Incoming MS Bioinformatics student at Johns Hopkins University with a background in Biochemistry and Data Science (University of Washington, '25). I am focused on building computational workflows and applying machine learning to solve complex problems in genomics and precision medicine.
- AI for Biology: Generative/foundation models for biological sequences, single-cell multi-omics integration.
- Computational Genomics: Scalable algorithms for sequencing data, variant calling, and gene regulation.
- Clinical AI & Precision Medicine: Translational bioinformatics, biomedical NLP, and clinical text processing.
A modular Python pipeline for patient-level biomarker feature prioritization using multivariable OLS regression, log-transform robustness checks, and publication-grade statistical visualizations.
- Keywords: Bioinformatics, Computational Biology, Precision Medicine, Biomarkers, Translational Oncology, Regression Analysis
A multimodal epidemiological pipeline integrating Excel, Stata, and SPSS datasets to analyze nationwide lung cancer risk using Welch's t-tests, Chi-Square tests of independence, and multi-panel stratification dashboards.
- Keywords: Epidemiology, Precision Medicine, Data Integration, Hypothesis Testing, Clinical Informatics, Scipy
A computer-assisted Python pipeline featuring Tesseract OCR and a streaming regex ingestion engine to digitize and structure historical document archives.
- Keywords: OCR, Data Engineering, Tesseract, Regex, Data Ingestion
- Languages: Python (Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn), R (Tidyverse, Bioconductor basics), SQL
- Tools & Workflows: Git/GitHub, Reproducible Environments (
requirements.txt, Conda), Jupyter Notebooks
- Email: shuoyang.grad@gmail.com
- LinkedIn: linkedin.com/in/shuoyang1315