“A partnership model to effectively engage the research community in agenda-setting is the Computing Community Consortium (CCC). With support from the National Science Foundation, the CCC allows the computer science community to establish a vision for the field and quickly mobilize the community to pursue “big ideas.” Could this type of consortium work for the nanotechnology research community?”

For example, the RFA for NCER’s Education Technology program (RFA CDFA 84.305a) states:

To support research on education technology tools that are designed to provide or support instruction in reading, writing, mathematics, or science (including pre-reading, pre-writing, early mathematics, and early science) or to provide professional development for teachers related to instruction in reading, writing, mathematics, or science. The Institute intends to contribute to improvement of reading, writing, mathematics, and science learning by (1) developing innovative education technology tools intended to improve reading, writing, mathematics, science, or general study skills; (2) evaluating fully developed education technology tools intended to improve reading, writing, mathematics, science, or general study skills through efficacy or replication trials; (3) evaluating the effectiveness of fully developed education technology tools intended to improve reading, writing, mathematics, science, or general study skills that are implemented at scale; and (4) developing and/or validating assessments that use education technology and that can be used in instructional settings.

The long-term outcome of this program will be an array of education technology tools that have been documented to be effective for improving reading, writing, mathematics, and science achievement.

The Education Technology program — like all programs under the Education Research Grant Programs — accepts applications twice a year.

For more information about these and other funding opportunities through NCER, check out the center’s FY 2010 RFAs — http://ies.ed.gov/funding/10rfas.asp — and submit a proposal if your research is appropriately aligned.

(Contributed by Chase Hensel, CRA/CCC Tisdale Fellow)

Imbued with boundless patience and ability to recall facts, robots hold promise as effective teachers in high-repetition scenarios such as language class autism therapy. Teams from UCSD, MIT, UConn, etc., are field-testing teaching robots for a variety of uses. The results of these tests have been positive and the future use of robots in the classroom seems likely.

The article also discusses the Holy Grail of artificial intelligence — teaching machines to teach themselves, in the spirit of infant children. It perhaps overstates that we can obtain this Holy Grail in the near future; there’s considerable research and innovation that must come first.

Please check out the feature, and its associated media — the video on Robotic Teaching is particularly exciting.

- Learning to Read People; and

- A timeline detailing the history of Artificial Intelligence.

Share your thoughts — especially those on the future of AI as the article describes it — below.

(Contributed by Chase Hensel, CRA/CCC Tisdale Fellow, & Erwin Gianchandani, CCC Director)

Peter Lee

In joining Microsoft Research, Peter departs DARPA, where he has been the
Director of the agency’s Transformational Convergence Technology Office
(TCTO) for the past year. There Peter has

challenged conventional Department of Defense (DoD) approaches to computer science research by infusing new energy into [DARPA]’s relationships with academia and industry and reinforcing the agency’s unique role at the intersection of research and application.

Today, TCTO is re-establishing basic research programs in a broad range of
rapidly emerging computing-enabled technology areas such as social media,
synthetic biology, high-performance computing, and networking, as well as
employing a diverse range of innovation strategies including broad community programs, competitions/challenges, and crowd sourcing.

One of the highlights of his work at DARPA was the DARPA Network Challenge, which mobilized millions of people worldwide in a hunt for red weather balloons — a unique experiment in social media and open innovation that made an impact on thinking throughout the DoD.

For the past year, we’ve had one of our very best in a leadership position
at DARPA, and we thank Peter for his outstanding service and
wish him the best as he transitions into his new role.

Recent technological and societal trends

• Ubiquitous connectivity, and thus true mobility
• Massive computational capability available to everyone, through the cloud
• Exponentially increasing data volumes – from ubiquitous sensors, from higher-volume sensors (digital imagers everywhere!), and from the creation of all information in digital form – has led to a torrent of data which must be transferred, stored, and mined:  “data to knowledge to action”
• Social computing – the way people interact has been transformed; the data we have from and about people is transforming
• All transactions (from purchasing to banking to voting to health) are online, creating the need for dramatic improvements in privacy and security
• Cybercrime
• The end of single-processor performance increases, and thus the need for parallelism to increase performance in operating systems and productivity applications, not just high-end applications; also power issues
• Asymmetric threats, need for surveillance, reconnaissance
• Globalization – of innovation, of consumption, of workforce
• Pressing national and global challenges:  climate change, education, energy / sustainability, health care (these replace the cold war)

What’s on your list?  Please post below!

Historically, the computing industry has been driven by a set of exponential increases in single-thread performance. The ubiquity of multi-cores and the fact that much of the IT industry is relying on main-streaming parallel processing for survival is a truly seismic event. At the same time, there remains a huge gap between the theoretical limits of instruction-level parallelism (ILP) and what processors actually attain. Novel techniques to push ILP further in the familiar sequential execution model may yet to be invented. In this environment, one wonders if this is as good as it gets for ILP. Is ILP research over? Should it be? What are the truly new ideas and insights that can propel another three decades of exponential performance growth? How should ILP research be funded, performed and evaluated?

The wheels have come off the exponential track! – This Call for Position Papers is for the second of the two workshops and focuses on “Instruction Level Parallelism”; the first workshop focused on “Failure is Not an Option: Popular Parallel Programming”. For this second workshop, members of the computer architecture community are invited to submit a 1-page position paper outlining their thoughts on ILP research.

Some questions a submitter may wish to address are:

• Is there anything left to do with ILP research?

• Should funding agencies and industry support it?

• Should computer architecture conferences embrace it?

• What are the top 5 constraints on ILP in current microprocessors?

• What are the key new ideas and fruitful areas to explore in ILP?

• What is the role of re-configurability and heterogeneity in ILP?

• How to effectively support continuous run-time optimization in single-threaded systems?

Potential contributors are encouraged to be brief, and keep the following in mind:

• The position paper should not be about what you are working on currently; it should be about a vision for computer architectures available 10-15 years from now.

• There is no need to address all of the above questions. Addressing one or a few, or even others the submitter deems relevant is fine.

• Should computer architecture conferences embrace it?

• Keep the topic of ILP central.

• The steering committee will select the workshop invitees based on the responses. The committee is looking for a wide range of insightful, contrarian and forward thinking views.

Submit a 1-page PDF file to acar@cs.uiuc.edu by 6pm PST, August 6th, 2010.

Computational thinking has the potential to change the types of questions considered by social and economic scientists. For example, Nash (and other) equilibria lie at the heart of theories about the behavior of economic agents. Computational thinking can help characterize the range and robustness of possible equilibria and markets for which the computation of equilibria is intractable. Theories of strategic learning by computational agents, studied both in economics and computer science, can shed light on the dynamics of how agents arrive at equilibria. Theories of the spread of contagion or gossip in networks can help explain and contain the chain reactions that can arise. Social/behavioral/economic and computer scientists can jointly study the dynamic functioning and evolution of social and economic networks with mutual benefit to both fields of study. Some important examples of such systems are recommender systems, voting systems, and reputation management systems.

This new program came out of a workshop held last September at Cornell University that was well attended by computer scientists and economists alike. The report from the workshop provides an excellent introduction to this research area.

(Contributed by Lance Fortnow, Northwestern University)

The history of these assessments goes back to the Brooks/Sutherland National Academies study in 1995, and includes several reviews by the President’s Information Technology Advisory Committee (in particular the landmark 1999 PITAC report), and most recently a 2007 assessment by the President’s Council of Advisors on Science and Technology (PCAST).  The impact of these assessments on the direction of the NITRD program has been significant.

The  White House Office of Science and Technology Policy (OSTP) has convened a working group to conduct a new assessment, under the auspices of PCAST.  The assessment is to be carried out this summer.

Ed Lazowska (University of Washington, and chair of the Computing Community Consortium) co-chairs the working group, along with PCAST member David Shaw (D.E. Shaw Research).  Other members of the working group are Francine Berman (Rensselaer Polytechnic Institute), Stephen Brobst (Teradata Corporation), Randal Bryant (Carnegie Mellon University), Mark Dean (IBM Research), Deborah Estrin (UCLA), Ed Felten (Princeton University), Susan Graham (UC Berkeley), Bill Gropp (University of Illinois), Anita Jones (University of Virginia), Michael Kearns (University of Pennsylvania), Paul Kurtz (Good Harbor Consulting), and Bob Sproull (Sun Labs).

Members of the research community are invited to provide input to working group members regarding the nation’s IT R&D portfolio.

“And while we provide students from around the world visas to get engineering and computer science degrees at our top universities, our laws discourage them from using those skills to start a business or power a new industry right here in the United States. Instead of training entrepreneurs to create jobs on our shores, we train our competition.”

Read the full text here.

(Contributed by John Leslie King, University of Michigan)

This Sunday’s New York Times Magazine contains an incredibly fascinating expose about “Watson,” an advanced “question answering” machine that IBM researchers have been busy developing for the past half-decade.  The story provides a step-by-step account of the challenges and research advances underlying Watson’s development — including a detailed description of how Watson works today.  It chronicles early wins — and, notably, losses — for the supercomputer versus real-life former Jeopardy! contests.  And it describes ways in which natural language processing and data mining advances enabled by Watson’s development could be extended to other fields, like healthcare, e-government, and transportation.

This Sunday’s story is a must-read — and it’s just the first in a series titled “Smarter Than You Think” the NY Times is publishing this summer, describing recent advances in AI and robotics, and the potential impact of this work on society.

And don’t forget to try your luck against Watson in a simulated New York Times Web interactive.

(Contributed by Erwin Gianchandani, Director, CCC)

We are looking for your great ideas for how advances in computer and information science and engineering can transform the nature and conduct of healthcare and wellness as we know it today.

(Contributed by Jeannette Wing, Assistant Director for NSF/CISE)

Computing is a “general purpose” phenomenon.  It can be applied to many things, which brings heterogeneous communities to the discussion.  The computing research field has porous boundaries, making it an intellectual watering hole.  This offers stimulation and excitement, but it can cause problems.  People from different fields follow different conventions for doing or explaining their work.  Philipe van Parijs has addressed this as Clarity and Charity¹.  Here is the gist as I learned it.

When you are trying to make sense of new things, you shouldn’t assume that it’s entirely up to the authors to have those things make sense to you.  Authors should make things clear to the reader, but this is hard to do when writing for people from different fields.  The reader can and should help out.  A frustrated reader has usually invested a lot to understand the work already, but it is often worth investing a bit more to find out what the author “must be saying.”  The smart reader closes the gap between the author’s explanation and his or her understanding. Expect clarity, but when things are unclear, try some charity.  It’s a cost-effective strategy.

¹Philipe van Parijs, Evolutionary Explanations in the Social Sciences: An Emerging Paradigm, Totawa NJ: Rowman and Littlefield, 1981, pp. xiii-xiv (online version through Google Books).

(Contributed by John Leslie King, University of Michigan)

“CCC has played an important role in identifying and promoting exciting “visions” for the future of Information Technology (IT) research — ideas that have the potential to attract the best and brightest to the field, drive economic growth, and address national challenges in areas such as health, energy, and education …

“These papers and workshop reports have had a clear influence on Administration budget and recruiting decisions and have already sparked collaborations between government, industry, and academia. The agility and flexibility of the CCC is particularly important for a field like IT, which changes rapidly and has such a profound impact on science and engineering, the economy, and our society.”

Read the entire post here.

It’s remarkably how rapidly things are returning to a sane state!

First, I can’t believe that there weren’t more comments on John King’s terrific post,  “Fratricide and the Ecology of Proposal Reviews.”  This is serious business.  And it’s not “new news” — CISE has had the lowest average proposal scores in NSF for years.  We are killing ourselves in a misguided effort to show how smart we are.  (The number of “highly ranked proposals” that can’t be funded is, quite naturally, a criterion argued within NSF for the allocation of funds among Directorates.)  For god’s sake!

Second, the NSF Graduate Fellowship awardees have recently been announced.  Did you know that the number of fellowships awarded to each field is related to the number of applicants from that field?  And did you know that CISE has dramatically fewer applicants than other fields of comparable size?  Once again, we are killing ourselves.  Get with it!!

Third, many of you are aware that Jeannette Wing will be leaving CISE on June 30, after a truly spectacular run as CISE AD that has led to a dramatic increase in the recognition of our field as a “player” and as central to advances across-the-board.  We’ll have more to say about that in a subsequent post.  You may not know, though, that Debbie Crawford also is leaving her role as Deputy AD.  Debbie, too, is a star — she has been an extraordinary contributor.  In addition, all three CISE Division Directors are nearing the ends of their IPA appointments – Sampath Kannan (CCF), Ty Znati (CNS), and Haym Hirsh (IIS).  Sampath, Ty, and Haym — like Jeannette and Debbie — are tough acts to follow.  For the past few years we have had some of our very best in leadership positions at CISE.  Nothing could be more important than continuing this trend.  It’s all about leadership.

This story contains a lesson about the ecology of review processes. Reviewers rate proposals to determine which proposals to support, but that’s not the only use for their ratings. Leaders of funding agencies do not allocate funding to fields by reading all the agency’s proposals and reviews. They use summary measures. One of these is “proposal pressure,” meaning the number of highly-rated proposals within a field that cannot be funded because the field’s budget is too small. A field with more highly-rated proposals than it can support is “under-funded.” Right?

We in the computing research field often eviscerate the proposals of our colleagues during proposal reviews. Why are we so fratricidal? Is it to demonstrate how tough we are? If so, we’re hurting ourselves. People from other fields are happy to have fratricidal computing researchers in competition for interdisciplinary grants because there will be more funding for everyone else!

There are two kinds of responsibility in proposal review. One separates good proposals from weak proposals to ensure that good proposals are funded. The other ensures that computing research holds its own in funding with other fields. The computing research field gets better when we criticize weak proposals and recommend improvements. The field does not get better when our criticisms of each other are so harsh that that computing researchers get less of the pie.

(Contributed by John Leslie King, University of Michigan)

The Qinghai quake is the latest of the series of tragedies. Prof. Bin Li at the Shenyang Institute of Automation and an active member of the IEEE Technical Committee on Safety Security Rescue Robots, contacted the Chinese national earthquake response service this morning. It doesn’t look like ground robots are appropriate– the structures are mostly small and constructed from brick and mud. That type of construction is problematic– the brick and mud turns to a liquidized dust, acting like water to fill all the voids and displaces air. Even if there are voids, the suspended dust causes respiratory distress. Eric Rasmussen InSTEDD has many tales to tell of the similar Turkey earthquake.

China, by the way, does have at least one rescue robot. Bin tells me it was deployed to the mine collapse but could not be used because it wasn’t waterproof. (A gentle aside to manufacturers: d’uh!)

Aerial vehicles might be helpful for tactical operations and I can’t help thinking that an unmanned marine vehicle with an acoustic camera capable of penetrating turbid waters could provide more information about that crack in the big dam…

Bin was a participant in the NSF-JST-NIST workshop at Disaster City at the first of the month and we look forward to working with him and his group.

[This was written by Professor Robin Murphy at Texas A&M University and originally appeared on her  CRASAR research group  blog.]

This follows on the heels of Dr. Dugan’s impressive and heartening House Armed Services Committee testimony, blogged here, and a Computing Research News article by Lazowska and Patterson describing “New Directions at DARPA,” here.

Here’s my favorite paragraph from Dr. Dugan’s HASC testimony:

“Upon arrival at DARPA, we were determined to understand and repair the breach with universities. We discovered the following: Between 2001 and 2008, DARPA funding to US research university performers did decrease in real terms, by about half. But, as importantly, a noble and recent focus in the Agency on solving nearer term problems for the Department had resulted in some additional, perhaps unintended, consequences. The nature of the work changed, from multi-year commitments, to those with annual “go, no-go” decisions governing continued funding, which made it difficult for universities to commit to graduate students. A later stage focus resulted in more work done by universities as subs to prime contractors responsible for integration efforts, and the resulting flow-down of restrictions on the use of foreign nationals, export control, prepublication review, among others.  We assessed that we could address many of the concerns identified.”

Our community was vilified – and our integrity questioned – by the previous Director for asserting precisely these things.  (He famously distributed a chart showing that university funding was not decreasing … however, the chart had the backing spreadsheet attached, which showed that some key institutions, as well as the most recent year, had been omitted from the chart.)

It’s great to see these changes in direction!  Remember that we must respond, by re-engaging.

The name is the same, but the project is totally different, and totally right-headed.  Teams of top researchers are building a diverse suite of tools and technologies that will allow a broad range of networking research experiments to be carried out.  As an example, a set of research universities and research backbone networks are in the process of rolling out Stanford’s OpenFlow switches, which will allow novel low-level protocols to be run alongside TCP/IP.  More than 200 research leaders attended the 7th GENI Engineering Conference, held March 16-17 at Duke University.

The purpose of this post is to bring to your attention a new “Call for White Papers” for a GENI Experimenters Workshop to be held at Princeton University on June 29-30.  This is a great chance to get on board a train that is moving rapidly and in a really interesting direction.

In doing so, OSTP leads with CCC’s “Landmark Contributions by Students in Computer Science“:

“Students have contributed some of the most important advances in information and communications technologies—including data compression, interactive computer graphics, Ethernet, Berkeley Unix, the spreadsheet, public key cryptography, speech recognition, Mosaic, and Google.  Today, with the right kind of support, students can play the role of innovators again — by leading the way in the development of broadband applications. In the same way that Mosaic and Google drove demand for today’s Internet, new applications could drive demand for a gigabit/second Internet and 4G wireless.”

Read the proposed OSTP initiative and send comments to broadband@ostp.gov.

The Assistant Director for CISE leads a directorate comprised of three divisions: Computing and Communication Foundations; Computer and Network Systems; and Information and Intelligent Systems.  The CISE directorate is also a major contributor to NSF’s cyberinfrastructure investments through the Office of Cyberinfrastructure.

The search committee will be headed by Dr. Susan Graham, Pehong Chen Distinguished Professor of Electrical Engineering and Computer Science at the University of California, Berkeley.  The qualifications for the Assistant Director include: outstanding leadership; a deep sense of scholarship; a grasp of the issues facing the computer and information sciences in the areas of education and research; and the ability to serve effectively as a key member of the NSF management team.  The NSF is especially interested in identifying women, members of minority groups, and persons with disabilities for consideration. Recommendations of individuals from any sector – academic, industry, or government – are welcome.

Please send your recommendations by April 30, 2010, including any supporting information that you can provide, to the AD/CISE Search Committee via e-mail (cisesrch@lists.nsf.gov) or at the following address: National Science Foundation, Office of the Director, Suite 1205, 4201 Wilson Boulevard, Arlington, VA 22230.

This announcement, with additional related documents about the search, are available here.

(This announcement is a slightly edited version of a solicitation letter from Dr. Arden L. Bement, Jr., Director of NSF)

The ACM-Infosys Foundation Award, established in August 2007, “recognizes personal contributions by young scientists and system developers to a contemporary innovation that exemplifies the greatest recent achievements in the computing field.”

ACM announcement here.  Wall Street Journal article here.

Congratulations Eric!

ACM announcement here.  Microsoft announcement (a wonderful profile of Chuck) here.  Terrific 6-minute interview on NPR’s All Things Considered here.

Congratulations Chuck, and thanks for being an inspiration to all of us!

To stimulate work in this area, the NRC is offering one or more monetary prizes for excellent contributed papers that address one or more of the questions of interest described in the section entitled “Questions of Interest” in the call for papers linked here.

“While the history of computing-related contributions to shaping our world is a compelling topic, future opportunities in computing—where the field might go and what problems it might tackle—are perhaps even more compelling. Whether it’s creating the future of networking, revolutionizing transportation, delivering personalized education, enabling the smart grid, empowering the developing world, improving health care, or driving advances in all fields of science and engineering—all national priorities—computing has key contributions to make and key roles to play.”

Read the full article here.

ARPA-E is a new office of the Department of Energy focused on extramural breakthrough research, in the DARPA tradition.

Watch Majumdar’s talk here. See white papers on the essential role of computing research here, here, and here.

Wing noted that NSF’s CISE and ENG Directorates fared particularly well in the President’s FY2011 budget request.  She attributed this to two factors:

• These fields drive innovation that creates jobs and increases America’s competitiveness.

• These fields are closely aligned with the Administration’s four science and technology budget priorities:

• Applying science and technology strategies to drive economic recovery, job creation, and economic growth;
• Promoting innovative energy technologies to reduce dependence on energy imports and mitigate the impact of climate change, while creating green jobs and new businesses;
• Applying biomedical science and information technology to help Americans live longer, healthier lives while reducing health care costs; and
• Assuring we have the technologies needed to protect our troops, citizens, and national interests, including those needed to verify arms control and nonproliferation agreements essential to our security.

Read the President’s science and technology budget priorities memorandum here. See the President’s FY2011 NSF budget request here.

• Andrei Broder, Yahoo!
• Irene Greif, IBM
• Bill Gropp, UIUC
• Laura Haas, IBM
• Mike Jordan, UC Berkeley
• Brewster Kahle, Internet Archive
• Tom Mitchell, CMU
• Larry Peterson, Princeton
• Ben Shneiderman, University of Maryland
• Mark Wegman, IBM
• N.R. Narayana Murthy, Infosys (Foreign Associate)

Congratulations to these outstanding colleagues!  The NAE announcement may be viewed here.

The results are in!  “You voted!  We listened!!”  (Even if  “you” is a bot …)  The winner of the popular vote is … Computer Engineer Barbie!

The New York Times reports:  “Barbie has come a long way since 1992, when the blond bombshell of a doll was programmed to say, ‘Math class is tough.’  Barbie, whose various careers have taken her from aerobics instructor to supermodel to business executive, will next be a computer engineer, a career chosen by half a million Barbie fans.”  Read the full article here.

If you know of a student has already made a special contribution in one of these areas, please nominate them!Nominations may REUSE existing materials such as videos, essays, articles, business plans, posters, presentations, photo essays or can be newly created.

• Nominations are due 1 March 2010.

Peter spoke on DARPA and TCTO at the University of Washington on February 2.  The talk is inspiring and informative.  Watch the streaming video here.

“What the country needs most now is not more government stimulus, but more stimulation. We need to get millions of American kids, not just the geniuses, excited about innovation and entrepreneurship again. We need to make 2010 what Obama should have made 2009: the year of innovation, the year of making our pie bigger, the year of ‘Start-Up America.’

“Obama should make the centerpiece of his presidency mobilizing a million new start-up companies that won’t just give us temporary highway jobs, but lasting good jobs that keep America on the cutting edge. The best way to counter the Tea Party movement, which is all about stopping things, is with an Innovation Movement, which is all about starting things. Without inventing more new products and services that make people more productive, healthier or entertained — that we can sell around the world — we’ll never be able to afford the health care our people need, let alone pay off our debts …

“And to reignite his youth movement, he should make sure every American kid knows about two programs that he has already endorsed.  The first is National Lab Day … [which] aims to inspire a wave of future innovators, by pairing veteran scientists and engineers with students in grades K-12 to inspire thousands of hands-on science projects around the country.”

My Japanese hosts at the International Rescue Systems institute are sanguine about the long delays in getting new technologies from the labs and into the hands of the responders, agencies, and the victims themselves. It takes time, they say.  They are patient; it took 5 years to rebuild Kobe with the resources of one of the great nations of the world.

During my visit this week and through out my meetings with industries and agencies over the years since 9-11, I have been repeatedly struck by the brilliance and potential of many innovations. Unmanned vehicles and sensors offer viewpoints that humans and dogs can’t provide. A dog can tell if a survivor is inside a collapse structure, but not whether it is safe for a rescuer to enter or how to best shore it up or remove rubble without causing further injuries. Wireless communications improve daily.

The field of social computing is a truly new vista- and if harnessed could not only help the victims help supply the responders with information but be more able to help themselves. I marvel at the ideas of Gloria Mark at UC Irvine and Leysia Palen at Colorado for crisis informatics. One of the lessons of the Kobe earthquake was that centralized, official response teams were insufficient and in the end, the volunteers from the survivors were what made the difference in rescuing people and putting out the fires.

I have also been struck by the price we pay as a society by not incorporating more computer science into engineering and business. Some of the most magnificently agile robots have been rejected or failed in the field because the designers had provided a poor human-machine interface- topics taught in computer science but generally neglected in other disciplines. Other innovations have fallen short because the designers did not understand the domain- how the responders actually work- and did not understand how to understand a domain- again something that computer science addresses daily in human-centric design methodologies.

And as can be seen from the news reports from Haiti, the  potential contributions of computer science to intelligent, distributed decision making are important too. There is always a tendency to try to make things more centralized, imposed more control and enforced coordination. And the ShadowBowl exercises run by Eric Rasmussen, now at InSTEDD, show that this just doesn’t work. There are too many agencies, NGOs, and emergent groups that may not even know about each other. A few years ago in an outbrief of a major international disaster, I overheard one agency complain bitterly about Doctors Without Borders, which is normally not equated with Satan. As an outsider, it was clear that both agencies had been doing their jobs but had no way of even knowing that the other agency was in the area or opportunistically coordinating activities. The cognitive sciences can help if they’re allowed.

Great progress is being made by viewing these events from what David Woods at Ohio State calls a polycentric viewpoint- that there will always be multiple centers of decision making and the decisions will change in scope and function over time. Rather than try to continue to dynamically create and maintain a top-down structure, embrace the distributed nature of incidents and create architectures that let the groups go about their business while minimizing conflicts, duplication of resources, etc.

I also believe it is also important for scientists to understand context and policy. The US teams sent to Haiti by FEMA can’t use ground robots because they aren’t approved yet. Military UAVs, so popular in Iraq and Afghanistan, must conform to FAA and FCC requirements to be used by civilians. I believe we must begin to educate our students on policy- what that means for funding and adoption and how to positively influence it. A bright star in this regard has been Henrik Christensen’s leadership through the CCC in creating the US Congressional Caucus on Robotics.

I continue to pray for the people of Haiti and the international response community, but I’m slipping in a few prayers for us to change the way we think about technology, computer science, and science education. I am not sanguine, I believe that we’re running out of time.-Prof. Robin R. Murphy, PhD Raytheon Professor of Computer Science & Engineering

• Environmentalist
• Surgeon
• Architect
• News Anchor
• Computer Engineer

Get out the vote! http://www.barbie.com/vote/

• Among the 10 major BLS occupational groups, the “Professional and related” category (which includes computer science occupations) is projected to grow by the largest percentage between now and 2018 — by 16.8%.  (The average growth projected across all occupations is 10.1%.)

• Focusing in on the “Professional and related” occupations, of the 8 occupational clusters that are included, “Computer and mathematical” occupations are projected to grow by the largest percentage between now and 2018 — by 22.2%.  In other words, “Computer and mathematical” occupations are the fastest growing occupational cluster within the fastest growing major occupational group.

• Looking at all science and engineering occupations — “Computer and mathematical,” “Architecture and engineering,” and “Life, physical, and social science” — computer science occupations are projected to be responsible for nearly 60% of all job growth between now and 2018.  The next largest contributor — all fields of Engineering combined — is projected to contribute 13.4% of total growth.  All of the life sciences combined:  5.6%.  All of the physical sciences combined:  3.1%.  In other words, among all occupations in all fields of science and engineering, computer science occupations are projected to account for nearly 60% of all job growth between now and 2018.

Forty years ago, in 1969, Neil Armstrong left footprints on the surface of the moon.  It was an extraordinary accomplishment.

Also in 1969, with much less fanfare and at much less expense, Len Kleinrock’s programmer Charley Kline sent the first message over ARPANET.  (The message was “lo” – the first two letters of “login.”  Then the system crashed.)

With forty years of hindsight, which of these events has had the greater impact?  Unless you’re really big into Tang and Velcro, the answer is clear.  From four computers in 1969, the Internet has grown to more than half a billion computers and more than a billion regular users, and is impacting every aspect of our lives.

“Exponentials R Us.”  That’s the magic of computer science.  It’s what differentiates us from all other fields.  (To the extent that other fields are experiencing exponentials, it’s because of computer science – for example, the sensor technology and computational power that are driving biotech.)   “Exponentials R Us” is the past, the present, and the future of computer science.  If you think you can have greater impact doing something else, you’ve got your head wedged.

With that as context – as the single most important message – here are a few things that have been particularly cool in the past decade …

So, what about the next ten years?  …  Here are a few things to watch …

Read the complete post here.

Deadline:  December 11, 2009

What questions shape our intellectual future? What attracts the best and brightest minds of a new generation? What are the next big computing ideas – the ones that will define the future of computing, galvanize the very best students, and catalyze research investment and public support?

The Computing Community Consortium (CCC) is charged with mobilizing the computing research community to answer these questions by identifying major research opportunities for the field, and by creating venues for community participation in this process. The CCC supports these efforts through advocacy with federal agencies, through visioning activities such as workshops, through arranging plenary talks on key topics at major venues, and through other community building activities.

The CCC is funded by the National Science Foundation under a cooperative agreement with the Computing Research Association. The work of the CCC is carried out by an active and engaged Council, currently chaired by Ed Lazowska with Susan Graham as vice-chair, which reports to the CRA board. The members of the Council are appointed by CRA in consultation with NSF, with staggered 3 year terms. In the aggregate, the Council must reflect the full breadth of the computing research community – research area, institutional character, etc. Details on the role of CCC, as well as the current composition of the Council, may be found at http://www.cra.org/ccc/.

We invite nominations (including self-nominations) for members to serve on the CCC Council for the next three years. Please send suggestions, together with the information below, to Eric Grimson (mailto:welg@csail.mit.edu) by December 11^th. Also serving on the nomination committee are Kathleen Fisher, Susan Graham and Jennifer Widom. This committee’s recommendations will serve as input to CRA and NSF, who are responsible for making the final selection.

1.     Name, affiliation, and email address of the nominee.

2.     Research interests.

3.     Previous significant service to the research community and other relevant experience, with years it occurred (no more than *five* items).

4.     A brief biography or curriculum vitae of the nominee.

5.     A statement from the nominee of less than 1 page, supporting his or her nomination by describing his or her ideas for, and commitment to, advancing the work of the CCC in engaging broader communities, finding wider funding sources, and encouraging new research directions. What the CCC Council needs is not famous people with lots of awards, but people with ideas, judgment, and the willingness to work.

While the technical program plainly illustrates the quality of the conference, what is more difficult to convey to those who did not attend is the positive energy and excitement that permeates the entire event.  Hundreds of students excitedly swarmed the Amazon.com booth to write code, with the hopes of being dubbed a “Ninja Coder.”  Students showcased t-shirts with the slogan “I code like a girl, and I’m proud of it!”  Throughout the halls, colleagues and friends hugged as they reunited.  And who can overlook the not one but two dance parties put on by the conference and its sponsors.  Hundreds of computer scientists on the dance floor, celebrating the fact that they are in a field where they get to do what they love every day.

As its name implies, the Grace Hopper Celebration is not simply a conference, but a celebration of the work that we do as computer scientists, and particularly as women computer scientists.   It’s a wonderful reminder to all of us—men and women, students and faculty, academics and those from industry—that we work in an exciting field at an exciting time.  It is clear from the conference that the women in the field are critical in driving this exciting field forward, both now and in the future.

This report was contributed by Dr. Christine Alvarado, Assistant Professor of Computer Science at Harvey Mudd College.

In the 30+ year history of this award, only one computer scientist has been recognized.  A principal reason is we don’t nominate many people.  Let’s change that!  It’s too early to submit nominations, but it’s not too early to start thinking about who you’d be willing to nominate.

Information on the Waterman Award is on the NSF web here.

What is a “better Internet”? The current Internet has been a remarkable success, providing a platform for innovation that far exceeds its original vision as a research instrument. It is well documented that the Internet has transformed the lives of billions of people in areas as diverse as education, healthcare, entertainment and commerce. Yet many of these successes are threatened by the increasing sophistication of security attacks and the organizations that propagate them. A materially more secure Internet would be “better”. Further, billions of people remain untouched by the advantages of the Internet; Internet World Statistics puts worldwide average Internet penetration at about 22% in mid 2008. An Internet that affordably reaches the other 80% of the world population would be “better”.

Beyond security and accessibility, there are other areas where limitations of the current Internet are significant. The Internet usually works pretty well, but every user has experienced inexplicable periods of degraded performance or outright non-function. The current Internet provides no visibility to end-users and shockingly little visibility to network managers and operators to support understanding, adapting to and fixing reliability problems. Such limitations require lay people spend their leisure time as network systems administrators and companies to spend heavily in network operations. Further, the lack of performance reliability prevents the Internet from advancing to become a truly dependable, critical infrastructure. Indeed, current societal reliance on the Internet for critical functions is disproportionate to our ability to deliver a high degree of dependability. A more predictable Internet would be “better”.

The Internet embeds societal values in ways that are often implicit and not well understood. For example, the Internet is “open”, usually intended to mean that anyone can join the network by implementing the public protocol IP. In principle, users can run any application on the Internet, without limitation imposed by the network protocols. Open networks promote organic growth, but suffer from a lack of mechanisms to vet or bar participation. Issues of trust and individual accountability are confusing. As the well-known cartoon says, “On the Internet, no one knows you’re a dog.” An Internet that contains support for identity would be “better”.

The research community is poised to dramatically advance the agenda of building better networks through advances in both empirical design methodology and systematic design methodology. We have an approach to support large-scale and flexible experimentation based on programmability of devices and federation of multiple test-beds. We have a nascent mathematical framework for understanding architectural features and underlying principles. The time is right to advance and link both methodologies to realize better networks.

– Ellen Zegura

Back in early 2008, they began organizing four workshops, one each in four topical areas of robotics: manufacturing and logistics, healthcare and medical robotics, service robotics and emerging technologies.  More than 100 people attended these workshops, representing a mix of industry and academia.  Preliminary workshop reports were made available to the community, and an online discussion board provided a forum for further input.

A sampling of the four workshops’ findings:

• In manufacturing it is evident that the main applications so far have been large-scale production of entities such as cell phones and cars whereas small-scale production has received limited attention.  It is further evident that processes such as logistics and material handling have significant potential for use of robotics, but so far little attention has been devoted to such applications.  There is a need to consider new methods for easy programming of robots, and further integration of sensory information to enable robust and safe operations.  Less than 5% of all industrial robots today use sensors as part of the primary control system.
• Medical robots are today widely used for prostate surgery and are also gaining momentum for cardiac procedures and hip replacement.  The main motivations are faster recovery, improved quality and a reduced risk of any side effects.  The potential for medical robotics is very significant.  Related to healthcare there is also the use of robots for rehabilitation as it enables a higher degree of customization to individual patients and faster initiation of training.  In addition the engagement with robots is sometimes easier than interaction with humans due to privacy and scheduling considerations.  Wider adoption of healthcare robotics calls for new methods in machine learning, human robot interaction and flexible mechanisms for physical interaction with humans.
• Service robotics has two aspects: professional and domestic.  Professional robotics involves for example agriculture, forestry, mining and harbor automation. The number of people involves with agriculture and related industries is decreasing while the demand is increasing and there is a need to further automate the industry to remain competitive.  For domestic services there is a need to provide cleaning, surveillance, life sign monitoring, remote video, etc to assist people in their busy lives, but also to provide key functionality to enable people to remain in their homes as mobility and mental capabilities are reduced with age.  In service robotics it is characteristic that users have no or very limited training and the systems must be intuitive / easy to use.  In addition there is a need for flexible integration with existing technology (a scalable integration strategy). Finally there is a need for navigation and flexible perception to allow deployment in natural environments (e.g. homes).
• In emerging technologies that are several opportunities as sensing become ubiquitous, more flexible mechanisms are designed and new technologies such as nano become available.  The access to complex computing with a limited footprint allows deployment of AI in new settings.  The use of machine learning and new types of interfaces with a high degree of connectivity opens entirely new opportunities for use of robotics. Not to mentioned new actuation methods.

Robotics in general is characterized by a significant economic potential and has research opportunities across the entire spectrum from basic to applied.  There are clear short-term opportunities in areas such as medicine and manufacturing and at the same time there is a potential to create an entirely new industry for cognitively endowed robots with richer interaction with the world.

The workshop reports are nearly in their final form.  You can watch for them and other updates at http://www.us-robotics.us.

–Andrew McCallum

“Congress is now debating the American Recovery and Reinvestment Act of 2009. Included in this package is over 10 billion dollars for science facilities, research, and instrumentation.

“The reason for this inclusion is simple: today’s research is tomorrow’s infrastructure.

“When our nation faces immediate challenges, the feasible solutions depend upon the ideas, resources, and designs that are “on the shelf,” ready to deploy …

“Increasingly, information technology is the cornerstone of America’s infrastructure. Today’s information technology research is a cornerstone of tomorrow’s infrastructure.”

Read the full editorial here.  A set of white papers describing the role of computing research in meeting the challenges of the 21st century is available here.

http://www.youtube.com/watch?v=_lLDNosedHk

It’s inspirational.

– Ed Lazowska

• The Internet and the World Wide Web as we know them today
• Search technology – Where once we filed, today we search
• Cluster computing
• The transformation of science via computation

In this post, we summarize just a sample of your additions (we have grabbed text from your posted comments, without a lot of editing, so this will be loose – “it’s the thoughts that count”) and invite your further comments – cleaning up these additions, or providing others.  Please let us hear from you!

Secure communication – the foundation of e-commerce

All of e-commerce relies on the results of computing research:  the Internet, the World Wide Web, cluster computing, parallel relational database systems, cryptography and algorithms for secure credit card transactions.  Here, we focus on the latter.  Without secure communication – for example, the ability to conduct a credit card transaction with an online merchant – there would be no e-commerce.  The complex of events (both theoretical advances and deployment of practical, useful software) that allow a user to type a credit card number into a web browser and be reasonably assured of its safety is a game-changer, making secure communication and secure commerce a reality for (potentially) all users of the Internet.  Without these artifacts, we would have no Amazon.com, no eBay, no thriving online pornography industry, …

Mobile computing and communication

Twenty years ago, computing was a desktop experience.  “Portable computers” were the size of a briefcase.  Communication was via 9600 baud telephone modem.  Contrast that to today:  2 pound laptops that fit in a mailing envelope, mobile phones with Web browsers that fit in a shirt pocket, and ubiquitous WiFi and 3G cellular at many millions of bits per second.   Clearly, mobile computing and communication – the untethered lifestyle – is a game-changer.

Expert systems become ubiquitous

Thousands of routine decisions daily are made by computer systems that have specialized knowledge of a problem area. In the past, rule changes at a central office – e.g., the IRS, or the headquarters for a corporation – were incorporated slowly into practice. With expert systems, the people making the decisions have the benefit of codified knowledge bases that reflect current policy and practices.

Research on expert systems began in the 1970′s with support from DARPA, the National Institutes of Heath, and NSF. Expert systems have subsequently become an essential part of the IT toolkit for every major company. Help desks, credit checking and equipment troubleshooting are examples of systems that have been replicated many times over and are routinely saving money for business and public institutions.

Expert systems technology is a game-changer.

Robotics in everyday life

Twenty years ago, robots appeared in artificial intelligence laboratories, automated assembly lines, and science fiction movies.  In recent years, iRobot Corporation has sold roughly 1,000,000 Roomba robotic home vacuum cleaners annually, and multiple robotic automobiles have completed the DARPA Grand Challenge and Urban Challenge, autonomously navigating a 150-mile desert course and a 60-mile urban course.  Robots have entered the mainstream of society, integrating a wide variety of Artificial Intelligence technologies such as computer vision, sensing, and planning.  This is a game-changer, and the best clearly is yet to come.

Digital media

Today, almost no one thinks of photography in any form other than digital.  The means by which we capture, edit, and share digital images are the result of multiple breakthroughs in computer science.

Similarly, digital compact disc audio – a breakthrough when it entered the mainstream only two dozen years ago – is going the way of the dinosaur, replaced by MP3 audio on personal devices such as iPods.

Our video entertainment is in digital form too – whether on a DVD, a personal video device, streaming media, or a video game.

Digital media is revolutionizing entertainment and the entertainment industry – a game-changer.

GPS, mapping, and navigation

GPS – the ability to pinpoint your position nearly anywhere on earth – is a marvel.  But even more amazing are the algorithms that provide navigation – available on the Web, and in $200 self-contained portable devices from Garmin, TomTom, and others.  GPS, mapping, and navigation are game-changers.

Collaborative filtering and recommender systems

Collaborative filtering and recommender systems dramatically altered how we think about computing applications by introducing the idea that the actions and preferences of other people could be a useful resource in computations intended to support someone else’s activities.  This is easily appreciated by a broad audience – anyone who has used Amazon.com’s “people who bought this also bought…” or other social features; a somewhat narrower audience will also appreciate that a major improvement in search engine performance occurred when they started taking into account link structures and then click behaviors.

There’s a clear  tie to computing research, both in work on algorithms for using data from other people, and in interfaces for collecting it and presenting predictions or recommendations.  The idea was first articulated in CACM and in the ACM CSCW and CHI conferences, and there are now thousands of papers about it.

A few additional ideas that were suggested

These need fleshing out or weeding out!  Our comments in [blue brackets] …

• Something related to applications of machine learning – the applications within computing (e.g., NLP, vision, graphics), to other sciences (with big data), to finance (credit card fraud, and dare I say Wall Street) abound [for sure - needs fleshing out]
• Something related to advances in software engineering, and the application of logic to analyzing both hardware and software designs and artifacts [the application of logic might work; we still have a "software crisis," though, and "there (still) is no silver bullet," so need to be careful with claims]
• Something related to scientific computing and large-scale computational science, simulations, etc. [we meant this to be covered by one of our original topics - "the transformation of science via computation"]
• Virtualization [can someone say "1960s"?]
• Network coding [would need to be painted larger]
• Compressed sampling/sensing [would need to be painted larger]
• Quantum computing [premature]
• Elliptic curve crypto [covered crypto under secure communication]
• Molecular computing [come see us in 10 years!]
• Randomized algorithms [would need to be painted larger - colored with applications]
• Theory of distributed computing: impossibility results, Byzantine generals [we meant to feature this under our "cluster computing" topic, which relies integrally on these algorithms; cluster computing is not a hardware breakthrough, it's a distributed algorithms breakthrough!]
• Wearable/ubiquitous/mobile computing [covered under mobile computing and communication, a new topic above]
• Sensor networks [tell me more]
• Human computation (Captchas, the ESP game, etc.) [maybe ...]
• Computational microeconomics: ad placement, automated mechanism design [sounds good - say more!]

Again, we invite your comments!  Let us hear from you!

– Ed Lazowska and Peter Lee

The workshop vastly exceeded my expectations – 8 hours of brainstorming about strategies and best practices, in four areas:

·     “Go Outside Your Box” – what strategies can we adopt to increase collaboration across subfields and with other fields?

·     “The World Needs Us” – how to contribute to the solution of societal “Grand Challenge” problems while simultaneously driving computing research forward.

·     “Breaking the Cycle” – can we change the reward structure to decrease incrementalism, encouraging long-range thinking?

·     “Serving the Community” – how can we further increase the culture of service to the research community and to the nation?

I’m sure others will blog on various aspects, and teams have formed to write up specific strategies and best practices.  But here are a few things that really struck me:

Computer science:  the ever-expanding sphere

A model of how our field evolves can help us make smart decisions.  Think of computer science as an ever-expanding sphere (this analogy is due to Alfred Spector; all graphics are due to Peter Lee).  We transform other fields and we change the world.  We do this not just through the application of computation, but through the introduction of computational thinking.  When we transform these fields, we make new discoveries about our own field that enlarge our “bag of tricks” – our ability to transform other fields.  So we constantly reinvent ourselves by reinventing others.

We’ve transformed circuit design, publishing, photography, communication, mechanical CAD, certain fields of science, …  We’re in the process of transforming biology, transportation, …  And we’re always transforming ourselves.  Computer science truly is an endless frontier.

What this means is that even when working inside the sphere, we’ve got to be looking outward.  And at the edges of the sphere, we’ve got to be embracing others, because that’s how we reinvent ourselves.

Computer science lives in Pasteur’s Quadrant

The vast majority of work in our field is motivated both by concerns of use and by a desire to evolve principles of enduring value.  If anything, we may be too much in Pasteur’s Quadrant – we may place too little value on research without obvious utility, and we may be too reluctant to reject as “not computer science” work that’s focused on applications where it may not be obvious that our own field will be advanced.  (Jim Gray had the stature and courage to pioneer our move into data-intensive eScience – today, the transformations this has stimulated “within the sphere” are obvious.)

Lots of the action is at the interfaces

This is true fractally – it’s true of the interfaces between computer science and other fields (the edges of the sphere), and it’s true of the interfaces between subfields of computer science.

We’ve got to produce students who are comfortable at these interfaces.  It’s increasingly difficult.  Stuart Russell observed that “Bohr drives Pasteur” – we need strength at the core, and the core is ever-expanding.  At the same time, students need to be able to make connections.  I’m concerned we’re making the wrong tradeoffs these days.  Students enter graduate school with records that look like promotion cases a decade ago!  We decrease course requirements to get students engaged in our own research as quickly as possible.  Our colloquia are half-empty because everyone’s too busy beavering away to attend.  These factors decrease breadth and agility within the sphere.  We don’t require minors, which would expose students to other fields – this decreases the ability to work at the edge of the sphere.  As a field, we should tackle these issues head-on.

Visions, incremental progress, and random walks

A research project needs to be hard enough to be interesting, and easy enough to be doable.   There needs to be a vision – a sense of where you and your colleagues are headed over a five-year or ten-year period.  And it needs to be tackled in what Alfred Spector calls “factorizable pieces.”

If there’s a vision, then a “factorizable piece” may appear incremental, but it’s headed somewhere important.  Without a vision, it’s part of a random walk.  It’s important to differentiate these!  A goal of the CCC “visioning workshop” process is to articulate some of these visions for our field.

Bob Sproull pointed us to a wonderful paper by Ivan Sutherland on the conduct of research – “Technology and Courage.”  Read it!

Onward

I’m sure others will blog on various aspects of the workshop.  Look in the mirror – is there a field you’d rather be part of?

– Ed Lazowska

• The advance needs to be “game changing,” in the sense of dramatically altering how we think about computing and its applications.
• The importance of the advance needs to be obvious and easily appreciated by a wide audience.
• There needs to be a clear tie to computing research (or to infrastructure initiatives that build upon research and were sponsored by computing research organizations).
• We’re particularly interested in highlighting the impact of federally-funded university-based research.

We’re focusing on work carried out in the past 20 years or so, in part because of the upcoming 20-year celebrations for the CISE directorate at NSF. Of course, lots of great fundamental research can take more than 20 years before the impact becomes obvious, but even in such cases there is usually continuing influences on more recent research that can be cited here.

To get your juices flowing, here are four game-changers that we definitely think belong on the list. Use these to think about others that belong on the list, or feel free to argue with our choices.

The Internet and the World Wide Web as we know them today

In 1988 — 20 years ago — ARPANET became NSFNET. At the time, there were only about 50,000 hosts spread across only about 150 networks. In 1989, CNRI connected MCImail to the Internet — the first “commercial use.” In 1992, NCSA Mosaic triggered the explosive growth of the World Wide Web. In 1995, full commercialization of the Internet was achieved, with roughly 6,000,000 hosts spread across roughly 50,000 networks. Today, there are more than half a billion Internet hosts, and an estimated 1.5 billion Internet users.

While many of the underlying technologies (digital packet switching, ARPANET, TCP/IP) predate the 20-year window, the transition from the relatively closed ARPANET to the totally open Internet and World Wide Web as we know them today falls squarely within that window. NSF-supported contributions included CSnet, NSFNET, and NCSA Mosaic.

The Internet and the World Wide Web are game-changers.

Where once we filed, today we search

The vast majority of the world’s information is available online today, and we find what we need — whether across the continent or on our own personal computer — by searching, rather than by organizing the information for later retrieval.

Research on the retrieval of unstructured information is based on decades of fundamental research in both computer science theory and AI. But the paradigm shift that is web crawling and indexing and desktop search is much more recent. It traces its roots to university projects such as WebCrawler, MetaCrawler, Lycos, Excite, Inktomi, and the NSF Digital Libraries Initiative research which begat Google.

Search is a game-changer.

Cluster computing

At the risk of offending our many computer architect friends, we’re going to assert that cluster computing is the most significant advance in computer architecture in the past 20 years.

A decade ago, Jeff Bezos was featured in magazine advertisements for the DEC AlphaServer, because that’s what Amazon.com ran on — the biggest shared-memory multiprocessor that could be built. Similarly, the AltaVista search engine was designed to showcase the capabilities of big SMP’s with 64-bit addressing.

Today, this seems laughable. Companies such as Google and Amazon.com replicate and partition applications across clusters of tens of thousands of cheap commodity single-board computers, using a variety of software techniques to achieve reliability, availability, and scalability.

