Hi there! I'm Ruifeng Hu, Ph.D., a computational biologist specializing in bioinformatics, machine learning, and multi-omics data analysis. Currently, I work as a Research Scientist at Yale School of Medicine, applying advanced statistical and AI-driven approaches to decipher complex biological data for biomarker discovery, precision medicine, and disease modeling.
I have rich experience in:
- Multi-omics Data Analysis: Single-cell & bulk RNA-seq, spatial transcriptomics, CRISPR screens, genetics.
- Machine Learning & Deep Learning: Regression, clustering, generative models (VAE, LSTM, Transformer).
- Cloud & HPC Computing: Nextflow, Airflow, Docker, AWS, GCP, high-performance computing.
- Bioinformatics Pipelines & Web Development: Automated workflows and interactive genomic data platforms.
I actively contribute to open-source projects and have developed various bioinformatics tools and databases. My research focuses on leveraging AI and data-driven methods to advance biomedical discoveries.
I thrive in collaborative environments, working closely with wet lab scientists and other researchers to bridge the gap between computational and experimental biology. Always exploring cutting-edge AI applications in bioinformatics!