My work involves uncovering and addressing biases in data, from statistical biases like Simpson's paradox, to biases incorporated into AI models.
My research follows 4 different themes: analyzing social media, geospatial biases, complex science, and statistical biases.
We explore how harmful behavior spreads on social media, and the impacts of cognitive biases on human-computer interactions.
We explore biases in geospatial data, such as the Modifiable Areal Unit Problem, and how addressing these biases reveal new insights in data.
We explore emergent phenomena, such as the growth of networks or city scaling.
We address biases in models, such as AI fairness, and biases embedded in data, such as Simpson's paradox or survivorship bias.
Click below to explore different research projects I persue.