Master’s Thesis Presentation • Human-Computer Interaction — Towards the Learning, Perception, and Effectiveness of Teachable Conversational Agents
Nalin Chhibber, Master’s candidate
David R. Cheriton School of Computer Science
Nalin Chhibber, Master’s candidate
David R. Cheriton School of Computer Science
Alexandra Vtyurina, PhD candidate
David R. Cheriton School of Computer Science
Ryan Goldade, PhD candidate
David R. Cheriton School of Computer Science
Yuhao (Eric) Dong, PhD candidate
David R. Cheriton School of Computer Science
Alex Williams, PhD candidate
David R. Cheriton School of Computer Science
Sajjad Rizvi, PhD candidate
David R. Cheriton School of Computer Science
Alex Williams, PhD candidate
David R. Cheriton School of Computer Science
Peoples’ work lives have become ever-populated with transitions across tasks, devices, and environments. Despite their ubiquitous nature, managing transitions across these three domains has remained a significant challenge. Current systems and interfaces for managing transitions have explored approaches that allow users to track work-related information or automatically capture or infer context, but do little to support user autonomy at its fullest.
Silvia Abrahão, Department of Computer Science
Universitat Politècnica de València
Meng Xu, School of Computer Science
Georgia Institute of Technology
Ryan Smith, Associate investigator
Laureate Institute for Brain Research