Postdoctoral Scholar @ Plan Pathology @ UC Davis
I study crop disease from the first field observation to the final model, combining molecular diagnostics, multi-omics, and reproducible data science to find signals that can improve crop decisions.
🍇 FIELD → 🧬 MEASURE → 💻 MODEL → 🌱 DECIDE
🌿 Crop scientist: I begin with the plant, the field pattern, and the biological question.
🧬 Molecular scientist: I measure the signal with RT-qPCR, digital PCR, RNA-seq, and metabolomics.
📊 Data scientist: I build reproducible pipelines, integrate evidence, test models, and communicate uncertainty.
🎯 Translator: I turn results into diagnostic markers, biological mechanisms, and crop-improvement questions.
🍇 Grapevine–virus interactions · Transcriptomic and metabolomic profiling across commercial-vineyard samples, seasons, cultivars, and maturity stages
🧬 Molecular diagnostics · RT-qPCR and digital PCR assay development, validation, and quality control for plant pathogens
📊 Multi-omics data science · Differential expression, pathway analysis, biomarker discovery, causal analysis, Bayesian inference, and machine learning
🧪 Food safety and formulation · Plant-derived nano-formulations, toxin control, release modeling, and mechanism-of-action studies
A bulk RNA-seq pipeline that takes raw FASTQs to QC reports, gene counts, and differential-expression results. The study design is checked for estimability before any compute runs, and every project keeps its own configuration, logs, and results.
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An RNA-seq workflow for studying Grapevine Red Blotch Virus across vineyard samples, seasons, and maturity stages. |
An AI-ready R visualization skill with three plotting engines and PNG, PDF, and interactive HTML output. |
A visual portfolio connecting publications, methods, reproducible analyses, and research communication. |
38 peer-reviewed journal articles · 22 book chapters · 2,300+ citations · h-index 25
