I am a 5th-year Ph.D. candidate in the Department of Psychology at Princeton University, working with Dan Osherson, Nick Turk-Browne, and Eldar Shafir. My primary research goal is to understand how we detect, extract, and learn about statistical structure from the environment, by exploring structure at three different levels. A related line of research examines how existing knowledge and beliefs are updated in light of new information. Moreover, I investigate how having limited resources impacts fundamental cognitive abilities.
Perception of statistical structure
- Basic level: How sensitive are we at detecting simple structures (e.g., 1111 and 1010) in the context of pure noise (i.e., genuine randomness)? How does the ability to distinguish between structured and random events relate to the tendency to identify given events as random?
- Object level: The visual system is extremely efficient at extracting general properties of objects as well as learning about relationships among objects. How do these processes interact? How are regular sources of information processed in the context of noisy sources? And once regularities are learned, how do they influence other aspects of cognition?
- Conceptual level: The environment often contains imperfect information: Scenes can appear blurry and objects can be occluded. When scenes or objects are distorted, when and how well can the brain detect their category?
- Related to the perception and learning of structure, I'm also interested in how existing knowledge and beliefs are updated in light of new information or evidence. Once new information is learned, how does it influence current beliefs?
- Another topic near and dear to my heart is poverty. I'm currently conducting experiments in the field, examining how poverty impacts fundamental cognitive functions, such as fluid intelligence and cognitive control, and what interventions are effective at reducing such impact.