Grants Database

The Foundation awards approximately 200 grants per year (excluding the Sloan Research Fellowships), totaling roughly $80 million dollars in annual commitments in support of research and education in science, technology, engineering, mathematics, and economics. This database contains grants for currently operating programs going back to 2008. For grants from prior years and for now-completed programs, see the annual reports section of this website.

Grants Database

Grantee
Amount
City
Year
  • grantee: Information Technology and Innovation Foundation
    amount: $299,400
    city: Washington, DC
    year: 2021

    To conduct research and training to accelerate low-carbon energy innovation by examining sector-specific industrial decarbonization opportunities and organizing a week-long energy innovation policy training program for early career scholars

    • Program Research
    • Sub-program Energy and Environment
    • Investigator David Hart

    The Clean Energy Program at the Information Technology and Innovation Foundation (ITIF) is one of the leading research efforts examining the energy innovation ecosystem in the United States. This grant, led by energy policy scholar David Hart, funds two projects at ITIF—one training, one research. The training project involves organizing a week-long energy innovation policy “boot camp” in 2022 in Washington, D.C. that will involve a cohort of approximately 20 early-career social scientists.  Participating researchers will be introduced to the practicalities of how energy policy is made and will encourage them to highlight the potential connections between research and decision-making in their own work. The second project involves advancing a collaborative research effort that ITIF is undertaking with scholars at the Boston University Institute for Sustainable Energy (BU-ISE) and the BU-based Fraunhofer USA Center for Manufacturing Innovation (CMI) to examine the decarbonization potential of two industrial subsectors.  Researchers will conduct technical, economic, and policy analysis for each chosen subsector, and they will collect data and conduct interviews with industry and regulatory stakeholders that explore relevant energy innovation policy issues, such as financial incentive structures, global competitiveness, and innovation diffusion patterns. The research is expected to result in at least two reports and academic papers, and it will form the basis of a number of policy briefs that the team will provide to industry and governmental stakeholders.

    To conduct research and training to accelerate low-carbon energy innovation by examining sector-specific industrial decarbonization opportunities and organizing a week-long energy innovation policy training program for early career scholars

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  • grantee: Yale University
    amount: $599,903
    city: New Haven, CT
    year: 2021

    To generate novel research and advance a multi-disciplinary research network that increases understanding of the energy and environmental impacts of the digital economy

    • Program Research
    • Sub-program Energy and Environment
    • Investigator Reid Lifset

    Digital technology developments—including new technologies such as blockchain and the Internet of Things, and behavioral shifts like the rise in digital platform use—can have profound implications for energy and the environment. In 2018, the Foundation supported an emerging effort to study these impacts, and this grant supports the continuation and expansion of this network. Led by Reid Lifset at Yale University, Jordan Diamond at the University of California, Berkeley, and Kasantha Moodley and Dave Rejeski at the Environmental Law Institute, this research network is now known as the Network for Digital Economy and Environment (nDEE). Having already explored the direct effects of digital technologies on energy and the environment, they will now conduct research projects to explore the indirect effects of these digital technologies on energy systems. Three specific research projects will be supported at the outset, with a process designed to further source additional research ideas. The first project will study how the rise of short-term rental services like Airbnb is impacting carbon emissions. The direct effects on emissions through, say, increasing tourism, are well documented, but there are also indirect effects to consider, such as increased travel from Airbnb locations that may be located at the outskirt of cities, thereby increasing overall emissions. The second project will look at the energy implications of product returns. Many product life-cycle analysis calculations stop short of assessing what happens when a product is returned to the seller, and this analysis does not continue to follow a returned product’s continuing environmental impact beyond that point. The third project will seek to design improved personal environmental footprint calculators that integrate robust privacy preserving features. While exploring indirect effects is more challenging than exploring direct effects, completing this work will improve our understanding of how the digital economy contributes to global carbon emissions and what steps we might take toward reducing its impact.

    To generate novel research and advance a multi-disciplinary research network that increases understanding of the energy and environmental impacts of the digital economy

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  • grantee: Resources for the Future, Inc.
    amount: $299,978
    city: Washington, DC
    year: 2021

    To organize a two-day Sloan energy and environment conference, Energy Insights 2022, that highlights the connection between energy research and decision-making

    • Program Research
    • Sub-program Energy and Environment
    • Investigator Kristin Hayes

    Today’s energy, environmental, and natural resource challenges require rigorous and independent research and analysis to inform the design of effective policies. This grant supports Resources for the Future (RFF) in co-organizing Energy Insights 2022, a conference that will emphasize the connection between energy research and policy decision-making, in partnership with the Sloan Foundation’s Energy and Environment program. Following a successful collaboration in organizing the Energy Research Insights for Decisionmaking conference in 2018, this event will feature a range of Sloan-funded energy-related research exploring key issue areas including new technologies, transportation, energy infrastructure resiliency, and distributional equity and environmental justice. By drawing on Sloan’s grantee network and RFF’s connections to policy audiences, the private sector, and the wider research community, Energy Insights 2022 aims to build and strengthen networking opportunities among energy and environment researchers and connect their research to decision-makers.

