projects/ideas
Ceslestial GAN
As my final project for my Creative Code class, using Tensorflow, Keras, and Google CoLab I built and trained a Generative Adversarial Network (GAN) to produce novel celestial data images.
Conservation Software (Rosalind’s Ark)
I want to utilize the gargantuan leaps in data analysis that exist today to prop up conservation and sustainability efforts.
Currently, this project is in need of conversations with experts in the field to discover what kind of structure would be needed in the service of this mission.
Gender Differences Among Relationship Regret in College Students
As part of my role as an Undergraduate Research Assistant in the Interdisciplinary Research Group at Binghamton University, this work investigated the reasons why college students might regret their relationship decisions on social media, and the resulting gender differences between those decisions.
Our hypothesis was that the reasons given by participants, and the statistical differences between those reasons that fell along gendered lines, would align with predictions made by sexual script theory. This is a psychological theory that predicts intimate human interaction to follow internal scripts that are socially inscribed, just as Tomkins’ script theory predicts all other human behavior to follow a program for action. We used a survey design to carry out qualitative data gathering (Survey Design), followed by a mixed methods analysis using Qualtrics and SPSS to determine the validity of our null.
This hypothesis turned out to be supported for men and only partially supported for women, indicating that script theory lacks an exhaustive explanation of human behavior, although partially valid.
This research was conducted within the Interdisciplinary Research Group at Binghamton University and was presented at the annual Undergraduate Research Fair in 2017. The presentation poster can be seen here.
Schema Growth: Testing the Effects of Novel Stimuli on Schemata
As a final lab project, this research proposal sought to explore what schemas really are and discover how they might respond to the incorporation of new information.
Schemas can be thought of as figurative organizational structures in the brain, and they are a significant feature in both psychology literature as well as computer science, where they’re actually physical data sets or structures.
However, little research has described how they correspond to the cognitive processes involved in learning, e.g. new memories or information that challenges preconceived notions. This work would be significant because it could provide an explanation for why challenging (contradictory) information can be difficult for people to process and why the belief polarization effect persists.
A presentation on this proposal can be seen here, and the formal write up can be seen here.