Tutorial 4 Presenter Bios

Tutorial: Human-Centered Evaluation of Explanations

Jordan Boyd-Graber

University of Maryland

Jordan Boyd-Graber is an associate professor at the University of Maryland, with joint appointments between computer science, the iSchool, language science, and the Institute for Advanced Computer Studies. He has been teaching using a flipped classroom approach since 2013. He and his collaborators helped end the use of perplexity for topic models (Chang et al., 2009), first developed interactive topic models (Hu et al., 2011), and improved word-level analysis of topic model explanations (Lund et al., 2019).

Samuel Carton

University of Chicago

Samuel Carton is a postdoctoral researcher at the University of Chicago. His interests lie in model interpretability and human-AI interaction.

Shi Feng

University of Chicago

Shi Feng is a postdoctoral researcher at the University of Chicago. His research interests include interpretable NLP, adversarial robustness, and alignment.

Vera Liao

Microsoft Research Montreal

Vera Liao is a Principal Researcher at Microsoft Research Montreal, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics) group. She is an HCI researcher by training, with current interest in human-AI interaction and explainable AI.

Tania Lombrozo

Princeton University

Tania Lombrozo is the Arthur W. Marks ’19 Professor of Psychology at Princeton University. She is a leading expert in understanding explanations.

Alison Smith-Renner

Dataminr

Alison Smith-Renner is a Senior Research Scientist in human-AI interaction at Dataminr. Her research interests include explainable and interactive natural language processing from a human-centric perspective.

Chenhao Tan

University of Chicago

Chenhao Tan is an assistant professor of computer science at the University of Chicago, and is also affiliated with the Harris School of Public Policy. His research interests include natural language processing, human-centered AI, and computational social science.