I will also claim the Human-Computer InteracXiong Lab, the PercepXiong and CogniXiong Lab, and the DeciXiong-Making lab.

We conduct experiments to understand how humans interpret data and make decisions using visualizations, generating guidelines for visualization tools that help people more effectively explore and communicate data to make decisions. Some questions we are interested in answering include...

1. How do people make comparisons in data? How can we design natural language visualization tools to support comparisons in visual analysis?
2. How are people biased when interpreting data? Why do these biases happen? How can we design information systems that mitigate them?
3. How do people synthesize information across multiple sources? How can we design tools to help people more effectively seek and synthesize information?
4. How do we design trustworthy visualizations? What are the ethical and practical implications of studying trust and data storytelling in human-data interaction?

The output of our work also directly impacts policy. We are working with the local district attorney’s office to examine the effects of transparent data communication and visualization techniques on public trust and institutional legitimacy. PI Xiong is also an affiliate with the Human Factors Task Group at the National Institute of Standards and Technology, where she helps evaluate and improve standards in forensic science investigations to reduce cognitive bias in training and practice, especially in scenarios that involve the use of technologies.