Joseph Kuo

I am a Computational Biologist and AI Engineer with a strong focus on leveraging deep learning to enhance biomedical research, particularly in the areas of single-cell omics, transcriptomics, and epigenetics. My experience includes integrating machine learning models for large genomic data analysis, optimizing workflows, and translating AI-driven insights into reproducible bioinformatics solutions.

Currently, I serve as a Leading Bioinformatician at Grünenthal, where I apply and optimize state-of-the-art bioinformatics tools for various hospital research projects. My work streamlines data analysis workflows and improves reproducibility in genomic studies. I have successfully applied deep learning models to mass expression data, uncovering novel insights into gene regulation within large transcriptomic datasets.

With a solid educational background, including a Dr. rer. nat. in Computational Biology from RWTH University, I am well-versed in advanced processing of single-cell and bulk RNA-seq, ChIP-seq, ATAC-seq, methyl-seq, and 16S sequencing. I am passionate about using my skills to contribute to impactful research in the biomedical field.