• November 2024: Gave a short-talk at Genome Informatics 2024, Wellcome Genome Campus.
• October 2023: Delivered a platform oral presentation at ASHG 2023 in Washington, DC.
• May 2024: Gave a short-talk at Jackson Laboratories Workshop on Long-Read Sequencing.
• October 2023: Published "Alzheimer’s disease rewires gene coexpression networks" in npj Systems Biology and Applications.
• July 2022: Defended my proposal and became a PhD Candidate.
• August 2021: Joined Icahn School of Medicine at Mount Sinai as a PhD Student.
• June 2021: Our meta-analysis paper on the iGEM Interlab studies is now published in Plos one.
• September 2020: Our paper on the iGEM 2018 InterLab study got published in Communications Biology!
• February 2020: Presented updated work of ChassiDex at EMBO symposium Designing Biological Systems.
• December 2019: Master's thesis work on Alzheimer's inter-tissue co-expression network dysregulation presented by advisor at CSHL conference - Development and 3D Modeling of the Human Brain!
• October 2019: Presented work on the spatial progression of Alzheimer's at BESCON.
• October 2019: Our paper on the iGEM 2018 InterLab study is now on bioRxiv!
• July 2019: Our paper on ChassiDex the host organism database is now on bioRxiv!
• October 2018: Won the Gold Medal at the iGEM 2018 competition!
• November 2017: Won the Silver Medal at the iGEM 2018 competition!
• May 2018: I visited CDrum Lab, NUS as an undergraduate summer researcher.
• May 2017: I visited MedGenome as a undergraduate summer intern.

I am passionate about computational biology, focusing on analyzing the human genome to understand complex diseases. My work involves multi-ancestry meta-analysis, cell-type prioritization using snRNA-seq, and exploring the transcriptional complexity of the brain using long-read sequencing.

The transcriptional complexity of the human brain is genetically controlled through a network of cis and trans-acting genetic regulatory elements. Numerous studies have elucidated the functional consequences of cis-acting genetic variants and their ties to neurological disease risk. However, fewer studies have explored trans-acting genetic variants, which often indirectly modulate gene expression and splicing through cis-regulatory elements. Studying these indirect trans-regulated effects is particularly challenging due to their small individual effect sizes and huge genome-wide multiple testing burden. So, to achieve the statistical power required to map trans-acting variants influencing the transcriptome, we have uniformly processed a paired transcriptomic-genetic resource called “BigBrain” containing 13,350 RNA-seq samples with corresponding genotype data from 6,586 individuals from 12 publicly available cohorts. BigBrain includes data from healthy controls and various brain disorders spanning several central nervous system regions and ancestries. Large-scale genome-wide quantitative-trait-loci mapping of trans-acting genetic variants using BigBrain will enhance our understanding of the genetic regulation of the human brain and nominate regulatory elements contributing to neurological disease risk.

The study aims to understand the inter-tissue network of gene-gene interactions at the transcriptional level. We developed a framework to statistically infer the underlying correlation (co-expression) network structure among genes in different brain tissues, and the rewiring of this gene co-expression network between healthy vs diseased groups of individuals. We applied this framework to infer inter-tissue interactions in Alzheimer’s Disease (AD) across four different brain regions - Frontal pole, Superior temporal gyrus, Parahippocampal gyrus, and Inferior frontal gyrus - by utilizing gene expression data available on these brain tissues/regions collected postmortem from about 225 AD individuals with varying disease severity and 100 healthy controls. Known cell type-specific marker genes are then used to estimate the frequency of different brain cell types in each individual and thereby assess the effect of cellular composition on the identified inter-tissue gene networks.

The iGEM InterLab Study is a series of projects ( 2014 and 2015 study, 2016 study, 2018 study) organized by the iGEM competition, focused on addressing the problems frequenting reproducibility in science.

The 2018 InterLab study of which I was a part of addresses the question, Can we reduce lab-to-lab variability in fluorescence measurements by normalizing to absolute cell count or colony-forming units (CFUs) instead of OD? A widely used and important technique to measure the optical density (OD) of bacterial growth spectrophotometry, is based on fluorescent measurements. So, it is essential to address the variability in these measurements to ensure reproducibility across labs. Recommendations to produce reliable and repeatable measurements based on studying the data from 244 different labs is detailed in the paper.

ChassiDex is an open-source, easy to access database of host organisms and tools to work with them. Researchers are increasingly opting to work with unconventional organisms as they have unique advantages over common model organisms, but the characterization of these organisms haven't been documented extensively. ChassiDex provides information about growth and maintenance conditions of such different organisms with applications in synthetic biology, protocols, parts, vectors and other data required to work with them, all in one place.

Our work was featued in the following newspapers and newsletters - Times of India, New Indian Express, IEEE Newsletter India Bioscience

Synthetic biology is a recent and unique field that raises several ethical questions, and therefore, public engagement is essential. India is a diverse country with 22 official languages where only 10.6% of the population understands English (2011 census). The Language Project aims to break the language barrier to make science accessible to everyone.

Hence, we began with the goal to design an introductory course on the basics of synthetic biology in several Indian languages. We have so far created more than 100 educational videos, across 26 languages (9 Indian vernacular languages) by collaborating with 13 other iGEM teams. The effort which began as part of the community outreach for the iGEM 2018 competition, continued for the iGEM 2019 competition. The science communication inititative was recongized at the iGEM 2019 competition with a nomination for the Best Education and Public Engagement award!