Eliciting Configuration Design Heuristics with Hidden Markov Models

McComb, C., Cagan, J., and Kotovsky, K. 2017, International Conference on Engineering Design Configuration design problems, characterized by the selection and assembly of components into a final desired solution, are common in engineering design. Although a variety of...
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Impossible by Design? Fairness, Strategy, and Arrow’s Impossibility Theorem

McComb, C., Goucher-Lamber, K., and Cagan, J. 2017, Design Science, vol. 3(2) The design process often requires work by teams, rather than individuals. During team based design it is likely that situations will arise in which individual members of the team have...
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Capturing Human Sequence-Learning Abilities in Configuration Design Tasks through Markov Chains

McComb, C., Cagan, J., and Kotovsky, K. 2017, Journal of Mechanical Design, vol. 139(9), pp. 1-12. Designers often search for new solutions by iteratively adapting a current design. By engaging in this search, designers not only improve solution quality but also begin...
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Mining Process Heuristics from Designer Action Data via Hidden Markov Models

McComb, C., Cagan, J., and Kotovsky, K. 2017, Journal of Mechanical Design Configuration design problems, characterized by the assembly of components into a final desired solution, are common in engineering design. Various theoretical approaches have been offered for...
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Research and Practice Group Methodology: A Case Study in Student Success

McComb, C., and Tehrani, F.M 2014, ASEE Pacific-Southwest Conference Experiential learning is a key component in engineering education. In civil engineering, this component is typically delivered through multiple projects. These projects may include term projects for...
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Human system can mean many different things. In this lab, we look at it in three different ways:

Systems of Humans

  • Can we build accurate simulations of problem-solving teams?
  • How can be make organizations more efficient and effective?

Systems for Humans

  • In what way can intelligent tools boost human performance?
  • Can intelligent design tools be developed that mimic expert behavior?

Systems + Humans

  • What are the implications of merging humans and machines as equal partners?
  • What does an intelligent algorithm need to truly contribute?

Our research interests span the entire spectrum of human systems. Some examples of our research include discovering how to effectively manage and organize design teams and multi-team organization, designing computational algorithms that mirror human learning patterns, and developing new methods for rapidly analyzing renewable energy technology. If research like this sounds interesting to you, please take a look at our open positions.