The Frontiers Where Psychology Meets Affective Computing
Researchers from different fields often have very different goals, methods, and expectations for conducting and evaluating work. This diversity can present challenges to an interdisciplinary researcher, but it also provides opportunities for the exchange of valuable insights and tools across fields. In this talk, I argue that psychology and computer science have critical contributions to make, not only to the interdisciplinary field of affective computing, but to one another. Using examples from my own research, I highlight the theoretical and statistical clarity that psychology can offer to computer science, as well as the precision and efficiency that computer science can offer to psychology. Specific examples of work that will be discussed include the automated assessment of clinical depression, the study of cultural differences in facial behavior, the relationship between interpersonal communication and spontaneous head motion, and the statistical analysis of errors in the generalizability of an automated facial expression analysis algorithm.
Jeffrey Girard is a doctoral candidate in clinical psychology at the University of Pittsburgh. His work takes a deeply interdisciplinary approach to the study of human behavior, drawing insights and tools from psychology, computer science, and statistics. He is particularly interested in developing and applying technology to advance the study of emotion, interpersonal communication, and psychopathology (e.g., depression). Jeffrey offers a unique and valuable perspective to the affective computing community, especially regarding research design, statistical analysis, and clinical applications.