Cancer diagnostics, Liquid Biopsy, MRD minimal residual disease for cancer monitoring, Data science, Machine learning, Algorithm development, Bioinformatics, Cloud computing

• Developed and improved analysis pipelines for RNA-Seq, DNA-Seq, single cell sequencing leading to scalable, portable, and reproducible analytics platform.• Managed lifecycle of multiple NGS projects and provided expertise in terms of project planning, defining analysis strategy, pipeline development, data analytics, visualization, tool development and troubleshooting.• Strategized and developed a new computational tool “RiboDesigner” for designing efficient probes for rRNA depletion for any given species.• Developed a machine learning algorithm prototype to predict drug recommendation system using patient biomarkers and RNA-Seq data in lung cancer.• Performed bioinformatics analysis and troubleshooting of “ctDNA assay” for detection of SNV, indel, fusion and CNV.• Developed a new variant calling pipeline for analyzing COVID-19 samples.

Designed, developed and implemented new computational methods and pipelines for NGS data analysis. Applied statistical and machine learning techniques for data mining, biomarker discovery and predictive models. In depth knowledge of various programming and scripting languages (R, Python), statistical and data mining tools, machine learning, data visualization, Linux, HPC Cluster and Cloud environment. Innovative, Independent, self learning, productive with strong interpersonal and communication skills.Selected projects:• RNA-Seq and proteomics analysis to explore the effects of hyperoxia on learning and memory development in neonatal babies.• RNA-Seq analysis and Biomarker discovery in Neuroinflamation: Understanding the role of RNA Binding protein HuR in neuroinflammation in primary microglia cells.• Identifying genomic variants in M. Tuberculosis upon exposure to cigarette smoke.• RNA-Seq and pathway analysis of various mutants in S. pneumoniae.• Development of computational pipelines for various NGS projects including microbiome and metagenomics. Developed microbiome data analysis pipeline (QWRAP) based on analysis of open source tools and database. https://github.com/QWRAP/QWRAPv3• Leading the microbiome and metagenomic data analysis for several projects (20+) related including Biomarker discovery for immunology and cancer projects.• Data mining from TCGA samples for Renal Cancer project.• Developed a new machine learning method (mgSNP) for tracking microbes across various metagenomic samples. It was specifically used to identify microbes successful in microbial transplants.

• Performed data Integration of Gene expression (RNA-Seq) and GWAS datasets, followed by pathway analysis (Ingenuity) on triple negative breast cancer & tamoxifen resistance.

• Involved in research projects related to Microbial genomics, Microarray, Tiling array, Gene Ontology, protein protein interaction.• Designed and developed tiling array data analysis pipeline for prokaryotes (TAAPP).• Designed and developed host pathogen protein-protein interaction database (HPIDB).