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   Lee, Myeong ; Butler, Brian S. ( February 2019 , Journal of the Association for Information Science and Technology)
2. Description–experience gap under imperfect information: Information continuum and aggressive cost estimating in capital projects

   https://doi.org/10.1108/ECAM-02-2018-0075  

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3. On the Information Leakage in Private Information Retrieval Systems

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   Guo, Tao ; Zhou, Ruida ; Tian, Chao ( June 2020 , 2020 IEEE International Symposium on Information Theory (ISIT))
4. Mutual Information in Community Detection with Covariate Information and Correlated Networks

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   Mayya, Vaishakhi ; Reeves, Galen ( September 2019 , 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton))

   We study the problem of community detection when there is covariate information about the node labels and one observes multiple correlated networks. We provide an asymptotic upper bound on the per-node mutual information as well as a heuristic analysis of a multivariate performance measure called the MMSE matrix. These results show that the combined effects of seemingly very different types of information can be characterized explicitly in terms of formulas involving low-dimensional estimation problems in additive Gaussian noise. Our analysis is supported by numerical simulations. 

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5. From Information to Ideas: How Designers Structure Information to Support Idea Generation

   https://doi.org/10.1115/DETC2020-22527  

   Damen, Nicole B. ; Toh, Christine A. ( August 2020 , International Design Engineering Technical Conferences)

   null (Ed.)

   Design can be seen as a series of decisions that are informed by information that the designer has gathered from the environment and transformed into actionable knowledge. The sheer volume and variety of available information compels designers to impose structure upon the desired information, which in turn may affect subsequent design activities. To better understand how information may inform design decisions, this study investigates the relationship between designers’ information organization behaviors and their generated ideas by recruiting eight professionals (four from software design and four from graphic design) for individual 3-hour design sessions. They were asked to generate ideas for a design problem (reducing pedestrian accidents in Nebraska) using the provided information. Results reveal that designers structured the information in three different ways (Clusters, Relations, and Nests), and both designer background and organizational strategy display different roles in the features generated in their ideas. 

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