Thursday, November 21, 2019
3:30 p.m., Avery 115
4:30 p.m., Avery 115
Daniel SzafirAssistant Professor, ATLAS Institute and Institute of Cognitive Science at the University of Colorado Boulder
Robots hold significant promise in their potential to assist humans with a wide variety of activities across social and domestic settings as well as critical domains such as manufacturing, healthcare, and space exploration. However, practical deployments involving human-robot teaming remain quite limited as humans and robots do not communicate well; people often find robots incomprehensible and have difficulties understanding what a robot can or will do, while robots lack computational models for reasoning about complex human behaviors. In this talk, I will discuss my research to address these issues by supporting more effective information exchange between humans and robots. Drawing on principles from cognitive engineering, I develop generalizable knowledge, methods, and techniques that enable robots to convey their actions and intentions to people in ways that are intuitive and comprehensible and introduce new approaches that enable robots to model and understand various forms of human input, with a focus on supporting natural interaction paradigms. By integrating these efforts, I will show how we can design new tools, systems, and technologies that make robots safer, more efficient, and even more enjoyable to work with.
Daniel Szafir is an Assistant Professor in the Department of Computer Science and the ATLAS Institute at the University of Colorado, Boulder. He holds courtesy appointments in the Ann and H.J. Smead Aerospace Engineering Sciences Department and the Department of Information Science at CU and is an affiliate of the CU Institute of Cognitive Science (ICS), the Research and Engineering Center for Unmanned Vehicles (RECUV), the Program in Culture, Language, and Social Practice (CLASP), and the Center for Neuroscience. Dr. Szafir works at the intersection of robotics and human-computer interaction to investigate the fundamental principles that underlie effective interactions between people and autonomous systems and his work has won best paper awards at ACM/IEEE HRI and HCII. His research draws on methods from human-robot interaction, cognitive science, and design to build new algorithms, interfaces, and systems that mediate user interaction with robotic technologies within the domains of collaborative work, education, emergency response, and space exploration. He completed his Ph.D. in Computer Science at the University of Wisconsin–Madison in 2015 and was named to the Forbes 30 Under 30: Science list in 2017. His research support includes NASA, the National Science Foundation, Google, Intel, and Mitsubishi Heavy Industries.