📊 Statistics PhD Student | 🧬 Multi-Omics Analyst | 🖥 R Package Developer

I am thrilled to be joining the Statistics PhD program at Texas A&M University in Fall 2024.

• Awarded the Inaugural Su Binghua Distinguished Biostatistics Scholarship ($2,800) by Tigermed, 2024
  • Only undergraduate recipient among PhD candidates across mainland China
• Received the National Scholarship from the Ministry of Education of China.
• Secured First Prize in the National College Student Mathematics Competition.
• Honored with Meritorious Winner (M Award) in the Mathematical Contest in Modeling (MCM) in the USA.

Under the guidance of Prof. Jun Chen at Mayo Clinic and Prof. Liangliang Zhang at Case Western Reserve University, my research primarily revolves around microbiome data analysis.

• Developed the MicrobiomeStat R package, writing over 17,000 lines of R code. Comprehensive documentation is available on the package wiki, which contains in-depth guidance and tutorials exceeding 20,000 words. Additionally, an interactive MicrobiomeStat Shiny application has been created to provide a user-friendly platform for longitudinal statistical analysis and visualization of microbiome data.
• Pioneered the MicrobiomeGallery collaborative platform.
• Independently developed the ggpicrust2 R package, which amassed 85 stars on GitHub and over 11,000 downloads on CRAN.

My future vision embraces a multi-omics perspective, synthesizing insights from genomics, proteomics, transcriptomics, and more.

• Sole first author on a paper accepted by Bioinformatics.
• Preparing to submit another paper as sole first author to Microbiome.

I am very open to collaborations, especially in the areas of multi-omics, single-cell, spatial transcriptomics, and microbiome data analysis. If you have any projects in these fields and think we could collaborate, please feel free to reach out! I am also eager to assist others with their data analysis needs in these areas.

Additionally, I am particularly interested in collaborating with researchers who have used my tools, such as ggpicrust2 or MicrobiomeStat. If you're considering using or have already incorporated these tools into your research, we can explore potential co-authorship opportunities. Whether it's data analysis, interpretation, or manuscript preparation, I'm happy to contribute my expertise. Let’s work together to advance these fields!

Claude's innovative approach using the entire NCBI database with the LLM offers direct taxonomic insights from FASTQ sequences. A potential game-changer when compared with traditional methods.

Exploring how microbiome DA methods, known for processing the compositional nature of microbiome data, perform on other omics.

Assessing the LLM model's capability as a microbiome data analysis expert against real-world experts.

A tool designed to assist graduate school aspirants in discovering PI names from specific professional journals.

Aiming to develop a platform to fine-tune ChatGPT with bioinformatics repositories, enhancing query results for newer tools.