated with the BRCA Initiative at Yale Cancer Center and NYU Perlmutter Cancer Center. His research integrated single-molecule fluorescence imaging, quantitative super-resolution microscopy, protein modeling, and bulk/single-cell RNA-seq to dissect BRCA biology, DNA damage response mechanisms, and therapeutic sensitivities.
At the CCB, Sudipta leverages his deep experimental foundation to develop reproducible scientific software packages and scalable computational pipelines for single-molecule, single-cell, spatial multi-omics, and high-dimensional biological datasets. His current work focuses on AI-native biology applying statistical modeling, machine learning, and emerging AI reasoning systems to evaluate data quality, identify predictive biomarkers, and translate complex multimodal data into actionable biomedical insights.
Publication https://scholar.google.com/citations?user=BSnZeXkAAAAJ&hl=en