Genevia Single-Cell Mentorship Program 2026

I am a bioinformatician with a multidisciplinary background in developing and applying novel spatial and single-cell transcriptomics methods to study the biology and pathology of diverse tissue types.

I co-developed the spatial transcriptomics method that was later commercialized by 10x Genomics as Visium—the most widely used technology for spatially resolved expression studies today. I also developed VASA-Seq, a new method for single-cell total transcriptome sequencing.

Beyond method development, I have extensive experience analyzing spatial and single-cell data and supporting researchers across various fields in designing and applying such experiments.

I am a senior bioinformatician and cellular physiologist with over seven years of experience in analyzing diverse biological datasets, particularly next-generation sequencing. My expertise spans a wide range of bioinformatic tools and includes in-depth knowledge of various data types such as single-cell RNA-seq, RNA-seq, spatial transcriptomics, and advanced image analysis (confocal and super-resolution).

I have worked with data from human, mouse, rat, and various cell lines. Throughout my academic career, I have applied pathway and network analysis to reveal metabolic changes across multiple disease states. My strong background in data analysis, coupled with extensive experience in experimental cellular physiology, positions me uniquely to derive meaningful biological insights from large datasets.

I am a bioinformatics scientist specializing in oncology and human health data analysis, with over five years of experience in handling various omics data types. This includes bulk data (whole-exome, RNA-seq) and single-cell and spatial data (scRNA-seq, spatial transcriptomics, single-cell proteomics), as well as expertise in the experimental techniques to generate these types of data.

Throughout my career, I have successfully applied omics analysis to cancer and aging-related diseases, securing public grants, publishing in journals, and presenting at international conferences. I am highly motivated to solve complex challenges and advance healthcare research.

I am a senior bioinformatics scientist with over 10 years of experience in analyzing a wide range of next-generation sequencing (NGS) data types, including spatial transcriptomics, single-cell RNA-seq, bulk RNA-seq, ChIP-seq, CUT&Tag, ATAC-seq, single-cell ATAC-seq, MeDIP-seq, and BS-seq.

With a background in both mathematics and biology, I am well-equipped to analyze and interpret complex biological datasets. My work spans various fields, with significant contributions in immunology and oncology research.

I am a senior bioinformatics scientist with over 8 years of experience specializing in tumor biology and transcriptomics. My expertise includes the analysis of RNA-seq and single-cell RNA-seq data, as well as deep learning-based algorithms in image analysis.

I have applied my expertise to various biomedical applications, particularly in gastrointestinal diseases, tumor biology, and chronic inflammation.

I am a senior bioinformatics scientist with over 10 years of experience in immuno-oncology and tumor evolution, specializing in single-cell data analysis and scientific software engineering. My work centers on integrating and analyzing multimodal data, developing analysis workflows, creating scientific software, and modeling tumor evolution.

I have deep expertise in bulk and single-cell sequencing (WES/WGS, RNA-seq, ctDNA) and 3+ years of experience with spatial omics (transcriptomic and imaging-based). During my Ph.D. and postdoctoral research, I led multiple single-cell studies that resulted in high-impact publications and contributed to two cancer atlases (NSCLC and CRC).