University of Oregon Eugene

NSF Awards · FY 2026 · 2026-09

The rapid growth of large language models (LLMs) has enabled major advances in artificial intelligence (AI), including systems that assist with writing, coding, education, and decision-making. However, training these models demands enormous computing resources, creating significant challenges across multiple dimensions, including model quality, training time, energy efficiency, and reliability. Although many optimization techniques have been proposed, most focus on only one or a few aspects of training, leaving their overall impact on total training efficiency unclear. This project addresses this gap by developing a systematic understanding of the trade-offs among existing optimization strategies and by delivering a quantitative efficiency model that enables informed, cost-aware decision making for LLM training. In addition, the project advances optimization methods in underexplored areas, particularly energy efficiency and reliability. The anticipated outcomes will promote more sustainable computing practices, strengthen national competitiveness in AI, and support applications that advance economic growth, education, national security, and public services. The project also establishes an integrated education program to support workforce development and expand participation in advanced computing and the AI industry. This project develops a unified framework for analyzing and optimizing LLM training efficiency across performance, energy consumption, reliability, and model quality, addressing the growing gap between the unprecedented resource demands of LLM training and the limitations of existing optimization approaches. The research comprises three primary components. First, it develops a novel efficiency model that integrates performance, energy, reliability, and quality optimizations to enable holistic decision making for large-scale training systems. Second, it designs a mathematically grounded, checkpoint-free fault tolerance mechanism that improves error detection and correction while reducing end-to-end training costs and mitigating failure-related interruptions. Third, it develops a knowledge-driven energy optimization approach that enhances the energy efficiency of large-scale LLM training and expands the performance-energy trade-off space to meet diverse cost constraints. The resulting techniques will be integrated into leading large-scale training frameworks and evaluated using state-of-the-art workloads to demonstrate improvements in scalability, robustness, and cost efficiency. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2026 · 2026-03

This award provides student travel for the 2026 Oregon Programming Languages Summer School (OPLSS) to be held at the University of Oregon. This summer school provides an important and valuable educational opportunity for students to study foundational topics related to programming languages and verification. The focus of this year's school is "Types, Proofs, and Program Logic". The significance and importance of the summer school include: instructing how to build and reason about reliability and correctness of computing systems, which is particularly important for systems with artificial intelligence (AI) and machine learning components; building international community and cooperation in foundational research areas; and enhancing education of US students by exposure to and interaction with leading-edge research and researchers. By supporting US-based students, the school will thus train the next generation of researchers and practitioners in both industry and academia, thus supporting NSF priorities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-10

The field of dynamical systems aims to understand how mathematical systems change over time according to a set of rules. It is an active and growing area of mathematical research that is vital in its own right, and has profound interactions with many other fields. Dynamical systems can model a variety of phenomena, from the motion of the human heart to the spread of disease within a population. Since systems often demonstrate chaotic behavior, it is natural to study them through the lens of their underlying geometric structure and dynamical invariants. By studying flexibility and rigidity phenomena in dynamics, the PI will investigate various relationships between these invariants and structural properties, thereby revealing new features of smooth dynamical systems and the geometry of manifolds. Thus, structural aspects of dynamical systems will be clarified with the goal of making the tools of dynamics more readily applicable in other areas of mathematics, as well as other scientific fields. As part of the proposed project, the PI aims to involve undergraduate and graduate students in exploring the behavior of some low-dimensional systems with computer experiments in the context of flexibility and rigidity. The main goals of the project split into two distinct directions. First, the PI will develop techniques to construct uniformly hyperbolic systems, such as geodesic flows on negatively curved manifolds and Anosov volume-preserving diffeomorphisms, in a fixed class with a particular collection of invariants such as entropies and Lyapunov exponents. Concurrently, the PI will determine the natural restrictions on those invariants in a fixed class and search for relations that imply new instances of dynamical and/or geometric rigidity. The second main goal is to produce natural measures that encode dynamical behavior and have good statistical properties in new cases with a focus on non-conformal repellers and geodesic flows on CAT(0) spaces. This project is jointly funded by the Analysis Program of the Division of Mathematical Sciences and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-10

