Archive of articles published in the 2016 issue.

2018 IBM Two-Year Worldwide PhD Fellowship


IBM is pleased to announce the 2018 IBM Two-Year Worldwide PhD Fellowship for the academic years of 2018-2019 and 2019-2020.  Strong collaboration with faculty, students and universities is vital to IBM. The PhD Fellowship Program advances this collaboration by recognizing and supporting exceptional PhD students who want to make their mark in promising and disruptive technologies.

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Executive Q&A: Jeannette M. Wing, Head of Microsoft Research


Microsoft is a Lab and Center member of CRA. This article is the second in a series of our industry member profiles.

Jeannette M. Wing joined Microsoft Research in January 2013, after holding positions in academia and government, most recently at Carnegie Mellon University and the National Science Foundation (NSF). From 2007 to 2010, she served as assistant director of the Computer and Information Science and Engineering Directorate at the NSF. Wing is a former CRA board member and recipient of the 2011 CRA Distinguished Service Award. Her areas of expertise are in trustworthy computing, formal methods, concurrent and distributed systems, programming languages, and software engineering.

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It’s Not About the Money: Optimizing Academic-Industrial Partnerships


Today, more than ever, industry leaders are looking to partner with academic computer science programs. With available computer science expertise at a premium, they’re looking for ideas, for new hires, and for help on crucial projects. Universities are the mother lode for the personnel and expertise they crave. On July 18, I presented at the CRA Conference at Snowbird session titled “Local Corporate Labs, Centers and Development Offices: Optimizing Department/Industry,” which explored the growth of corporate lab culture, and I’d like to share some of insights from that talk.

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After Leaving Computing, New Majors Tend to Differ by Gender


As computing departments across the U.S. wrestle with increased enrollment, it is important to recognize that not everyone who becomes a computing major stays a computing major. In 2014, CERP collected data from a cohort of U.S. undergraduate students who agreed to be contacted for follow-up surveys in 2015. While most of the students surveyed remained computing majors (96%), some students changed to a non-computing major. As shown in the graphic above, students in our sample moved to a variety of majors, and the type of new major tended to differ by gender. Most men (69%) who left a computing major switched to engineering, math/statistics, or physical science majors. On the other hand, most women (53%) tended to move to social sciences, or humanities/arts. These data are consistent with existing social science research indicating women tend to choose fields that have clear social applications, such as the social sciences, arts, and humanities. CERP’s future analyses will explore why women, versus men, say they are leaving computing for other fields.

Note this summary of longitudinal survey data is suggestive and is intended to spur further empirical investigation. Given our sample size, we did not run inferential statistics and do not claim the gender differences are significantly different. As such, the findings reported here should be interpreted with caution.

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Expanding the Pipeline: The 2016 ACM Richard Tapia Celebration of Diversity in Computing Shows Inclusion Matters


The 10th annual ACM Richard Tapia Celebration of Diversity in Computing (hashtag #Tapia2016) was held in Austin, Texas, on September 14-17. This year’s conference had a record-breaking 965 attendees, achieving 20 percent growth over 2015. Eighty sponsors and 150 colleges and universities were represented. With the theme “Diversity Matters,” the Tapia conference brought together students, faculty, researchers, and professionals from all backgrounds and ethnicities in computing, and is the premier venue to promote and celebrate diversity in the field. The Tapia conference was sponsored by the Association for Computing Machinery (ACM) and presented by the Center for Minorities and People with Disabilities in IT (CMD-IT).

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How to Engage Your Alumni: The Story of UMD’s New Iribe Building


As computer science departments across the country grow rapidly, we all may feel overwhelmed by the staggering growth of our enrollments. While faculty growth still has not caught up with the influx of students, we cannot be anything but happy at the diversity of students who are choosing to become computer science majors. Many people may believe that alumni engagement begins after students earn their diplomas. That assumption is false. Alumni engagement begins the moment that students start their education in our departments. With planning, outreach, and genuine interest in their lives and careers, we make alumni engagement an important part of our mission in the Computer Science department at the University of Maryland (UMD).

