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Franz J Kurfess
Cal Poly SLO
San Luis Obispo, California
 

Franz J. Kurfess joined the Computer Science Department of California Polytechnic State University in the summer of 2000, after a short stay with Concordia University in Montreal, Canada, and a longer stay with the New Jersey Institute of Technology. Before that, he spent some time with the University of Ulm, Germany, as a postdoc at the International Computer Science Institute in Berkeley, CA, and at the Technical University in Munich, where he obtained his MS and PhD in Computer Science.

At Cal Poly, he is the coordinator of the human-computer interaction lab, and teaches courses in the areas of artificial intelligence, knowledge-based systems, user-centered design and development, and human-computer interaction. His main areas of research are artificial intelligence and human-computer interaction, with particular interest in the usability and interaction aspects of knowledge-intensive systems. He is currently investigating a framework for the analysis of “interaction spaces,” consisting of the physical space where interaction between humans and computational systems takes place, and a conceptual space delineated between the shared communication channels, symbol systems, vocabularies and languages, and the conceptual model of the domain and the world. So far, humans have been able to accommodate the limitations of computational systems concerning such interactions fairly well. When expanding interaction to situations where robots (or computational systems in general) have to communicate with other robots, it becomes much more critical to have a coherent framework for interaction in place.


     

Attention models in graphs: a survey
Lee J., Rossi R., Kim S., Ahmed N., Koh E. ACM Transactions on Knowledge Discovery from Data 13(6): 1-25, 2019.  Type: Article

Having spent some time on early attempts to bring together neural networks and symbol-oriented knowledge representation, I am intrigued by the more recent work on deep learning and knowledge graphs. While many of the approaches appear ...

 

Machine learning education for artists, musicians, and other creative practitioners
Fiebrink R. ACM Transactions on Computing Education (TOCE) 19(4): 1-32, 2019.  Type: Article

Together with colleagues from computer science, agriculture, food science, biology, and related fields, I am currently working on a framework for teaching artificial intelligence (AI) and machine learning (ML) to students and practitio...

 

Objects with intent: designing everyday things as collaborative partners
Rozendaal M., Boon B., Kaptelinin V. ACM Transactions on Computer-Human Interaction 26(4): 1-33, 2019.  Type: Article

As electronics shrink and become cheaper, everyday objects can be endowed with significant computational capabilities. An observer or user can then perceive aspects of agency and intelligence in such objects. In this paper, the authors...

 

 Inclusive design for a digital world: designing with accessibility in mind
Gilbert R., Apress, New York, NY, 2019. 272 pp.  Type: Book (978-1-484250-15-0)

Having taught courses in user-centered design (UCD) and human-computer interaction (HCI) for over 20 years, I am familiar with both the history of the field and the methods and tools currently in use. On several occasions, I’...

 

 Guidelines for human-AI interaction
Amershi S., Weld D., Vorvoreanu M., Fourney A., Nushi B., Collisson P., Suh J., Iqbal S., Bennett P., Inkpen K., Teevan J., Kikin-Gil R., Horvitz E.  CHI 2019 (Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, UK, May 4-9, 2019) 1-13, 2019.  Type: Proceedings

From a human-computer interaction (HCI) perspective, the arrival of virtual assistants (for example, Alexa, Siri, Google Assistant, and Bixby) has led to a shift in interaction mode from visual to speech-based: instead of manipulating ...

 
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