Understanding volcanoes is essential both for advancing knowledge of the dynamic processes that shape our planet and for ensuring public welfare and safety. Volcanic activity provides critical insights into systems that connect Earth’s surface to deep within the planet, and volcanoes pose some of the most unpredictable natural hazards. This project will improve how scientists interpret information about when and where volcanoes have erupted, information which is often incomplete and inconsistent. These insights will support the development of regional statistics to improve hazard assessment and forecasting, an urgent national need identified by the National Academies of Sciences, Engineering, and Medicine. They will also clarify the temporal and spatial scales that drive volcanic behavior. To facilitate participation in science, the project will implement a two-part educational model. It will begin with a general education math course that engages a wide range of students and builds confidence and trust through fundamental, accessible ideas, followed by a second course where students practice framing questions using their newly learned mathematical tools. This emphasis on question-framing is inspired by the research itself, which advances volcanic interpretation by recasting complex Earth science problems as fundamental statistical questions, ones that could arise in an introductory math class. The goal of this project is to develop methods for extracting statistically robust patterns from existing volcanic records. This work is organized into three parts: analyzing volcanism as (1) a temporal process, (2) a spatial process, and (3) a spatio-temporal process. To analyze volcanism in time, the project will discretize eruption records at varying temporal resolutions. Coarse discretizations are reliable but uninformative, while fine discretizations offer more insight at the cost of reliability. An information-theoretic approach will be used to determine the optimal temporal resolution for each record. This analysis will identify the portions of each record with the highest statistical power, quantify the trade-off between reliability and descriptive scope when including lower-quality segments, assess whether the behavior is best characterized as random, clustered, or periodic, and provide a basis for comparing records of differing quality. This component is grounded in the question: ``What is the most active volcano?” Second, spatial analysis will employ Voronoi tessellations to develop truly two-dimensional, area-based metrics for volcanic-vent distributions, rather than relying on existing one-dimensional measures (e.g., inter-vent distance). This areal framework will enable a natural delineation of vent arrangements and the classification of spatial patterns as random, clustered, or regularly spaced, providing the spatial characterization needed to begin answering longstanding questions about controls on stratovolcano spacing and the mechanisms that govern vent clustering. This phase is anchored by the question: "What is the extent of a volcanic field?” Finally, these results will be synthesized into a spatio-temporal model that leverages both spatial and temporal insights to better understand volcanic system dynamics. This portion is framed by: "When and where will the next eruption occur?” Collectively, these methods will produce, for the first time, consistent and comparable statistics for regional volcanism and will yield new tools for both scientific discovery and improved hazard forecasting. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-10

The Cyberinfrastructure Alliance for Oregon (CIAO) is a collaboration across Oregon's eight public universities and Link Oregon, the statewide, non-profit optical network. This project facilitates the development of a statewide strategic cyberinfrastructure (CI) plan to revolutionize the research landscape in Oregon. Building on a strong partnership with Link Oregon, the Oregon Regional Computing Accelerator at Portland State University (NSF Award #2346732), and a committed statewide research computing group, this plan increases capability for world-class research, addresses current limitations to access to CI resources at smaller institutions, and supports educational programs to build a skilled workforce for Oregon. This project is designed to boost research productivity across the state, enable Oregon to support U.S. leadership in science and engineering, and provide a model that could be applied in other states to address strategic CI needs. This project outlines a shared vision, values, and goals to guide future investments in CI, aligning efforts across the state and empowering institutions to execute strategically. The plan 1) facilitates regional collaboration and data sharing, 2) fosters a community of practice for research IT professionals, and 3) develops the CI Strategic Plan for Oregon. Key activities include campus visits, data collection, and statewide workshops to strengthen regional and multi-disciplinary collaboration, workforce development, and expansion of research computing capabilities across Oregon's public universities. CIAO will work with campus leaders, research IT leaders, an external advisory board with national expertise, and university leadership on developing, reviewing, approving, and disseminating the strategic plan. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-10

