Cambridge, Massachusetts, United States
Computational Biologist | Image-Based Profiling | Deep Learning for Therapeutic Discovery I am a computational biologist focused on applying deep learning methods to image-based profiling to advance therapeutic discovery, particularly in rare diseases and complex biological systems. My work centers on extracting high-dimensional phenotypic signals from cellular images and integrating them with multi-omics data to identify disease-relevant biology, discover biomarkers, and predict drug response. I am especially interested in using representation learning to bridge cellular phenotypes with molecular mechanisms and translational outcomes. With a background spanning quantitative genetics, bioinformatics, and machine learning, I bring a cross-disciplinary approach to understanding disease biology and enabling data-driven drug development. I value open, collaborative science and building computational frameworks that scale across datasets and therapeutic areas.
Senior Scientist, Bioinformatics
Developed machine learning algorithms based on evolutionary histories of B-cell receptors to facilitate the de-novo antibody design and protein optimization.
A Ph.D. student in computational biology focused on population genetics and evolutionary biology.
Implemented a new cell-calling procedure and optimized the SNP-calling process in the analysis pipeline for single-cell RNA sequencing data