Alkek Center for Metagenomics and Microbiome Research (CMMR)Department of Molecular Virology & Microbiology• Performs 16s rRNA amplicon sequencing data processing and downstream analysis.• Performs Metagenomic Whole Genome Shotgun sequencing data processing and downstream analysis, enhancing project outcomes.• Develops statistical analysis plans tailored to project needs. • Performs data cleaning and manipulation for accuracy and integrity of datasets. • Conducts comprehensive analysis of clinical and device-measured data from exploratory to final stages.• Successfully developed, tested, and utilized successfully Dual RNA-Seq pipeline for microbiome studies.• Frequently utilizes downstream analysis tools such as MaAsLin2, LEfSe, PICRUSt, Tax4Fun, and DEseq2 enhancing research capabilities.• Experienced in conducting metabolomics analysis using MetaboAnalyst.

Advanced Technology Cores (ATC)• Analyze large biological datasets such as NGS data as well as metabolomic data and proteomics data (e.g. RNA-seq, ChIP-seq, ATAC-seq, scRNA, scATAC, RPPA). • Using statistical and data analysis tools, such as python and R, providing analysis with researchers on diseases and conditions including Cancers; Bladder, Lung, Breast, Kidney; obesity and hyperoxia. • Built custom, automated bioinformatic pipelines in python for analysis and visualization (t-test, PCA, box plots, volcano plots, heatmaps). • Implemented a sample preparation protocol and an image-based quality control tool on user feedback for Reverse Phase Protein Array (RPPA) analysis. • Implemented immunofluorescence microscopy image processing and analysis tool in MATLAB based on user feedback to extract features of primary cilia and hence to study molecular mechanisms of VHL disease. • Developed customized UNIX/LINUX scripts to automate data extraction to improve efficiency of routine tasks. • Collaborate directly with internal and external investigators regarding implementing and reporting bioinformatics and digital image processing applications. • Contributed to 9 publications, 5 grant proposals and numerous academic research projects.

THESIS RESEARCH PROJECT: Optimal Parameters to Determine the Apparent Diffusion Coefficient in Diffusion Weighted MRI via Simulation. • Gained extensive hands-on experience in medical image processing and modeling using Matlab • Simulated Diffusion Weighted MR images and ADC maps utilizing MATLAB • Performed statistical analysis on simulated MRI data to determine optimal parameter combination of ADC maps for improved cancer diagnosis • Implemented interactive GUIs, ROI selection in MATLAB to visualize and manipulate 3D and 4D MRI • Implemented algorithms for DCE-MRI rigid image registration of esophagus cancer utilizing MATLAB