This project seeks to fund US-based students to attend ACM SIGCOMM Internet Measurement Conference (IMC) 2025, held in Madison, Wisconsin on October 28 - 31, 2025. ICM 2025 is a premier annual forum that attracts high-quality, forward-looking research contributions and provides a vibrant forum for technical and professional exchanges. ICM 2025 will expose students to cutting-edge developments in the field and enable interactions with world-leading researchers. Students will gain feedback on their ongoing work, broaden their academic perspectives, and build lasting professional connections. This project supports students from US universities to attend ACM IMC 2025 conference in person. Students will have the opportunity to present their work and be exposed to state-of-the-art developments in the field. They will also have the opportunity to interact with peers from institutions worldwide, meet with senior researchers, and participate in discussions that are likely to shape the future of the field. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Ramesh Jasti of the University of Oregon will explore new ways to design and build “carbon nanohoops,” a unique type of molecular ring made entirely of carbon atoms arranged in a circle. These molecules have unusual electronic and optical properties that make them promising building blocks for future technologies. This work aims to broaden the utility of nanohoops in optoelectronic materials and provide fundamental insight into how molecular design governs the properties of strained pi-systems. In addition to the scientific goals, this work will provide training opportunities for students at all levels and support outreach programs that introduce young learners to science. This research will focus on the design, synthesis, and characterization of donor-acceptor (D–A) substituted [n]cycloparaphenylenes (CPPs) and related nanohoops to understand how electronic modulation alters their photophysical properties and supramolecular interactions. Systematic variations in nanohoop size and D–A substitution patterns will be used to tune emission wavelengths, quantum yields, and solubility. The team will also investigate how these modifications influence host–guest chemistry, with a particular focus on generating strongly bound ring-in-ring complexes using pi–pi donor–acceptor interactions. Spectroscopic and electrochemical studies, complemented by computational modeling, will guide the understanding of structure–property relationships. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Diamond consists of a regular array or a lattice of carbon atoms as well as an extremely small number of defects in the carbon lattice, including impurities, such as nitrogen or silicon atoms, and vacancies - places in the lattice where atoms are missing. Suitable combinations of impurities and vacancies can lead to the formation of color centers, which interact with light and give color to an otherwise transparent diamond. A special color center is a “silicon-vacancy”, which consists of two adjacent vacancies with a silicon atom inserted in between. An electron trapped in such a color center can serve as a “quantum bit” or a qubit - fundamental unit of quantum information. An outstanding challenge for using these qubits to develop solid-state quantum computers is to mediate and precisely control the interactions between the qubits. This experimental program couples silicon vacancy qubits to the compressional mechanical vibrations of a micrometer-sized thin rectangular diamond plate, which is embedded in a specially designed square lattice fabricated on the diamond film. The vibrational energy level structure of the square lattice isolates and protects the compressional vibrations. Interactions between the qubit and the compressional vibrations will be investigated at the level of single quanta of the mechanical vibrations, with the goal of mediating and controlling interactions between two silicon-vacancy qubits through their coupling to the mechanical vibrations. In addition, this program will also make contributions to education and human resources by providing excellent training to graduate and undergraduate students in quantum information science and technology. This program focuses on experimental studies of diamond spin-mechanical systems, in which spin qubits are coupled to vibrations of a nanomechanical resonator. The primary experimental platform is a GHz diamond Lamb wave resonator, essentially a thin rectangular elastic plate with free boundaries, embedded in a phononic crystal lattice. Owing to the protection by the suitably designed phononic band gap, the compressional mechanical modes of the Lamb wave resonator can feature ultrasmall mechanical loss with a mechanical linewidth less than a few hundred Hz. Spin qubits such as silicon vacancy centers will be implanted in diamond Lamb wave resonators. These resonators will be employed for the exploration of the quantum regime of spin-mechanics through a phononic cavity QED process, for which a silicon vacancy spin qubit is coupled to the fundamental compression mode via a direct acoustic transition. The ultrasmall mechanical loss and the robust spin coherence of a silicon vacancy spin qubit at low temperature can in principle lead to cooperativity, a dimensionless parameter that characterizes the spin-mechanical coupling, as large as 1 million. The successful completion of these studies will pave the way for entangling two distant spin qubits via their coupling to a mechanical normal mode of coupled mechanical resonators. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

