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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.
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Reviews by Franz J Kurfess |
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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 ...
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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...
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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...
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Image processing techniques for detecting and classification of plant disease: a review Hungilo G., Emmanuel G., Emanuel A. IMIP 2019 (Proceedings of the 2019 International Conference on Intelligent Medicine and Image Processing, Bali, Indonesia, Apr 19-22, 2019) 48-52, 2019. Type: Proceedings
For experienced farmers and biologists, detecting and identifying plant diseases is usually fairly straightforward: they are familiar with the most common problems related to their crops and can use visual inspection, possibly in combi...
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A systematic literature review on intelligent user interfaces: preliminary results Gonçalves T., Kolski C., de Oliveira K., Travassos G., Grislin-Le Strugeon E. IHM 2019 (Proceedings of the 31st Conference on l’Interaction Homme-Machine, Grenoble, France, Dec 10-13, 2019) 1-8, 2019. Type: Proceedings
Designers of user interfaces often face a fundamental dilemma: how much of the underlying functionality of the system should they expose to the user? An experienced user may want direct access to most, or all, of the functionality, whi...
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