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My research investigates how leaf traits and microbial fungi (endophytes) in tropical woody species influence host responses to herbivory and pathogens, and how leaf shape affects endophyte colonization in Mimulus spp. across altitudes. Learn more about my interests by visiting Research.
I empower people around me to extract meaningful insights from data by sharing my knowledge on data visualization, data wrangling, and data analysis. You can learn more about my teaching experience by visiting Teaching.
I’m currently looking for new opportunities for jobs, collaborations, and projects. Get in touch by sending me a note!
About me
Data scientist <- Ecologist and evolutionary biologist
I love learning, teaching and mentoring about R, Python, reproducible science and many things in ecology and evolutionary biology. That curiosity to learn about systems and how they work and how we can extract information and iterate to better and more efficient systems is what drives me. Some of the questions fuel this:
How does it work?
How can I make it so others understand it?
How can I make it better?
I’m a big fan of open science and reproducibility, and I’m always looking for ways to make my work more transparent and accessible to others. Participating in open source project and reproducible science is a constant exercise that can always be improved. Exercising it gives back to the community and helps me learn and grow.
My research spans from studying ant communities in the tropics to microbial fungi in Yosemite. I focus on how communities assemble and interact with their environment, using R and Python to create explore large genomic datasets.
- Ph.D. in Ecology and Evolutionary Biology ∙ Tulane University ∙ 2024
- M.Sc. in Natural Resources Management-Conservation Ecology ∙ University of Michigan ∙ 2018
- B.S. in Political Science ∙ University of Puerto Rico-Rio Piedras ∙ 2014