PhD candidate in Chemistry — Georgia Tech (Wu Lab) Chemical biology & quantitative proteomics.

I study how protein modifications shape biological processes such as cellular signaling and immune recognition. Protein glycosylation is my starting point — one of the most common and important modifications — and I build site-specific, quantitative MS methods to analyze it, integrating complementary approaches for deeper insight into these modifications.

• Site-specific glycopeptide analysis across different biological models
• Chemical and enzymatic method development for proteomics
• Analytical instrumentation — including mass spectrometry — for deeper chemical and biological insight
• New tools and concepts to push the boundaries of human knowledge

• Fu, L.; Yin, K.; Xu, X.; Wu, R. Systematic Quantification of Protein O-GlcNAcylation Reveals Common and Cell-Type-Specific Responses to N-Glycosylation Inhibition in Human Cells. Anal. Chem. 2026, 98, 15689–15699. DOI · code · interactive data browser
• Fu, L.; Xu, X.; Wu, R. Mass Spectrometry-Based Proteomics Methods for Systematic Identification and Quantification of Protein O-Glycosylation in Complex Biological Samples (Review). J. Am. Soc. Mass Spectrom. 2026, 37, 1041–1063. DOI

• mzml-utils — mzML processing, fragment-ion calculation, and peak matching
• GlycoSpectrumAnnotator — glycopeptide MS/MS annotation (EThcD support, false-match-rate)
• Glycoproteomic Data Analysis in R & Python — tutorials

• I build Claude Code skills and slash-commands that automate my glycoproteomics research — glycopeptide MS/MS spectrum annotation, quantitative (TMT) data analysis, and literature study — packaged as an installable agent toolkit for the lab. (Available on request.)

Chemical biology · MS-based proteomics · Scientific programming (R & Python) · Agentic AI

• 📧 lpfu46@gatech.edu
• 🔗 LinkedIn
• 🔗 ORCID

• 📖 I enjoy reading and exercising in my free time
• 🤝 Always open to discussions and collaborations — feel free to reach out! 🚀