I am a computational biologist Ph.D. in Bioinformatics and immunology. I have more than 8 years of extensive experience in analyzing single cell dataset (scRNA, scMultiome, scCITESeq, BEAM-T, Spatial, and scTCRseq), Cycif image, bulk (Genome, Exome, RNA, and ATAC), flow cytometry and microarray. Using single cell dataset I have developed supervised machine learning model to annotate the immune cell types. I have developed web based database using RShiny for bench scientist and developed pipeline using Nextflow.

Currently I am post doctoral fellow in Dr. Aaron Diaz lab in UCSF and collaborator in Dr. Jorg Goronzy's lab in Mayo Clinic. My project in UCSF focused on SHH Medulloblastoma primary vs recurrent difference using snRNA, snATAC, and Visium. Another project focused on lineage tracing of Medullobastoma using mutable and static barcode. My project in Mayo Clinic is focused on understanding the immune aging using scCITEseq, scTCR, scMultiome, spatial, and flow cytometry dataset. I works closely in collaboration on multiple projects with wet-lab scientist which involved analyzing scRNA, spatial, BEAM-T, spatial, Cycif Image, bulk RNA, ATAC etc.

During graduation I have worked on national consortium projects:
1. I have worked on one of the largest primary immunodeficiency cohort (>300 patients) where I have analyzed whole exome and genome datasets.
2. I was a part of a core bioinformatics team of IndiGen consortium, 1000 whole genome sequencing project for the Indian population.
3. I was also part of the SARS-CoV-2 genome analysis bioinformatics core team and involved in the submission of over 1000 Indian isolates of SARS-CoV-2 genome in public repositories.

Skills: Single cell and bulk data analysis, High Performance Computing, Machine Learning, Database development, AWS, R Shiny, R, Python, Bash/Shell scripting, Nextflow, Git.