Dr. Arvind Rao of Department of Computational Medicine and Bioinformatics at the University of Michigan

Spatial profiling technologies like hyper-plex immunostaining in
tissue, spatial transcriptomics etc have the potential to enable a multifactorial, multi-modal characterization of the tissue microenvironment.
Scalable, quantitative methods to analyze and interpret spatial patterns of
protein staining and gene expression are required to understand cell-cell
relationships in the context of local variations in tissue structure. Objective
scoring methods inspired by recent advances in statistics and machine
learning can serve to aid the interpretation of these datasets, as well as their
integration with other, companion data like genomics. In this talk, we will
discuss elements of spatial profiling from multiple studies as well as
paradigms from statistics and machine learning in the context of these
problems. This talk will also discuss the use of AI/ML and spatial analytics of
the tumr microenvironment to derive spatial biomarkers of immunotherapy

Biography:

Dr. Arvind Rao is an Associate Professor in the Department of Computational
Medicine and Bioinformatics at the University of Michigan. His group uses image analysis and
machine learning methods to link image-derived phenotypes with genetic data, across
biological scale (i.e. single cell, tissue and radiology data). Such methods have found application
in radiogenomics, drug repurposing based on phenotypic screens and spatial profiling in tissue,
as well as in spatial transcriptomics. Arvind received his PhD in Electrical Engineering and
Bioinformatics from the University of Michigan, specializing in transcriptional genomics, and
was a Lane Postdoctoral Fellow at Carnegie Mellon University, specializing in bioimage
informatics.

Address:Associate Professor, Dept. of Computational Medicine and Bioinformatics University of Michigan, , Ann Arbor, MI 48109-2218, Dr. Arvind Rao is an Associate Professor in the Depart48109-2218