I am a computational biologist and working in the Psychiatry department, at Washington University, with overall more than seven years of post-PhD research experience. Proven expertise lies in the analysis of complex high-throughput biological data, as evidenced by publications in international peer-reviewed journals.I possess extensive knowledge of bioinformatics, enhancing my ability to navigate and interpret intricate biological datasets.Proficient in various programming languages, including R, Bash, Shell scripting, Python, Perl, and CGI-Perl, facilitating effective data analysis and tool development.Specialized in implementing popular supervised and unsupervised machine learning/deep learning techniques such as SVM, Random Forest. I am adept at handling diverse NGS and multi-omics epigenetics data.Research interests:Dedicated to creating novel computational methods and algorithms for protein localization and structure prediction.Development of predictive models utilizing machine learning, deep learning, and statistical analysis.Specializing in predictive modeling of different chromatin states by integrating datasets of various histone modifications, uncovering re-occurring combinatorial and spatial patterns.Skilled in developing databases using MySQL and MongoDB, contributing to efficient data management.Proficient in developing visualization tools using R, R-Shiny, Plotly, JS, PHP, and embedding Genome Browser to enhance data interpretation and analysis.Analysis and integration of multi-omics data such as RNA-Seq, ChIP-Seq, ATAC-Seq, WGBS, and RRBS.Google Scholar: https://scholar.google.co.il/citations?user=DpFBfmAAAAAJ&hl=enHome Page: https://rbanaudha.wixsite.com/ravindra