rmk118.github.io/index.qmd at main · rmk118/rmk118.github.io · GitHub

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---
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    - href: https://www.linkedin.com/in/ruby-krasnow/
      text: LinkedIn
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    - href: mailto:rubykrasnow@gmail.com
      text: Email
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    - href: https://scholar.google.com/citations?user=aFCrgpEAAAAJ&hl=en
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    - href: https://orcid.org/0009-0007-0531-8420
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---

::: {#header}
## Welcome!

My name is Ruby Krasnow *(she/her)* and I am a quantitative marine ecologist focused on using mathematical modeling and data science to support sustainable fisheries management and marine aquaculture.

You can find my full CV [here](Krasnow_CV_for_web_2025-08-11.pdf).
:::

## Education

I am a Ph.D. student studying Marine Biology at the University of Maine. My primary advisor is Dr. Damian Brady, who leads a large lab group focused on [Marine Sciences of Aquaculture, Fisheries, and Renewable Energy](https://umaine.edu/bradylab/).

## Research

### Methods & Approaches

-   Synthesis research: systematic reviews, meta-analysis, interdisciplinary collaborations

-   Open and reproducible data science: [FAIR](https://www.go-fair.org/fair-principles/) (findable, accessible, interoperable, and reusable) data

-   Statistical analysis, modeling, and data visualization in R

    -   Generalized linear models, mixed-effects models, and related methods
    -   Dynamical/state-space modeling
        -   Applications of ordinary and partial differential equations in ecology
    -   Spatiotemporal modeling (including geostatistics and time series analysis)
    -   R package development

### Applications

#### Quantitative fisheries

I am especially interested stock assessment and population dynamics models for economically important crustacean species, particularly data-poor species like the Jonah crab (*Cancer borealis*). My dissertation is broadly focused on [estimating crustacean size at maturity from morphometric data](https://rmk118.github.io/thesis_proposal/).

#### Marine aquaculture

-   Dynamic Energy Budget models of cultivated sugar kelp
-   Spatial modeling for aquaculture site selection
-   Quantifying, predicting, and mitigating biofouling in kelp and shellfish aquaculture