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Current Research



Ongoing Projects @ CORE

Research Methdology Development






Developing Tools to Improve Survey Research

Much of our research is concerned with ways to improve the process of collecting self-report survey data. We explore ways to make the process more accessible, efficient, and scalable. Examples include:

• Generating and Recommending personality scale items through Artificial Intelligence

• Developing tools to collect audio data through popular survey platforms




Minimizing Fabrication and Falsification from Survey Data

Our research explores the ways in which both respondents and researchers might fabricate, manipulate, or misrepresent responses within survey data. Furthermore, we aim to develop and compare methods for detecting the presence of fabricated data. Examples include:

• Detecting fabrication by researchers and third-party services who collect survey data

• Detecting faking in personality surveys by respondents using machine learning






MACHINE LEARNING and DIVERSITY & INCLUSION






Developing Tools to Improve Examining Diverse Populations

Studying diverse populations often requires the use of methods capable of capturing subtle nuances in behavior and perception. This also necessitates the use of tools that ensure fairness across various intersections. Our research develops innovative methods to study underrepresented groups, harnessing advances in machine learning to create tools that enable scalable inferences in ways not achievable with traditional methods. Examples include:

• Inferring demographics from organizations

• Improving image classification models to draw individual inferences from images of people




Applying Machine Learning to Examine Diverse Populations

Our research program also applies computational methodologies to advance our understanding of intergroup differences and diversity within a group. These approaches leverage the unique benefits that technology offers to quantify and analyze the often subtle ways that psychological processes manifest in diverse group settings. Examples include:

• Examining discrimination and attitudes towards marginalized groups within organizations

• Understanding perceptions and portrayals of underrepresented groups from natural language and images