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Björn Hartmann
Researcher at University of California, Berkeley
Publications - 118
Citations - 9005
Björn Hartmann is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: User interface & Crowdsourcing. The author has an hindex of 47, co-authored 114 publications receiving 8114 citations. Previous affiliations of Björn Hartmann include Microsoft & Stanford University.
Papers
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Proceedings ArticleDOI
Collaboratively crowdsourcing workflows with turkomatic
TL;DR: It is argued that Turkomatic's collaborative approach can be more successful than the conventional workflow design process and implications for the design of collaborative crowd planning systems are discussed.
Proceedings ArticleDOI
What would other programmers do: suggesting solutions to error messages
TL;DR: HelpMeOut, a social recommender system that aids the debugging of error messages by suggesting solutions that peers have applied in the past is introduced, which can suggest useful fixes for 47% of errors after 39 person-hours of programming in an instrumented environment.
Journal Article
Implementing Expressive Gesture Synthesis for Embodied Conversational Agents
TL;DR: In this article, a computational model of gesture quality is presented to characterize bodily expressivity with a small set of dimensions derived from a review of psychology literature, and a detailed description of the implementation of these dimensions in animation system, including gesture modeling language is provided.
Proceedings ArticleDOI
Learning syntactic program transformations from examples
Reudismam Rolim,Gustavo Soares,Loris D'Antoni,Oleksandr Polozov,Sumit Gulwani,Rohit Gheyi,Ryo Suzuki,Björn Hartmann +7 more
TL;DR: Refazer as mentioned in this paper is a technique for automatically learning program transformations from examples of code edits performed by developers to fix incorrect programming assignment submissions, which can be used as input-output examples to learn program transformations.
Book ChapterDOI
Implementing expressive gesture synthesis for embodied conversational agents
TL;DR: This paper presents a computational model of gesture quality, characterize bodily expressivity with a small set of dimensions derived from a review of psychology literature, and describes the implementation of these dimensions in the animation system, including the gesture modeling language.