Published: November 2018, Issue: Vol. 30/No.10, Download as PDF

Archive of articles published in the Current Issue issue.

New from CRA: Database of Candidates for Academic and Industrial/Government Laboratory Positions


CRA has started a new service intended to improve the recruiting process for academic and industrial/government laboratory research positions.

Candidates for these positions can upload their resumes, research and teaching statements, job objectives and other preferences, and a link to a presentation video. Recruiting officers with access are able to search this information and are encouraged to contact candidates.

The database can be accessed through https://cra.org/cv-database/. For further information, including an instructional video, visit: https://cra.org/cv-database/#Info.

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Expanding the Pipeline: CRA-W Expands Research Mentoring at the 2018 Grace Hopper Celebration of Women in Computing


The 2018 Grace Hopper Celebration of Women in Computing (GHC) broke its attendance records again, with more than 20,000 participants gathering in Houston, Texas, from September 26th through September 28th, and CRA-W also broke its attendance records with a variety of programs for GHC attendees interested in research. From talks, panels, and mentoring circles to the CRA-W Research Scholars Program to poster presentations and sponsorship of other sessions, CRA-W played an important role at the conference.

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CRA Board Member Highlight: Rachel Pottinger


Increasingly, jobs rely on the ability to use computers to interpret, understand, and trust data. For example, my students and I have worked with ornithologists who cannot understand the representations of their bird sightings, civil engineers who cannot easily use their own building data, finance experts who cannot trace money between companies and their subsidiaries, and an XML document company whose clients cannot understand data that appears outside of their reports. In each case, the data users have been hampered because their data is exceedingly difficult to understand and trust, even though the users are experts in their fields. One reason for this difficulty is that the organization of the data is often designed for computers, not for people (i.e., for storage, not accessibility). Another reason is that data often come from different sources, leaving users with the challenge of integrating data that they neither understand nor trust.

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CRA Board Member Highlight: Barbara G. Ryder


My computer science research career started during my college internship at Bell Laboratories in Murray Hill, New Jersey, during the early 1970s in the center that later produced UNIX and the portable C compiler. This experience taught me that computing was broader than the introduction to scientific programming in my undergraduate studies in applied math. (There was no computer science undergraduate major at the time.) For most of my career, I was interested in deriving descriptions of program execution behaviors from code in order, for example, to optimize program time and/or memory performance, to validate desirable properties such as correctness or data security, or to refactor code for ease of maintenance.

Increasing diversity in computing has been my passion throughout my career, mostly through my informal mentoring of female CS students at Rutgers and Virginia Tech, participating in CRA-W mentoring workshops, and leading efforts in CS at Virginia Tech College of Engineering to join with NCWIT to increase the gender diversity of our CS students.

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NSF DCL- EArly-concept Grants for Exploratory Research on Artificial Intelligence (AI) and Society – Supported Jointly with the Partnership on AI


The goal of this Dear Colleague Letter, which specifically mentions the Computing Community Consortium (CCC) AI Roadmap, is to encourage the submission of EAGERs on understanding the social challenges arising from AI technology and enable scientific contribute to overcoming them.