Research intern interested in computational mass spectrometry, AI proteomics, scientific software, and scientific AI agents

I am a Research Intern in Tiannan Guo's group at Westlake University, with an MSc in Bioinformatics and Systems Biology. My current work involves mass-spectrometry data, machine learning, statistical evaluation, and research software. I am especially interested in learning how to develop computational tools that are useful, testable, auditable, and reproducible in real scientific workflows.

flowchart LR
    A[Instrument data<br/>DIA · timsTOF · ion mobility] --> B[Data infrastructure<br/>formats · HPC · reproducibility]
    B --> C[Computational models<br/>Transformers · representation learning]
    C --> D[Evaluation<br/>FDR · entrapment · ablations]
    D --> E[Usable scientific systems<br/>software · agents · audit trails]

• Computational mass spectrometry: DIA/DDA peptide identification, timsTOF and ion-mobility evidence, spectral representations, target–decoy FDR, and entrapment-based evaluation.
• Scientific AI agents: tool use, knowledge graphs, structured memory, provenance, failure recovery, human oversight, and careful validation.
• Research software and infrastructure: cross-vendor data processing, scalable HPC workflows, automated testing, cross-platform packaging, and reproducible benchmarks.
• Structural and experimental background: NMR, molecular dynamics, protein biochemistry, and mammalian cell experiments.

• AlphaRaw #138 — submitted a pandas compatibility fix and regression test for precursor-column filling.
• spectrum_utils #90 — submitted a fix that preserves numerical mass-error precision while keeping annotation strings concise.

Both pull requests are currently under maintainer review.

• DIA-BERT for timsTOF — contributing to an extension of Transformer-based peptide identification using ion-mobility evidence, multi-run data pipelines, multi-GPU training, controlled perturbations, ablations, and FDR-based model selection.
• JAVICS — working on a knowledge-graph-driven mass-spectrometry QC agent with diagnostic tool use, persistent workflow state, feedback, recovery, and auditable reports.
• MSITConvert — contributed to the automated acquisition-to-MSIT workflow, including Linux Singularity and Windows msconvert setup, batch execution, resume support, and output verification.
• AIPC evaluation — participating in the reproduction and technical evaluation of peptide-scoring systems using target–decoy FDR, entrapment-based FDP, integrity checks, and benchmark design.

These are ongoing research projects. Public code, datasets, and quantitative results will be linked when their release status permits.

• Research Intern, Tiannan Guo Group, Westlake University (2025–present)
• MSc, Bioinformatics and Systems Biology, Vrije Universiteit Amsterdam & University of Amsterdam (2023–2025)
• Master's Research Intern, Oliver Zerbe Group, University of Zurich (2024–2025)
• BSc, Pharmacy / Biochemistry and Pharmacology, China Pharmaceutical University & University of Strathclyde (2018–2023)

My earlier research experience includes NMR structure analysis, pressure-dependent molecular dynamics, protein modelling, antibody expression, and cell-based functional assays. This background helps me understand the experimental questions and limitations behind computational workflows.

Python · PyTorch · NumPy · pandas · Polars · scikit-learn · R · Linux · Git · Slurm · multi-GPU training

DIA-MS · timsTOF / diaPASEF · ion mobility · mzML / mzXML · Bruker TDF · target–decoy FDR · entrapment FDP

knowledge graphs · scientific agents · local RAG · audit trails · hidden validation · reproducible pipelines