“Resource allocation” is a term that psychologists use to measure how people prioritize their time and attention.

Long before she heard the term, Kajal Schiller understood it as a matter of survival. Before she was adopted at age six, Schiller had spent part of her preschool years as a so-called “street child” in India, with nearly 100 percent of her time and attention focused on food, shelter and safety.

Her thesis research as a Princeton senior applied the concept of resource allocation to ask whether socioeconomic status might determine how likely people are to take advantage of resources that can help them solve problems.

Her experimental design asked Princeton student subjects to play a computer simulation game and decide how many objects to see before determining their category. She hypothesized that her data might help illuminate why real-world decisions about whether to access mental health resources are affected by differences in income.

“The field of computational psychiatry can help create better models for how these processes occur,” she said.

Schiller graduated this May with a major in psychology and a minor in statistics and machine learning. Her thesis adviser, Yael Niv, is a professor of psychology and neuroscience who co-directs a novel Princeton-Rutgers collaboration funded by the National Institutes of Health that is applying the tools of computational psychiatry to understand mental health conditions.

Schiller’s other adviser, postdoctoral researcher Rachel Bedder, is a member of Niv’s lab who uses computer modeling to understand why some people ruminate on negative thoughts.

This fall, Schiller will begin a master’s program in public health data science at the Boston University School of Public Health.

Bedder praised Schiller as an imaginative researcher. “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,” she said.

Photo by

Denise Applewhite, Office of Communications

The research journey

Schiller said she was drawn to the “incredible purpose and meaning” of Niv’s work, especially as the co-founder and co-director of the Rutgers-Princeton Center for Computational Cognitive Neuro-Psychiatry.

For her senior thesis research, she worked with Bedder to code her experiment, while Niv oversaw the broader direction of the project. Both had also advised Schiller for her junior paper on rumination in adolescents with depression and PTSD, and Schiller’s senior thesis game simulation is an adaptation of one that Bedder had developed. 

Bedder praised Schiller as an imaginative researcher. “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,” she said.

With advances in AI and machine learning poised to revolutionize health research, Schiller’s foundational knowledge of coding and programming is a critical skill, Bedder said. “A lot of these computational models and mechanisms have these baked-in mathematical assumptions about how humans work and what they choose. Actually knowing how to apply these algorithms to questions of societal interest is really important.”

While this particular research design did not show a statistical difference in resource allocation tied to the students’ socioeconomic backgrounds, the connection between poverty and cognitive function has been well established in experimental data at Princeton and elsewhere. Niv said the work connects to broader themes of “how low-income background interacts with stress and with mental health.”

The Princeton journey

Schiller had been curious about psychology since childhood but arrived at Princeton undecided on a major. She pursued coursework in classics, linguistics and Sanskrit before an introductory course in developmental psychology convinced her the major would be a good fit. She gravitated toward her minor in statistics and machine learning after taking a data science course through Princeton’s Center for Statistics and Machine Learning.

Her humanities coursework helped ground her STEM studies in aspects of human experience, across time and cultures, she said. “It can be very easy to feel so distant from that when all you do is spend six hours in the office just coding or you're working on an engineering project.”

Beyond the classroom, Schiller participated in the Scholars Institute Fellows Program (SIFP) in the Emma Bloomberg Center for Access and Opportunity, where she led mental health initiatives and discussions with other lower-income students. 

“There are going to be times where you talk to Princeton students and they're going to be stressed,” Schiller said. “The thing is, if they feel comfortable enough to tell you, I think that is already a good starting place.” 

She was a peer academic adviser at Whitman College and served on the Whitman College Council. She was a member of the South Asian Students Association, 2D Co-op, the Princeton Psychology Society and Acts of Kindness.

The summer before her junior year, Schiller traveled to Bengaluru, India, for a Princeton Institute for International and Regional Studies global seminar in collaboration with the High Meadows Environmental Institute. It was her first time returning to her home country since being adopted.

“Going to India the first time with Princeton was definitely, I think, probably the healthiest way to have that interaction,” she said. Her earliest memories of childhood poverty are among her strongest motivators to pursue an advanced degree in public health.

Schiller will enter a master’s program in public health data science at the Boston University School of Public Health this fall.

Photo by

Denise Applewhite, Office of Communications