R · Behavioral time series
Nonlinear, natural, and noisy
A toolkit for categorical recurrence quantification and detrended fluctuation analysis, with scripts for preparing and analyzing real-world behavioral data.
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Research & Projects
My work connects quantitative research, collaborative program development, and accessible technical education. These experiences inform the perspective I bring to conservation research and project work.
Collective behavior
How do groups coordinate without a leader?
From humans to honey bees, I study how individuals coordinate their actions toward a shared goal. My doctoral research at the University of Connecticut investigated how task demands, communication, and action constraints shape division of labor and group efficiency.
My approach: Experimental design, analysis of naturally occurring datasets, nonlinear time-series methods, and computational tools for understanding complex social behavior.
Selected work:
- Ecological Psychology Meets Ecology: Honey bees as a model for perception-action, social dynamics, and human factors
- Action coordination in non-human self-organizing collectives, a multidisciplinary special issue I co-edited.
- Division-of-labor research software and analysis code.
This work provides a foundation for asking questions about behavior, coordination, and the relationships between organisms and their environments.
Open research tools
Reusable methods and research software are an important part of my work. These repositories document my approach to studying behavior, coordination, and change over time.
Quantitative research · Methods
Comparing time-series methods
Companion code for a study comparing vector autoregression, cross-correlation, and cross-recurrence analysis in social cohesion and collective action.
R · Published research
Social cohesion & collective action
Research code accompanying our PLOS ONE study of the relationship between online social cohesion and real-world action in Syria during the Arab Spring.
Experimental software · Analysis
Division of labor
A research game and companion analysis repository developed for my dissertation on coordination, task constraints, and group efficiency.
Program leadership
Building collaborative technical programs
At SEACORP, I served as a Task Manager and Software Engineer IV and co-directed the AI/ML Center of Excellence. Working alongside company executives, I helped establish the center to create opportunities for collaboration and education while supporting applied AI/ML work for defense customers.
Developing accessible machine learning education
As a part-time Teaching Professor at the University of Rhode Island, I developed and taught a two-course sequence in machine learning for engineering applications. The sequence helped establish the Undergraduate Certificate in AI/ML for Engineering Applications.
My goal is to make computational methods accessible to students and researchers from varied backgrounds. Explore the introductory coding labs.
Learning resources
I create practical materials that help students and researchers build confidence with data and computational methods.
R Markdown · Guided lessons
Introduction to R
A course in R for the quantitative social sciences, pairing step-by-step explanations with code examples and opportunities to practice.
Visualization · Workshop resources
Interactive data with R Shiny
Tutorial applications created for a Science of Learning and Art of Communication workshop on R Shiny, data visualization, and collection.
Python · Teaching notebooks
Introduction to machine learning
Code-along lessons covering data preparation, regression, classification, clustering, and neural networks for engineering students.
PyTorch · Student workshops
Advanced machine learning
Course notebooks on convolutional and recurrent networks, transformers, optimization, and natural language processing, alongside student-led workshops.
Community sustainability & science outreach
My work with the Keney Park Sustainability Project connects beekeeping with hands-on sustainability education. Alongside science communication, student mentoring, and Software Carpentry instruction, it reflects my commitment to making research accessible beyond the university.
Additional technical projects
Python · Document tools
RAGify
A Gradio application for asking questions of PDFs using retrieval-augmented generation. The project combines document processing with language models.
Explore RAGify →Machine learning · Personal finance
Stock AIdvisor
An exploratory app for identifying companies from descriptions and examining their stock data, built around accessible financial learning.
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