Research

As a researcher for Apprentice Learner (AL), a computational model of human learning, I studied AL's ACT-R memory implementation and compared the memory retention of AL to that of humans. More specifically, I coded JSON files that would stimulate spaced repetition and cramming conditions. I found that AL was able to demonstrate the recency effect, but not the primacy effect that is typically found in human memory retention studies.

For my research on signal processing for transabdominal fetal pulse oximetry, I researched how best to isolate the fetal signal from a mixed maternal and fetal signal. This involved the filtering of both real animal data as well as a Monte Carlo stimulation, and comparing the efficacy of traditional signal processing methods (e.g. Fourier Transform, bandpass filtering), as well as investigating the efficacy of Principal Component Analysis and Independent Component Analysis.

My research in Neuroscience involves testing human participants on Magnocellular and Parvocellular biased imagery in order to gather data on whether or not their reponses to features and spatial arrangements vary. Moreover, I also code in Python/JS in order to convert a PsychoPy task to run online using Pavlovia.