  Humans are talented with the ability to perform diverse interactions in the
teaching process. However, when humans want to teach AI, existing interactive
systems only allow humans to perform repetitive labeling, causing an
unsatisfactory teaching experience. My Ph.D. research studies Interactive
Machine Teaching (IMT), an emerging field of HCI research that aims to enhance
humans' teaching experience in the AI creation process. My research builds IMT
systems that exploit and guide user interaction and shows that such in-depth
integration of human interaction can benefit both AI models and user
experience.