    To organize a two-day Sloan energy and environment conference, Energy Insights 2022, that highlights the connection between energy research and decision-making

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  • grantee: New York University
    amount: $700,000
    city: New York, NY
    year: 2021

    To establish a Center for Decarbonizing Chemical Manufacturing Using Sustainable Electrification (DC-MUSE) and help diversify the next generation of scholars involved in industrial decarbonization

    • Program Research
    • Sub-program Energy and Environment
    • Investigator Andre Taylor

    Though industrial processes present many opportunities for decarbonization, realizing these opportunities has historically been challenging. Many sectors—including manufacturing, construction, and chemicals production—have, until recently, simply lacked low-carbon alternatives to current practices. Scholarly work is made more difficult by the lack of interdisciplinary knowledge and connections to networks needed to understand the complex interplay of technology, market structure, supply chains, and industrial organization in any sector. Andre Taylor at New York University is creating a new multidisciplinary, multi-institutional research effort addressing an important aspect of industrial decarbonization: chemical production. Working with Elizabeth Biddinger at the City College of New York, Taylor will establish a Center for Decarbonizing Chemical Manufacturing Using Sustainable Electrification (called DC-MUSE) and has assembled a team of scholars spanning chemical engineering, materials science, modeling, computation, and economic analysis across seven universities. The initial research focus will be decarbonizing ethylene manufacturing, which currently requires burning large amounts of fossil fuels to achieve the high input heat necessary for the chemical reactions that produce ethylene. Ethylene is an important initial target because it is a key ingredient in manufacturing, including in plastics, textiles, and other synthetic materials. The team will explore two alternative processes for generating ethylene that do not require high input heat (and, therefore, burning fossil fuels), then use this information to understand how low-carbon chemical plants might integrate with the grid. This grant will support a manager role for the center who will help coordinate activities among the network and build connections with stakeholders in government and industry.

    To establish a Center for Decarbonizing Chemical Manufacturing Using Sustainable Electrification (DC-MUSE) and help diversify the next generation of scholars involved in industrial decarbonization

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  • grantee: National Bureau of Economic Research, Inc.
    amount: $599,844
    city: Cambridge, MA
    year: 2021

    To continue and expand the Environmental and Energy Policy and the Economy (EEPE) initiative that connects energy and environmental economics research with decision-makers

    • Program Research
    • Sub-program Energy and Environment
    • Investigator Matthew Kotchen

    In 2018, the Foundation supported the launch of the National Bureau of Economic Research’s Environmental and Energy Policy and the Economy (EEPE) initiative. This initiative aims to encourage energy economists to produce policy-relevant research that is more directed at decision-makers than traditional scholarly work in the field. EEPE is led by Matt Kotchen at Yale University, along with steering community members Tatyana Deryugina at the University of Illinois, Urbana Champaign, and Jim Stock at Harvard University. Having been successful in its first few years, the EEPE initiative has been renewed for three years and is expanding to include a postdoctoral fellowship. Research will be presented at an annual conference and published in a volume by the University of Chicago Press. Many of the intended topics of study have an equity dimension, while future topics will include a number with an explicit focus on environmental justice. The grant will also provide funding for an early-career scholar to conduct policy-relevant research, helping to solidify the link between EEPE and policy decision-makers. The scholar will receive mentoring from staff at the Environmental Protection Agency (EPA)’s National Center for Environmental Economics, an office that performs economic analysis to inform EPA decision-making.

    To continue and expand the Environmental and Energy Policy and the Economy (EEPE) initiative that connects energy and environmental economics research with decision-makers

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  • grantee: Johns Hopkins University
    amount: $1,500,000
    city: Baltimore, MD
    year: 2021

    To understand the basic properties of biomolecular condensates based on DNA/RNA and to control condensate properties, interactions, and dynamic responses using nucleic acid circuits

