I apply my data science and mathematical skills to interdisciplinary research problems in evolution of language, biology, and social behavior dynamics.
Collaborators: Rick Dale & Suzanne Sindi
The project goal is to model word rank evolution using a Wright-Fisher inspired model. Google Ngram data is used to analyze eight languages and compared it to the model that simulates drift evolution. The time-series evolutionary dynamics of word ranks are investigated by adjusting the model parameters and comparing it to the language data.
Preprint:
Collaborators: Ben Yarrish, Laurel Ponce, and Sajid Bin Mahammud. 1
This project investigates the relationship between crime rates and policing in the United States. We are using mathematical and statistical modeling, data science methods, and city-wide data to answer key questions, such as: How does law enforcement response vary with changes in crime rates? How do community perceptions of law enforcement change based on their presence? What are the effects of police presence on marginalized communities? The project’s findings will inform public policy and enhance community-police relations.
Posters:
Collaborators: Maia Powell, Ayme Tomson, Suzanne Sindi, & Arnold Kim
The goal is to uncover the discourse and evolution behind certain hashtag social movements using NLP methods, machine learning algorithms, and language models. Twitter data was collected and processed using NLTK and several Python tools.
Poster:
Collaborators: Sam Nguyen & Juanita Ordonez
The objective was to fine-tune and evaluate three language models named BERT, ALBERT, and LongFormer on question answering data set called DuoRC where it contains movie plots with narrative structures. Due to the complexity and length of narrative texts, these models are needed to not only answer the question but must also go beyond its capabilities to perform complex reasoning and reading comprehension to infer answers to questions.
Preprint:
Presentation:
Collaborators: Robert C. Blake & Ben C. Yee
The objective was to encode opacity - a material property on how much radiation can pass through it - into a neural network as a surrogate model against an existing atomic physics code.
Poster:
Collaborators: Maia Powell & Matthew Mondares
The goal was to explore the spread of information generated by Twitter bots during the 2018 California Camp Fire disaster utilizing user-user and hashtag co-occurrence networks. Twitter bots are users who have automated repetitive and straightforward tweets. Most of them post, repost, or like other tweets to spread information faster than actual users for an unknown large-scale goal.
Report:
Collaborators: Madeline Brown, Ritesh Sharma, & Umesh Krishnamurthy
This project was about modeling flood risk given multiple factors such as scale, demographics, risk perceptions, topology, soil moisture, and precipitation. The general goal was to develop a model for real-time predictions to alert and inform communities of flood risks.
Presentation:
Collaborators: Michele Lynn Joyner, Edith Seier, Chelsea Ross, J Colton Watts, Nathaniel Hancock, Michael Largent, & Thomas C. Jones. 2
The goal of this study was to model the predation movements of the spider species Anelosimus Studiosus using stochastic differential equations.
Publications:
Posters:
If you see mistakes or want to suggest changes, please create an issue on the source repository.
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/stressosaurus/alexjohnquijano, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".