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Thoughts from White House Frontier’s Conference and the National AI R&D Strategic Plan


Last month, the President hosted the White House Frontiers Conference in Pittsburgh, an event that was co-hosted by the University of Pittsburgh and Carnegie Mellon University and attended by hundreds of scientific leaders in our community.

The Computing Community Consortium (CCC) Chair and Director attended the event, which had many speakers from previous CCC events.

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South Big Data Hub DataStart Highlights


As a result of the CCC / CRA Industry Academic Survey, conducted in spring of 2015 and the CCC Industry Roundtable Discussion held on July 24, 2015, the CCC partnered with the four NSF-sponsored Big Data Regional Innovation Hubs (BD Hubs) for a program on industry-academic collaboration. Each Hub is charged with addressing regional specific big data challenges. Areas of emphasis for the South BD hub include coastal hazards, industrial big data, and health analytics, among others.

As one of its CCC-sponsored activities, the South BD Hub ran the DataStart internship program, which paired graduate students from the South Regional Innovation Hub with data-related startup companies for three months.

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World’s Largest Technology Companies Create Historic Partnership on AI


In a recent blog post, we summarized the report of an academic/industry roundtable, which, among other recommendations, advocated for mechanisms to support long-term, strategic, and sustained conversation between academics and industry representatives. Recently, one such mechanism came into being with the announcement of the Partnership on AI by a consortium consisting of Microsoft, Google, Amazon, Facebook, and IBM.

Announcements


Nominations Open for 2017 CRA-E Undergraduate Research Faculty Mentoring Award
Due November 28

Nominees Sought for CRA Board of Directors
Due December 2

Nominations Open for CRA Distinguished Service and A. Nico Habermann Awards
Due December 9

CRA-E Graduate Fellows Program Accepting Applications
Due January 30, 2017

CRA Grad Cohort 2017 Applications Open
Due November 30

CRA-Education to Host Workshop at Supercomputing 2016
“Best Practices in Mentoring Undergraduate Research in Supercomputing”

Are you working on the Taulbee Survey?
The CRA Taulbee Survey is in progress. The deadline for the salary section is November 18 and the deadline for the rest of the survey is January 18, 2017.

If you are the academic unit head of a U.S. or Canadian department granting doctoral degrees in Computer Science, Computer Engineering, and/or Information, you should have received emails about the survey. If you did not, please check with the CRA Director of Statistics, Dr. Betsy Bizot, at bizot@cra.org.

Applications for NCWIT Aspirations in Computing Awards Are Open
Calling all teachers, counselors, administrators, mentors, or other influencers who support high school women’s passion for computing and technology! Applications for the National Center for Women & Information Technology (NCWIT) Aspirations in Computing Educator Award are open through November 28, 2016. Each winner receives $250 in cash and up to $750 for participation in computing-related professional development activities, recognition at a local Affiliate Award event and increased visibility in his or her school district and community, NCWIT resources and promotional items, as well as an engraved award for both the Educator and his or her school. Educators can apply online at http://bit.ly/AiCEdAward no later than 11:59 p.m. EST on November 28, 2016.

Call for ACM Karl V. Karlstrom Outstanding Educator Award Nominations
The Karlstrom Award is presented annually to an outstanding educator who is appointed to a recognized educational baccalaureate institution; recognized for advancing new teaching methodologies; effecting new curriculum development or expansion in computer science and engineering; or making a significant contribution to ACM’s educational mission. Those teachers with ten years or less experience are given special consideration.

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Computing Research and the Emerging Field of Data Science


Our ability to collect, manipulate, analyze, and act on vast amounts of data is having a profound impact on all aspects of society. This transformation has led to the emergence of data science as a new discipline. The explosive growth of interest in this area has been driven by research in social, natural, and physical sciences with access to data at an unprecedented scale and variety, by industry assembling huge amounts of operational and behavioral information to create new services and sources of revenue, and by government, social services and non-profits leveraging data for social good. This emerging discipline relies on a novel mix of mathematical and statistical modeling, computational thinking and methods, data representation and management, and domain expertise. While computing fields already provide many principles, tools and techniques to support data science applications and use cases, the computer science community also has the opportunity to contribute to the new research needed to further drive the development of the field. In addition, the community has the obligation to engage in developing guidelines for the responsible use of data science.