Ruimin Wang

Ruimin Wang is a Research Fellow in the Department of Immunobiology at Yale School of Medicine. His work focuses on advancing mass spectrometry-based metabolomics and developing computational tools for biomedical data analysis. He specializes in areas such as data compression, statistical methodologies for large-scale datasets, and bioinformatics software development.

Key contributions include creating web-based platforms (e.g., MRMPro, MetaPro) for streamlining mass spectrometry workflows, optimizing experimental designs (e.g., InjectionDesign), and enhancing data storage efficiency through novel compression techniques (e.g., Aird, StackZDPD). His research also addresses critical challenges in metabolomics, such as accurate false discovery rate estimation and entropy-based analytical methods.

Wang collaborates on interdisciplinary projects involving edge computing for biological data and deep learning models for feature detection in LC-HRMS data. His work bridges analytical chemistry, computer science, and clinical applications, aiming to improve diagnostic tools and biomedical research infrastructure.