Kajal Schiller, a recent Princeton graduate, has explored the concept of “resource allocation” in her senior thesis. This term is used by psychologists to understand how individuals prioritize their time and attention. Schiller’s personal experiences as a “street child” in India before her adoption have influenced her understanding of this concept.
Her research investigated whether socioeconomic status affects people’s likelihood to utilize resources for problem-solving. The study involved Princeton students participating in a computer simulation game to determine object categories, aiming to shed light on how income differences influence decisions about accessing mental health resources.
“The field of computational psychiatry can help create better models for how these processes occur,” Schiller stated. She graduated with a major in psychology and a minor in statistics and machine learning. Her thesis was guided by Professor Yael Niv, who co-directs a collaboration between Princeton and Rutgers funded by the National Institutes of Health, focusing on computational psychiatry’s role in understanding mental health conditions.
Schiller’s work was also advised by postdoctoral researcher Rachel Bedder from Niv’s lab, who commended Schiller’s imaginative approach. “Something that always really impressed me with Kajal is wanting to bring these concepts from psychology and computational psychiatry back to the real world and real problems,” Bedder said.
Despite no statistical difference found in resource allocation linked to socioeconomic backgrounds, previous data at Princeton supports the connection between poverty and cognitive function. Niv highlighted the broader themes related to low-income backgrounds’ interaction with stress and mental health.
Schiller’s academic journey at Princeton included studies in classics, linguistics, Sanskrit, developmental psychology, statistics, and machine learning. Her involvement extended beyond academics through participation in various student organizations focused on mental health initiatives.
This fall, Schiller will pursue a master’s program in public health data science at Boston University School of Public Health.
