I am an ecology and evolutionary biologist at Tulane University. My work uses metagenomics and whole-genome sequencing to explore the interaction foliar fungal symbionts, AKA endophytes, in tropical trees and alpine yellow monkeyflowers . I combine field biology and wet lab skills with data science to answer how leaf traits in tropical trees and alpine yellow monkeyflowers influence the endophyte communities able to colonize them. More info in my CV.

I leverage some machine learning algorithms to analyze genomic and ecological data for insightful patterns. My expertise includes:

• Ordination techniques: Utilizing dimensional reduction techniques to extract meaningful patterns from biological and environmental data.
• Linear models: Applying general linear models and linear mixed models to ecological data.
• Linear Discriminant Analyses (LDA): Applying statistical methods to enhance classification accuracy of fungal communities.
• Bioinformatics: Utilizing HPC clusters and Unix like systems to analyse ITS amplicons from endophyte communities

• Programming Languages: R (advanced), Python (beginner), and C (beginner)
• Bioinformatics Tools: Open-source tools: cutadapt, dada2, Trimmomatic
• Data Visualization: ggplot2
• Version Control: Git, GitHub

This project investigates the role of endophytes in the modulation of leaf functional traits and tropical trees' response to herbivory and pathogen damage.

This project aims to explore and characterize the endophytes found on the leaf tissue of Mimulus guttatus, Mimulus laciniatus, Mimulus nasutus and others along an elevation and geographic gradient in the Sierra Nevada, California, USA.

My scientific debut!

I am excited about the intersection of ecology, genomics and data science. Let's connect and explore potential collaborations or discuss how my skills can contribute to your projects. Feel free to reach out!

LinkedIn Email