I am a postdoctoral scholar working with Brandon Turner at Ohio State University. I finished my dual PhD in Cognitive Science and Psychology, advised by Jennifer Trueblood at Indiana University and my Masters in Psychological Sciences from Vanderbilt University. (CV) (Google Scholar)

I combine computational and experimental methods to study cognitive decision-making, focusing on the interplay between perception and attention with decision making. My research explores the interaction between human and machine cognition, aiming to use insights from one to improve the other.

1. How do we use machine intelligence to understand and improve humans?
   We find that one can use the representations from deep neural networks to find and fix inconsistencies in human (novice) decisions. These representations can be used to develop cognitive models to understand decision making patterns at the individual level .
2. What is attention and how does it shape learning and decision making?
   We must decide how to decide what information is worth sampling. This information is then used to make decisions. So, an intelligent agent has to learn the important associations but also learn what to attend to. I am interested in studying how we decide to attend and how this information impacts downstream behavior.
3. How do we use collective human intelligence to train machines?
   We find that if you put enough novices together, they can classify white blood cell images better than experts. When you crowdsource people from an app, the best approaches model individual decision idiosyncrasies and task features. If you only select the best people to annotate skin lesion medical data, you fail to get a sense of the uncertainty and might miss out on the rarer classes.
4. How do cognitive processes interact with decision making?
   We find that in a choice display with three items (ABC), the presentation order (e.g., BAC, CBA, ACB) impacts decisions potentially because one might pay more attention to the differences and compare neighboring options. However, manipulating attention processes by making alternatives salient impacts choice by creating a salience selection bias but does not change comparisons.
5. How do we scale experimentation and modeling?
   We conducted an exploratory registered report, recruiting more than 2000 individuals and assigning them to one of 144 conditions to conduct a large experiment in multi-attribute choice. In another project, we used a switchboard analysis to test hundreds of wisdom of the crowd models.

I always have time to chat about life, the universe, and everything. Shoot me an email!

See Publications, Projects, Computational Methods, Background, CV Google Scholar

News

• April 2026: I won the internal Decision Science Collaborative Grant for my project on the representations of white blood cells.
• April 2026: I was interviewed by the Smooth Brain Society about wisdom of the crowds, representations and depression on social media link
• March 2026: I presented my work at the Center for Conflict and Cooperation at NYU
• November 2025: I presented our work on the Switchboard Analyses at Mathematical Psychology at Psychonomics
• August 2025: I started my postdoc with Brandon Turner
• May 2025: I finished my PhD!
• April 2025: I won the Outstanding Researcher Award at Indiana University
• April 2025: Indiana University published a short piece on our PNAS Nexus article link
• March 2025: Our paper on Depression on Social Media got published at PNAS Nexus. open access link
• Jan 2025: Our paper on the impact of presentation effects on the attraction effect got Published at Judgment and Decision Making open access link
• ...
• August 2022: I moved to Indiana University along with Jennifer Trueblood
• August 2019: I started my PhD at Vanderbilt University