By Suzanne L. Weekes
The July 2020 installment of Unwrapped, SIAM’s monthly e-newsletter, included a heading that read “SIAM Establishes Task Force on Future Research Directions for NSF in the Era of COVID-19.” This task force was an ad hoc working group of the SIAM Committee on Science Policy (CSP) that was informed by conversations from the spring CSP meeting with federal agency officials, which took place virtually in April 2020. Recognizing that COVID-19 would dramatically impact the National Science Foundation’s (NSF) agenda and the broader federal research enterprise, the CSP charged the task force with drafting a report to help inform the NSF’s response to present needs associated with the pandemic and lay the groundwork for a more robust disaster response regime and future economic security and prosperity. The full task force report is available online.
Anne Gelb (Dartmouth College), SIAM’s Vice President for Science Policy, and then-executive director James Crowley asked me to chair the task force effort. Working with such wonderfully committed and informed SIAM members was a highlight of the summer of 2020. We met weekly in July, bringing people together over a nine-hour time difference — which meant that breakfast, lunch, and cocktails were occasionally consumed during the same meeting!
I would like to thank Marsha Berger (New York University), Amr El-Bakry (ExxonMobil), Tom Grandine (Boeing), Jan Hesthaven (École Polytechnique Fédérale de Lausanne), Peter March (Rutgers University), Madhav Marethe (University of Virginia), Lois Curfman McInnes (Argonne National Laboratory), Rosemary Renaut (Arizona State University), Fadil Santosa (Johns Hopkins University), and Padmanabhan Seshaiyer (George Mason University), in addition to Anne Gelb and James Crowley, for sharing their personal experiences, professional expertise, and keen vision. We all received excellent support for our work from Ben Kallen, Miriam Quintal, and Eliana Perlmutter of Lewis-Burke Associates LLC. Lewis-Burke, which has represented SIAM in Washington, D.C. since 2001, helps the CSP and the SIAM executive director connect with federal agency officials and advocate for research funding and sound research policy in Congress.
The task force also solicited and incorporated input from SIAM membership. The aforementioned notice in July’s Unwrapped directed readers to a survey that requested input in the following categories: Research and Related Activities Specific to COVID-19 Response and Recovery, Near-term Response to COVID-19 Impacts on the Larger Research Enterprise, “Shovel Ready” Research Infrastructure, and Long-term Economic Stimulus and Recovery. The survey responses are available online. Thank you to all readers who shared their thoughts with us!
Several themes emerged from the rigorous discussions in the task force as well as the survey responses. The following paragraphs detail these themes.
Mathematics of Disaster Planning, Response, Recovery, and Resilience
Research in applied mathematics, modeling, and computational science should continue to address the challenges associated with the ongoing pandemic through contributions to forecasting, diagnostics, treatments, vaccines, and studies of societal impacts. However, it is also critical to encourage and support research and modeling efforts that can prepare us to better handle future outbreaks and catastrophes. Mathematics, computational science, and data science will be vital to laying the foundation for a more robust disaster planning and response regime, particularly by strengthening supply chain resilience and optimization, improving decision-making amid uncertainty, and understanding group dynamics in crises. The Working Group on Predictive Modeling and Uncertainty Quantification, which is an open working group of the NSF Advisory Committee on Cyberinfrastructure, provided a document that further demonstrated the critical need to support decision-making with uncertainty quantification and predictive modeling, especially—but not exclusively—during the current pandemic.
SIAM’s task force report highlighted additional topics as general areas of emphasis, including network science and network analysis; secure and protected real-time data integration and analytics for accurate forecasting; predictive and informed modeling of disease spread, control, and mitigation; and mathematical foundations of artificial intelligence and machine learning. Because it is important that our members are aware of these critical topics, let us know if you are interested in organizing or presenting in a relevant area. Please contact Richard Moore, SIAM’s Director of Programs and Services, and/or me with your ideas. We can be reached at [email protected] and [email protected].
Partnerships
Many areas of disaster response and mitigation suffer from a gap in the pipeline between research and operations. Basic science and research and operational readiness often have quite separate communities and stakeholders, and cross-sectoral and interagency partnerships can help bridge that divide. We hope for more active engagement with the NSF’s Directorate for Social and Behavioral Sciences, which sits at the center of many decision-making and behavioral questions, and where modeling tools and understanding are underdeveloped relative to other fields.
The NSF should look to develop more partnerships that are relevant to pandemics and build resilience against future disasters. For example, the task force report recommends connecting the mathematical and computational science communities to disciplines or agencies that currently lack strong ties to our population, such as those within the Department of Health and Human Services (aside from the National Institutes of Health).
Task force members also discussed the unique need to translate foundational or applied mathematics research, and encouraged the NSF to consider incentives in partnerships between industry and universities. These incentives could motivate industry partners to make corresponding investments in their own development enterprises to ensure that university research is meeting customer demands.
Workforce Development
Task force members and survey responders expressed universal concern about workforce development and COVID-19’s negative ramifications for students and early-career researchers. The group urged that those at critical transition points in their careers, underrepresented and underserved groups hit hard by the pandemic, and primary caretakers who face especially challenging dynamics all receive special focus. The report goes into more detail about this topic and contains several ideas that SIAM members could help move forward. I encourage members who are interested in developing relevant grant proposals or programs that meet these needs to reach out to Richard Moore and/or me.
Infrastructure and Collaboration Tools
Most SIAM members are now nearly a year into the paradigm of remote work, though of course some of you were working remotely even before the pandemic. Regardless, we now have some sense of the promises and limitations of this mode of operation. We must consider the future of research in the applied mathematics, modeling, and computational science communities, as well as the specific infrastructure and tools that are required to enable that vision. The report identifies the need to build a cyber infrastructure that can catalogue, store, access, parse, manage, and process data. Supporting digital management tools is also necessary.
SIAM is committed to raising the profile of applied mathematics, computational science, and modeling within the federal research enterprise, and ensuring the application of high-quality research results to solve real-world problems through industry, government, and other avenues to ultimately benefit society. The task force report was delivered to key personnel in the NSF’s Directorate for Education and Human Resources; Directorate for Computer and Information Science and Engineering; Directorate for Social, Behavioral, and Economic Sciences; and the Division of Mathematical Sciences.
 |
Suzanne L. Weekes is the executive director of SIAM. |