Successfully contributed to over 15 projects providing expertise in computational proteomics (MS, O-Link, NULISA, Soma Logic), Metabolomics, Lipidomics, and Mass Spec Imaging for pipelines in Immunology, Rare Disease, Neurology and Immuno-Oncology.Managed a team of 5 CRO scientists to develop an AI-based data analysis app for Olink Proteomics data analysisTeam was top 3 finalist for Sanofi’s 2023 Global Research Awards for Accelerating Clinical Translation categories (Pipeline Productivity).Represented Sanofi at internal and external conferences, consortiums like AMP-PD, EPMD etc.

Developed statistical and machine learning-based models to leverage new insight into biological systems from multi-omics data (e.g., metabolomics,genomics, metagenomics, transcriptomics) and published as first-author, lead computational biologist in neuromuscular degeneration, cancer immunotherapy, autism, toxicology, and heart disease areasGained hands-on experience in several pipeline frameworks (Cromwell/WDL, Docker, XCMS) in HPC cluster and Cloud platforms (AWS, Google)Taught courses in Microbiome, Metabolomics, NGS Pipeline Development, WDL Pipeline Framework, Data Carpentry with RInvited talks at Marine Biology Lab (Woods Hole), Iowa State University, and University of ConnecticutCollaborated with interdisciplinary teams of translational research/medical scientists, biologists software engineers, and computational scientists

Developed machine learning predictive models to identify the children with ASD (Autism Spectrum Disorder) from typically developing children with about 80% accuracy using mass spectrometry-based metabolomics from blood plasma samples, which resulted in a new ASD diagnostic assay and a neurological disorder business unit (NeuroPointDx)Provided data analysis and computational biology support in developing in-vitro human stem cell and metabolomics based assays for toxicity screening of drug candidates and chemical compounds which resulted in becoming a key platform in support of EPA’s ToxCast program