Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

The Computing Community Consortium At Three – A Quick Self-Assessment

May 16th, 2010 / in big science, policy, research horizons / by Ed Lazowska

The Computing Community Consortium was launched three years ago –- in the Spring of 2007. The “long version” of what we’ve been up to is detailed in a formal self-assessment submitted to NSF in the Summer of 2009. The “PowerPoint version” is contained in an overview slideset. Here, I’m going to focus on just a few specific activities, to argue the benefits of having our act together as a field.

Broad agenda-setting

During the transition period to the Obama administration, we had the opportunity to feed a number of “white papers” into the transition team’s planning process.  Thanks to the receptiveness of the incoming administration, these white papers had impact far beyond what we had dared to imagine.

Our approach was to focus on the fact that fundamental advances in computer science and computer engineering are essential to meeting the nation’s challenges and achieving the nation’s priorities.  America’s energy future, from transportation to the smart grid, depends essentially on fundamental advances in computer science and computer engineering.  Ditto for the transformation of health care.  Ditto for the future of education.  Ditto for 21st century data-driven discovery — “eScience” — which will be transformational, ubiquitous, and driven by fundamental advances in computer science and computer engineering.

This approach does not position our field a “tool” of other fields, because it is not about applying today’s technology.  Rather, it focuses on the fundamental advances in computer science and computer engineering that will be necessary to meet the nation’s challenges and achieve the nation’s priorities.

This work was done pro bono by a small number of people.  (Committees produce consensus; leaders produce visions.)  And it was carried out as what computer architects would call “speculative execution” — effort devoted in the belief that it might prove to be useful.  (If you wait until someone asks you for something, it’s too late — you need to have it ready!)

Focused agenda-setting

The CCC funds workshops initiated by members of sub-fields who want to chart a future direction.  Some of these have been hugely influential.

A great example is a robotics effort led by Henrik Christensen (Georgia Tech), Vijay Kumar (Penn), Matt Mason (CMU), and others.  This broad community effort, carried out over a period of 18 months, yielded a coherent direction for fundamental research in robotics, a set of “research roadmaps” for the field, and a white paper that is likely to result in a significant federal research initiative during the next fiscal year.

Computing Innovation Fellows

During the 2008-09 academic year it became clear that, due to the economic downturn, many extremely strong Ph.D. graduates would “exit the research game” due to lack of employment opportunities at universities and industrial research labs — sacrificing the nation’s investment in their education, and jeopardizing the nation’s future competitiveness.

Computer science had never had a broad-based coordinated postdoc program, but the Computing Community Consortium, working closely with NSF, was able to establish the Computing Innovation Fellows Project in remarkably short order — from concept to awards in less than six months.  It was NSF’s confidence in CCC as a “proxy” for the computing research community that made this possible.

The CIFellows Project had several unique aspects that we expect to have broad impact.  The first was the “max 2 rule” — at most two awardees were allowed to come from, or go to, any one institution.  (The goal was to establish persistent interactions between diverse institutions.)  The second was an ordering of the holistic quality assessment of candidates:  at each iteration (as the field was reduced from 500+ proposals to 60 awards), members of under-represented groups (women, minorities, particular research areas, etc.) were discussed first.  When the dust had settled, 42% of CIFellows awardees were women!  (To be clear:  gender only influenced the order of discussion!)


There’s lots more to say, but this is getting long for a blog post.  The bottom line is that a group of community-oriented research leaders can have a profound effect, given the endorsement (confidence and good will) of the research community, and the right environment in Washington.

There are many, many ways in which you can participate.  See the CCC web page for ideas!

The Computing Community Consortium At Three – A Quick Self-Assessment
  • jc264

    You said, “When the dust had settled, 42% of CIFellows awardees were women! (To be clear: gender only influenced the order of discussion!)”

    I don’t believe this is true. According to the published algorithm, 1-5 points were assigned for each of three categories, for each application. Then an additional 2 points were given if the applicants were: American citizens or permanent residents; women; minorities.

    So, if you had none of these attributes, your score would range between 3 – 15. If you were a woman, your score would range between 5 – 17; minority women had a minimum range between 7 – 19.

    You mentioned that 42% of the awards went to women. However, only 27% of the initial applicants were women. This isn’t proof, of course, but it indicates there may be a bias. Coupled with the designed bias of the selection algorithm, I don’t think you can claim that “gender only influenced the order of discussion.”

    The published algorithm can be found here: