Remarks

Good morning! Thank you, Kei, for that warm welcome and a special thank you to Rush Holt for the invitation to participate in this Forum once again. The National Science Foundation has a unique stake in American innovation and competitiveness, and I'm glad to offer its perspective to this important conversation.

NSF plays a distinctive role in the innovation ecosystem by supporting high-risk, long-term, curiosity-driven research – making investments that ultimately drive our economy and help secure America's long-term competitiveness. I'm heartened that these priorities continue to have the support of the Administration and Congress -- and that through the new models for innovation I will share with you today -- NSF is building on that confidence and support. We continue to fulfill our time-honored mandate to further the progress of science.

To keep the U.S. on the cutting-edge of research, technology, and innovation, NSF developed bold ideas for the future, which we call our "10 Big Ideas for Future Investment." Six of these are Big Research Ideas meant to define a set of cutting-edge research agendas that are uniquely suited to NSF's capabilities. These initiatives are aimed at catalyzing new breakthroughs, taking advantage of decades of technological revolutions and new discoveries. They focus on areas ripe for breakthrough, building on a foundation made possible by early investments in fundamental research.

Four of the Big Ideas would implement new processes that could enable more and better research, by embracing new practioners and approaches. One important approach is convergence, which is the process of bringing together people from a variety of disciplines around a focused problem. All of our Big Research Ideas require the convergence of disciplines to successfully take root.

To initiate its bold research agenda, NSF established a new Stewardship Model. The decisions about how agency funds are spent are coordinated by a cross-directorate team, and a single directorate -- "the steward" -- manages each Big Research Idea.

At NSF, we fund researchers in fundamental science, and we also help them on to translate their work into new products and services. We're proud to have a long history of innovation initiatives that link basic research with industry and application, and I'd like to highlight a few of those efforts.

Our Grant Opportunities for Academic Liaison with Industry (GOALI) program sets the stage for university-industry collaboration by enabling academics to conduct research in an industrial setting, or an industry scientist or engineer to bring commercial perspectives to a university lab. Similarly, our Partnerships for Innovation (PFI) program leverages public-private partnerships between academia and industry to accelerate the transition of technologies from lab bench to market. Providing focused entrepreneurial training, the I-Corps program brings teams of graduate and undergraduate students together with faculty and experienced business mentors. And finally, NSF's Small Business Innovation Research program provides seed investment to small technology businesses to help bring innovative technology to the market.

In addition to these initiatives, we also have a large network of science and engineering centers, laboratories, and other large facilities. Our Engineering Research Centers, or ERCs, integrate engineering research and education with technological innovation. In response to last year's NAE report on a new Vision for Center-Based Engineering Research, we have issued a solicitation for planning grants to strengthen the team-building process. We expect to issue a new solicitation for Generation-4 ERCs later this year.

NSF also supports more than 75 Industry University Cooperative Research Centers (IUCRCs), which have an average of 10 partners. The IUCRCs leverage every $1 of NSF funds with $7 of industry and other government agency funds to support basic, use-inspired research on a diverse range of topics. As you can see, these resources are spread throughout the entire country.

Since unveiling the 10 Big Ideas in 2016, we've worked diligently to push our bold research agenda forward. As you can see from the yellow arrows in this image, we’ve provided numerous calls even in the current fiscal year for innovative new proposals involving the Big Ideas, and I’d like to offer a few highlights.

Undoubtedly, more surprises are in store for us as we settle into this new era.

One is the investment we made in quantum research. EPiQC (pronounced epic) is a new $10 million collaborative project that unites experts in algorithms, software, hardware, and education to develop more efficient quantum algorithms to run on quantum machines. Overall, EPiQC will increase the efficiency of practical quantum computations by 100 to 1000 times, effectively bringing quantum computing out of the laboratory and into practical use much sooner than if we were to pursue these advances independently.

It is important to note that investing in quantum research is not new for NSF; we are simply making a larger, deeper commitment to this important area of research to take it to the next level. Our FY19 request is for 30 Million new dollars in this area. Many of our key country partners around the world are also making significant investments in quantum centers and research. The European Union intends to invest $1.2 billion in quantum studies. Canada is investing $170M in three university research centers. And Japan has pledged $125 million for quantum basic research, while China intends a $100 million quantum investment. We're glad that NSF has funded awards collaborating with all these countries in quantum research.

We also see enthusiasm from both the Administration and Congress for the acceleration of U.S. quantum research efforts. For example, both houses of Congress are working on legislation to support the coordination of U.S. government quantum R&D. The White House Office of Science and Technology Policy recently hosted the "Artificial Intelligence for American Industry" summit, which I was delighted to take part in. The summit offered an opportunity to discuss the promise of AI and the policies we will need to realize that promise to maintain U.S. leadership. I look forward to serving as co-chair of the National Science and Technology Council Select Committee on Artificial Intelligence and to build with my inter-agency colleagues on these important efforts.

Within a call for proposals for convergence research, NSF received hundreds of proposals from researchers across the country. Their proposals responded to broad societal challenges, such as human health, the environment, energy, food production and the economy. And their research includes new approaches to bioinspired design, innovative sensing strategies, engineered solutions to developing adaptive and self-evolving materials, and next generation intelligent machines. Out of the 247 prospectuses we received, 14 PIs were invited to submit full proposals for funding. We expect to fund most of these innovative projects this fiscal year.

While turning the Big Ideas into practice through programs like these, it became clear to us that some areas were ripe for accelerating because they are on a faster track to realizing innovative deliverables. To facilitate this growth, we developed a new organizational structure focused around two of our Big Research Ideas – the Future of Work at the Human Technology Frontier and Harnessing the Data Revolution. We call this new entity a Convergence Accelerator.

A Convergence Accelerator leverages external partnerships to accelerate convergent research in an area of national or scientific importance. What's new and exciting about this venture is that we are applying an accelerator model used in the private world to accelerate start-ups to basic research that is more application-driven. We believe this innovative approach can advance ideas from concepts to results quickly.

The Accelerators feature characteristics that set the stage for outcomes in both research and innovation. And because they are continually fed by basic research and discovery, they will be on the cutting-edge of science. NSF will provide the seed investments; we already have industry partners who are engaged in these two efforts.

Unlike the foundational research NSF usually invests in, the Accelerators strive toward an intentional outcome through a range of approaches that address a common challenge. The Accelerator model does this by allowing for both a top-down, strategic direction, and a bottom-up creative approach.

By applying this model to our mandate, our goal is to accelerate the process of convergent research, while achieving clear deliverables. We will direct our accelerators toward outcomes that don't fall within a niche market area, as private startups or incubators and accelerators traditionally do. Our cohorts of teams will bring a range of diverse skills to bear on broad national goals that require convergent approaches. The intention is to advance convergent research farther and faster, and this is a unique and creative way to do so.

This diagram shows the phases of a Convergence Accelerator. The three-stage process begins with team seeding, where we will build cohorts of a dozen or more multidisciplinary teams representing a variety of sectors. In the team formation phase, groups will receive considerable training to deepen their understanding of convergence, team dynamics and ideation – all the factors that go into forging solutions to a challenging goal.

Following this phase, teams will deliver a pitch. Based on the quality of that pitch and on the evaluation of the 6-month incubation period, some of the groups will receive grants of one to two million dollars to carry out their research.

In the final stage, the cohort structure will remain along with a semiannual review. At the conclusion, a prize will be awarded to the best outcome overall.

The Convergence Accelerators model builds on best practices we've been developing at NSF over the last several years. Our I-Corps network model consists of teams coming together in an intensive educational environment. The collective impact model of NSF INCLUDES involves multiple teams working to address a common challenge. We also have considerable experience in forming Ideas Labs and developing teams. And, it was through our recent industry-inspired workshop in quantum that we saw firsthand the community's interest in NSF sponsoring more workshops, particularly on the first two Convergence Accelerators.

What IS new to the Accelerators model is the inclusion of a 15-minute pitch rather than a 15-page research proposal and the competition for monetary prizes. While new to NSF, these strategies have been used by others with great success.

NSF will start with "tracks" that define focused areas of research within the Accelerators. Those tracks will have specific goals in terms of outcomes and deliverables. We'll begin workshops this summer to form teams and tracks that are recommended by the research community.

As I mentioned previously, Harnessing the Data Revolution is one of the Big Ideas we've chosen to accelerate. One example of an Accelerator track within this area is an advanced science data infrastructure that is interoperable and has open standards that enable the use of heterogenous data across many disciplines.

Another example is an open knowledge network. This is a higher-level, open semantic information infrastructure to help in the discovery of new knowledge from various sources. Through these exemplars, we see some of the characteristics that define the accelerators: intentionality, clear outcomes, milestones, deliverables, and agility.

Within the Future of Work at the Human Technology Frontier, we have three examples of Accelerator tracks: smarter manufacturing environments, smarter classrooms, and smarter cybersecurity at scale. We envision building on our basic research in this Big Idea to develop smarter, adaptive collaborations between humans and machines using artificial intelligence. We'll also build on our knowledge of work conducted in classrooms by teachers and students. Lastly, cybersecurity at scale is an example of a track that identifies and mitigates vulnerabilities using artificial intelligence. Again, these examples all build on important foundational research to accelerate the creation of new and smart workplace environments.

One very exciting aspect of the Accelerators is the model they provide for partnerships. At the core of this initiative is the belief that there is no bright line between basic and applied research. The two feed on and reinforce each other to produce better outcomes.

To achieve the best results, we must bring academics who have a deep understanding of fundamental research together with people from industry, foundations, and elsewhere who have a deep understanding of the applications and associated challenges. This allows those in the application arena to comprehend the opportunities enabled by fundamental research. It also empowers those doing fundamental research to better align their studies to market needs. The result is an acceleration of research for societal impact.

Partnerships are central to achieving these goals, and we're encouraged that the Accelerators provide both an opportunity and a model to forging these important alliances. International partnerships will also be incorporated into these efforts so that we can capitalize on innovative ideas from our colleagues around the globe and leverage each other's interests.

When striving to achieve real impact, it is not enough to have a Big Idea; we must also implement it well. I like this saying. Through programs like I-Corps, INCLUDES and the Convergence Accelerators, NSF is exploring new ways to approach complex challenges that call on the collective wisdom of new coalitions. We're excited that these efforts also offer an opportunity to observe what works best and to apply those lessons to improving our implementation.

For example, the Convergence Accelerators borrow ideas from the INCLUDES program like collective impact, theory of change and learning agendas -- all well-tested implementation models in the social sciences. As we uncover what lessons the Accelerators offer, we can apply those insights to the INCLUDES program and vice-versa. The result is a process that enhances efficiency and outcomes.

NSF is an ideal testbed for new models of implementation as we are a home to so many exciting pilot programs. This is yet another in a long line of cutting-edge approaches we are proud to pioneer.

As we look to the future, we must envision questions that will build on the progress we forge today. Two years ago, NSF staff generated the original 10 Big ideas to raise these transformative research questions. This year, we are reaching out to the scientific community, the public, industry, and other stakeholders to conceive the next set of Big Ideas collaboratively. We are doing this through a project called the NSF 2026 Idea Machine.

This initiative is a prize competition that invites participants to submit original, transformative research challenges that they believe should drive our long-term research agenda. We call it the NSF 2026 Idea Machine because the year 2026 is our nation's 250th birthday, and we hope to see the impact of the research agendas we receive through this process, while celebrating that milestone. We're very excited to launch the Idea Machine this August. Through this effort and your input, we intend to create a bold new research agenda for NSF, or Big Ideas 2.0! Let's advance these goals together and implement powerful new models for convergent science. Thank you!