    • Program Research
    • Investigator Rebecca Schulman

    Compartments, i.e., discrete spatial regions, are important to life. Cells use them to store molecules for later use and to promote biochemistry by keeping molecules close to one another. Life typically compartmentalizes via walls built from lipid membranes, but biologists have discovered that life also employs a membrane-free approach to compartmentalization. Rather than relying on a wall to demarcate what's inside vs outside of a compartment, life can instead employ phase-transitions, changes in the state of matter (e.g., liquid or solid), to segregate molecules. Envision a gel-like region of closely interacting chemicals within a large liquid-like region of a cell. These phase-change compartments are called biomolecular condensates. They are ubiquitous in living systems and important to cellular function. Condensates have been identified that sequester damaged proteins and orchestrate chromosome separation during cell division, and they've also been implicated in human diseases such as Alzheimer’s. This grant funds work by a team led by Rebecca Shulman at Johns Hopkins University who are attempting to understand and ultimately control condensates as a step towards an improved understanding of compartmentalization that could shed light on the matter-to-life transition. Condensates appear well-positioned for this purpose. On the one hand they share many core functions with cells. Condensates naturally form, grow, dissolve, fuse, and divide. On the other, they are vastly simpler, biomechanically, than cells themselves, allowing researchers to investigate these core activities without the complicating internal structure present in natural cells. The work will focus on nucleic acid-based condensates, condensates where the nucleic acid polymers DNA and RNA are the functional elements that condense or otherwise control the phase transition between a condensate and its exterior. The team's approach is to design, build, and characterize nucleic acid condensates. They'll design synthetic DNA templates that produce RNA molecules with the capacity for spontaneous phase separation, testing hypotheses about how aspects of polymer design influence the condensation process. They'll use optical microscopes and other tools to achieve high-throughput characterization that leads to phase diagrams that summarize condensate properties under varying conditions (temperature, different condensing macromolecules, various solution-phase buffer-molecules). They'll also develop molecular signals that cause distinct condensates to mix or demix with one another, or which cause one type of condensate to expel molecules that signal another condensate to perform some function. These studies will provide insights into how condensates can be used to transport "cargo," chemicals that are not essential to the condensation itself but are instead stored or transported by the condensate. If successful, the project could form the foundation of a new discipline of condensate engineering, one that could open new routes to chemical synthesis, advance our understanding of natural cells, lead to new types of intracellular organelles, and provide insights into how matter transitions to life.

    To understand the basic properties of biomolecular condensates based on DNA/RNA and to control condensate properties, interactions, and dynamic responses using nucleic acid circuits

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  • grantee: Massachusetts Institute of Technology
    amount: $1,500,000
    city: Cambridge, MA
    year: 2021

    To explore how nonequilibrium dynamics can structure biological systems across scales from molecules to ecosystems

    • Program Research
    • Investigator Jeff Gore

    Nonequilibrium dynamics is a thriving sub-field within physics that seeks to identify the principles underlying complex spatiotemporal patterns that arise in far from equilibrium systems. Living biological organisms are one important subclass of systems far from equilibrium, yet, due to their complexity and variety, they have remained relatively understudied by theorists and experimentalists alike. As such, significant questions exists both about the extent to which methods of nonequilibrium dynamics can be used to identify laws governing pattern formation and regularities in biological organisms. Funds from this grant support Jeff Gore, Nikita Fakri, and Jцrn Dunkel of MIT in a series of projects that will begin to examine whether and how nonequilibrium dynamics might be used as an organizing framework for understanding how ordered biological phenomena arise and evolve across a variety of scales. Topics to be explored by the team include the role of topology and topological defects in triggering order-enhancing processes in starfish cells; the assembly of ordered structures of colloidal molecules by motile bacteria; and how spatial distribution affects the evolution and ecology of microbe populations. In addition to knowledge gained, the project will involve the development and deployment of new imaging and theoretical analysis tools, expanding the available methods for the thermodynamic study of biological systems.

    To explore how nonequilibrium dynamics can structure biological systems across scales from molecules to ecosystems

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  • grantee: University of Maryland, College Park
    amount: $2,201,539
    city: College Park, MD
    year: 2021

    To produce, test, and scale infrastructure for re-engineering official economic statistics using administrative data from businesses

    • Program Research
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator John Haltiwanger