The notion of hardware “bricks” probably can be traced to Inktomi, a byproduct of the Berkeley Networks of Workstations project. The software techniques are drawn from several decades of research on distributed algorithms.

Cluster computing is a game-changer.

The transformation of science via computation

The traditional three legs of the scientific stool are theory, experimentation, and observation. In the past 20 years, computer simulation has joined these as a fundamental approach to science, driven largely by the NSF Supercomputer Centers and PACI programs. Entire branches of physics, chemistry, astronomy, and other fields have been transformed.

Today, a second transformation is underway — a transformation to data-centered eScience, which requires semi-automated discovery in enormous volumes of data using techniques such as data mining and machine learning, much of which is based on years of basic research in statistics, optimization theory, and algorithms.

Computational science is a game-changer.

Some non-inclusions

Quantum computing. There is huge potential here, but the impact hasn’t been felt yet.

Simultaneous multithreading. We claim that this, and many other important advances in computer architecture, are dominated by cluster computing. (Remember, we’re trying to be provocative here! Blame Dave Ditzel, who put this idea into Ed’s head.)

Your part goes here!

What’s your reaction to the four game-changers that we’ve identified? Do you agree that they belong on the list? If not, why not? If so, what do you think were the principal components of each — the key contributing research results?

Even more importantly, give us eight more! What are your nominees for game-changing advances from computing research conducted in the past 20 years?

Give us your thoughts!

– Ed Lazowska and Peter Lee

Interest was strong — more than 125 department chairs and lab directors attended the 90-minute session, more than 3X as many as have stuck around for any previous final session at Snowbird. Ed Lazowska, Susan Graham, Richard Ladner, Randy Bryant, and Chip Elliott presented. All presentation materials are on the web here. A 20-minute Q&A session followed the presentations.

Several highlights for me:

• CCC’s “Data-Intensive Scalable Computing” initiative, led by Randy Bryant and Thomas Kwan, has really taken off:  two new NSF programs, multiple workshops and conferences, significant educational penetration. There is a ton of opportunity here for our field — great computing research challenges, and great chances to partner with other fields that are transitioning from data-poor to data-rich. (There is a “new computational science” here whose breadth and impact will totally dwarf the breadth and impact of first-generation simulation-oriented computational science.)
• The theory community really has its act together — I’m excited at the prospect of the “nuggets” that will emerge from the recent workshop led by Richard Ladner and others.
• GENI is alive and well, although its shape has changed. GENI is no longer envisioned as necessarily being a single huge uber-instrument. Rather, a collection of research instrumentation needs are likely to emerge from this summer’s formulation of a broad Network Science and Engineering research agenda — needs that might, perhaps, be met by several focused instruments.The GENI Project Office is about to announce a number of awards to explore technologies for constructing such instruments; there have been major support commitments by the private sector, complementing those of NSF.

That’s the scoop.  It’s a great time to be engaged in computing research!

– Ed Lazowska

Robotics research and development have already transformed our lives in many ways: they perform nearly all the welding and painting on the cars we drive; they enable telerobotic surgery resulting in more reliable outcomes and faster recovery times; they perform millions of scientific experiments and observations in chemistry, biology and medical labs.  Increasingly robotics is also providing improved control and functionality in people’s daily lives: some new model cars can park themselves or provide advanced distance-keeping cruise control and collision warnings; millions of autonomous vacuum cleaners are in use in homes across the country; educational toys that move and sense are becoming increasingly popular.

With even larger future impact on the way in elder-care, environmental work and professional services, the international competition for leadership in robotics is significant.  Already, Europe, Japan, and other countries have organized strong, coherent, and well-funded robotics research and development initiatives.  The U.S. must also develop strategic and coordinated support for our robotics research community.

In addition to organizing a set of workshops, Henrik Christensen and his colleagues are leading the creation of a National Robotics Leadership Council to provide an ongoing organization for robotics advocacy and leadership.  The two early meetings will coincide with a caucus on robotics being organized by Congress for June 18.

This attention to connecting with governmental and industrial sponsors is exemplary of what the CCC should be enabling.  The physics research community is well known for its effective governmental lobbying; computer science needs to do a better job of building such connections.  While good scientific ideas must of course form the bedrock of our work, in these times, the focus of our argument must be economic—return on investment—a basis on which I think CS can make a very good case.

In my view, no one in the CS research community will see the CCC as a hero for “defining a research agenda”—these things are usually best developed bottom-up, (and besides there already exist many venues for workshops that are research-focused).  The CCC will be a hero if we can help increase funding for CS.  This will involve creative CS researchers coming together with government and industrial leaders, and developing the right scientific and economic arguments to make the case.

I applaud the National Robotics Leadership Council.  I think they are a good example to us all.

Their workshops, topics and dates are:

• Robotics in Manufacturing and Automation (June 17, DC)
  Organizers: K. Goldberg, V. Kumar, J. Trinkle, H. I. Christensen
• Healthcare and Medical Robotics (June 19-20, DC)
  Organizers: A. Okamura, M. Mataric & H. I. Christensen
• Domestic and Professional Service Robotics (August 7-8, San Francisco)
  Organizers: B. Thomasmeyer, O. Brock, H. Christensen
• Emerging Technologies and Trends (August 14-15, Snowbird, UT)
  Organizers: M. Mason, J. Hollerbach, H. I. Christensen

For more information about these efforts and how to participate see http://www.us-robotics.us/.

In its founding documents, the CCC describes its goals as follows:

The challenge for 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.

All great goals. But how do we set about accomplishing them? While it is still early days for the CCC, a number of very interesting proposals for “visioning” have already been generated by the research community, including proposals in robotics, CS theory, “big data” computing, and a wide variety of other areas. These promise to give us all something to think about, debate, work on, and leverage to enlarge the CS research funding pie. We can all hope that this kind of community involvement not only continues, but accelerates.

Brainstorming, discussing and driving “longer range, audacious research challenges” is the job of the entire community, and the CCC is always looking for ways to encourage and facilitate broad community participation.  The CCC will support and help to organize many venues for this: at workshops and conferences, in publications, and on its own web site at http://www.cra.org/ccc.

The purpose of this blog is to try a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

So, this blog is an experiment — being run initially by the CCC Council, but ultimately we would hope that the research community as a whole might somehow take over the most effective online forums. We want to get started, though, and so here we are. To get us off the ground, we’ve assembled a group of researchers to provide the initial set of articles for this blog. Each member of this group blog is being asked to write their own (possibly opinionated) analyses or commentaries on CS visioning concepts, including those funded by the CCC. In addition, there will be reports of interesting events, discoveries, funding news, and even perhaps various scuttlebutt of relevance to the computing research community.

We hope that you will all subscribe! Expect roughly two to three articles per month.  You may post comments, and in fact doing so is very highly encouraged!  (They may even be anonymous if you prefer.)  This will be at least one online mechanism for community debate and discussion. If this works well, it is conceivable that we could muster up the courage to try something more in the vein of collaboration-encouraging social networking.

Welcome!

– Peter Lee and Andrew McCallum