Sharmishtaa Seshamani, Ph.D.
At the Allen Institute for Brain Science, Sharmishtaa Seshamani is working in the Human Cell Types group. Her current research focusses on building a data processing pipeline to facilitate the imaging of neurons in the brains of mouse and human brain samples in order to reveal important details about the morphology and connectivity of neural circuits. She received her Ph.D. in Computer Science from Johns Hopkins University where she focused on developing meta registration and mosaicking techniques for endoscopic imaging. Prior to joining the Allen Institute for Brain Science, she was a Senior Fellow at the Biomedical Image Computing Group in the University of Washington. There, she was working on a pipeline for fetal fMRI analysis which included algorithms for MRI artifact correction (bias and spin history), motion estimation and reconstruction.
As a member of the synapse biology team, one of my primary research goals is to develop a framework for automated large scale processing of array tomography data. In particular, I am interested in developing tools for linear and elastic registration and 3D reconstruction optimized for large datasets. I am also interested in applications of machine learning techniques for automatic parameter selection and connectivity data analysis.
- Computer vision
- Pattern recognition
- Medical image analysis
- Human Cell Types
January 13, 2019
Smith SJ, Sumbul U, Graybuck LT, Collman F, Sharmishtaa S, Gala R, Gliko O, Elabbady L, Miller J, Bakken T, Yao Z, Lein ES, Zeng H, Tasic B, Hawrylycz M
November 11, 2019
Smith SJ, Sümbül U, Graybuck LT, Collman F, Seshamani S, Gala R, Gliko O, Elabbady L, Miller JA, Bakken TE, Rossier J, Yao Z, Lein E, Zeng H, Tasic B, Hawrylycz M
September 17, 2018
Ounkomol C, Seshamani S, Maleckar MM, Collman F, Johnson GR