    Perhaps the most important economic statistic calculated by the government is the Consumer Price Index (CPI). The CPI is used as a guide for fiscal and monetary decision-making, as a deflator to compare times series data in constant dollars, and as an inflation-measure to adjust the purchasing power of federal benefits like Social Security. The basic methodology for calculating the CPI, however, has hardly changed since the statistic was first introduced over a century ago. First, using a series of voluntary surveys of businesses and consumers, the Bureau of Labor Statistics attempts to measure average monthly prices in 38 geographical areas for 211 broad consumption categories like men’s shirts. Second, the BLS estimates the proportion that each of these individual categories represents of a typical household’s spending on all 211 categories. The goal is to calculate how much a typical basket of goods and services would cost today, then compare that to the cost of the same basket at the end of some fixed period. Although this may sound straightforward, worrisome and worsening challenges arise from this methodology. First, the time required to collect responses to these surveys and aggregate data means that the CPI is not calculated for months after data is collected. Second, falling response rates to polls and surveys of all kinds means that the CPI calculation is increasingly reliant on an ever-smaller set of data, with consequent worries about accuracy. Third, the metadata collected by surveys about goods and services sold is often insufficient to gauge how much the price increase in, say, a mobile phone, reflects improvements in the phone’s quality or feature-set. Funds from this grant support a project called RESET, Re-Engineering Statistics Using Economic Transactions, led by economist John Haltiwanger (University of Maryland College Park), Matthew Shapiro (University of Michigan) and Ron Jarmin (U.S. Census Bureau). The RESET team has forged data partnerships with major online retailers and market data analysis firms to allow them access to real-time, highly granular information about the prices and features of retail products for sale online. The team proposes to use advanced machine learning techniques to solve the problems with current data collection methods. The RESET partnerships promise to be able to calculate the CPI more quickly, using more comprehensive data, and in a way that promises to give both regulators and researchers more ability to calculate how much of a price variation is due to systemic inflation and how much actually reflects changes in product quality.

    To produce, test, and scale infrastructure for re-engineering official economic statistics using administrative data from businesses

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  • grantee: Cornell University
    amount: $1,444,204
    city: Ithaca, NY
    year: 2021

    To support the growth of a public and sustainable patent data infrastructure and research collaborative that enables novel innovation research

    • Program Research
    • Initiative Empirical Economic Research Enablers (EERE)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Matt Marx

    Datasets about patents are among the most important tools for studying the economics of science and technology. Patent records do not tell the whole story, of course, but they do provide critical evidence about innovation, regulatory policy, and economic growth. Funds from this grant support the Innovation Information Initiative (“I-Cubed”), a diverse, interdisciplinary community of scholars devoted to enhancing research on the economics of science and productivity by increasing the coverage and usefulness of open patent data. Grant funds will support the I-Cubed networks creation and/or expansion of four innovative resources for researchers: a database of connections between patents and scientific papers; a database of connections between patents and retail products; a portal collecting patent metadata that will allow better disambiguation of inventors and inventions; and a database on patent funding that will distinguish, for example, between patents filed by established firms vs entrepreneurs or start-ups. These resources will allow researchers to ask and answer important questions about the economics of science and innovation with greater confidence. That includes questions about the return on investment to basic scientific research, identifying commonalities among innovators, the relationship between innovation and commercialization, and what sorts of funding and work structures are most supportive of patent production.

    To support the growth of a public and sustainable patent data infrastructure and research collaborative that enables novel innovation research

    More
  • grantee: Columbia University
    amount: $564,726
    city: New York, NY
    year: 2021

    To study fairness and bias concerns about artificial intelligence using causal analysis

    • Program Research
    • Initiative Economic Analysis of Science and Technology (EAST)
    • Sub-program Economic Institutions, Behavior, & Performance
    • Investigator Elias Bareinboim

    Correlation is symmetric. If some variable in a dataset, A, rises and falls in correlation with another variable, B, then B also falls and rises with A. Causal relations, in contrast, have direction. Saying “A causes B” is entirely different from saying “B causes A.” The directionality of causation makes detecting and analyzing causation using only correlations extremely difficult. Statistical methods framed entirely in terms of correlation therefore cannot express, let alone analyze or measure, causal relationships. Traditional data analysis also falls short when based on correlations that are spurious—that is, ones caused by random noise rather than fundamental processes. Big datasets do not make such challenges any easier, either. In fact, the opposite is the case. What’s ultimately needed, if we are to detect, measure, and understand causality, are more robust frameworks that draw on a richer set of concepts specifically designed to detect the inherent directionality of causal inference. Computer scientist Elias Bareinboim of Columbia University is developing just such an analytic framework. Drawing on seminal research conducted with his collaborator, computer scientist Judea Pearl, Bareinboim works with graphical methods designed to represent not only correlations between variables in a dataset, but whether and how other variables in the dataset affect those correlations. This framework allows the analyst to ask rigorous counterfactual queries of a dataset (what would have happened if…) that are essential for understanding causal relations among variables. In addition, Bareinboim’s framework is being adapted for implementation by sophisticated AI and machine learning programs. The goal is to allow them to separate causal relationships in data from non-causal correlations.   Grant funds will support Bareinboim’s research on these and related topics for a period of two years.

    To study fairness and bias concerns about artificial intelligence using causal analysis

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