Research
Below are more details on my different research projects
Common Fungal Networks
The Discovery: Using Sorghum and Dark Septate Endophytes (DSEs) as a model, I designed experiments to test if non-mycorrhizal fungi can connect plants.
The Impact: We provided the first evidence of common networks among plants formed by DSE, resulting in water movement between plants and biomass gain. All of this helps challenge the definition of what a common network can be.
Mining the Literature with AI
The Problem: We claim endophytes are in every single plant, but we lack a global analysis to prove it. Humans can't read fast enough to synthesize the tens of thousands of papers on endophytes.
My Solution: I build Natural Language Processing (NLP) pipelines to automate data extraction.
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Global Ubiquity: I classified over 20,000 abstracts to create the first global map of fungal endophyte presence/absence (Preprint available).
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Trait Flexibility: Using fine-tuned BioBERT models, I am assessing how and when fungi switch trophic modes (e.g., from saprotrophy to pathogenicity).
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A Tool: I developed nanodRop, an open-source R package to help other scientists process spectral data reproducibly.
Predicting Drought Resilience in Populus
The Experiment: Multi-year greenhouse and field studies stressing native Cottonwood crosstypes (P. fremontii, P. angustifolia) with drought and invasive Tamarisk.
The Insight: We found that investigating root fungal symbioses is critical for understanding forest resistance to climate stress.
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Read one of the papers: Seeley et al. (2025) in Plant Biology.
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Next Steps: Manuscript on mycorrhizal compensation in hybrids is currently in review.
Research Vision
As I transition to the next stage of my career (Spring 2026), I am seeking opportunities to apply my hybrid skillset, combining big data synthesis with experimental rigor.
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My Research Program Focuses On:
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Plant-fungal ecology: Uncovering the hidden rules of Common Fungal Networks and how fungi mediate stress in host plants.
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Computational Synthesis: Using LLMs and Machine Learning to mine data from the literature.
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One Health: Leveraging environmental fungal models to understand opportunistic pathogens and human health risks.
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Global Change: Linking micro-scale fungal traits to macro-scale ecosystem resilience.
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Interested in collaborating? Download my CV or get in touch.