This Pathways to Enable Open-Source Ecosystems (POSE) project increases access to a microfiber scaffold technology, fostering innovation through the creation of a comprehensive and robust, open-source hardware ecosystem. This project centers around a cutting-edge 3D printing technology known as melt electrowriting (MEW), a method for weaving intricate microfiber structures into porous materials. The project's open-source approach enables communities to perform rapid experimentation and adaptation of hardware. The low-cost and open-source system provides a global entry for the United States and advances the country’s technological and scientific leadership. As MEW is used in critical areas such as regenerative medicine, robotics, cancer research, and materials science, the project creates an opportunity to empower the domestic maker community. This solution improves future healthcare treatments for the aging, sick, and/or injured populations while training bioengineers in future manufacturing practices. This POSE project scopes the feasibility of making an advanced bioengineering printer more affordable. In this project, efforts focus on identifying user groups poised to leverage the modifiable nature of the open-source printer to build, train and then quickly implement MEW technologies into applications that require high-performance materials. This solution is expected to identify and leverage collaborations so that multidisciplinary groups of researchers can nimbly advance manufacturing projects. Planned activities include community building, developing governance and organizational structures, and ensuring quality, security, and privacy. Additionally, the open-source platform serves as an essential educational and training resource in advanced manufacturing and mechatronics, preparing bioengineering students for careers in automated biomanufacturing and artificial intelligence-guided fabrication. The overall goal of this project is to establish and rapidly expand domestic capabilities in MEW, fostering technological innovation and securing intellectual leadership in advanced biofabrication. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Johnson of the University of Oregon will expand on a molecular self-assembly strategy to make stable, complex molecular cages and large cyclic structures from simple building blocks. This project aims to establish design rules on how the shapes and sizes of the building blocks as well as subtle effects in the self-assembly process will influence the structures and properties of the resulting products. This research may provide efficient routes to new dynamic structures for stimuli-responsive materials. Professional development activities for students will include experience in mentorship and participation in Lens of the Market workshops to learn the basics of intellectual property protection and research translation. The Johnson lab has developed a design strategy to use Group 15 ions (or Cu+) as directing elements in self-assembly reactions of oligothiols to direct formation of discrete disulfide assemblies under mild oxidizing conditions. These products are formed under thermodynamic control to yield a variety of macrocycles, dimeric cages, unsymmetrical cages, and tetrahedral assemblies. The project will involve three specific aims: Aim 1 will explore the fundamental physical organic chemistry of dynamic disulfide formation in order to develop subtle control of thiol oxidation and self-assembly pathways; Aim 2 will seek to harness subtle effects in ligand sterics, shape, and reactivity to control self-assembly and influence product distribution. Aim 3 will extend the approach to controlling disulfide assembly in water. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

With the support from the Macromolecular, Supramolecular and Nanochemistry Program in the NSF Division of Chemistry, Prof. Michael Haley, Prof. Darren Johnson and their students at the University of Oregon will investigate an underexplored class of molecules that contain adjacent phosphorous and nitrogen centers. Properly known as azaphosphinines, these “PN-heterocycles” feature a strong hydrogen bond donor adjacent to a strong hydrogen bond acceptor within a compact, fluorescent core. This research will explore and expand the utility of these fluorescent molecules as strong hydrogen bonding motifs for self-assembly and molecular recognition. This project provides interdisciplinary research training to both graduate and undergraduate researchers. The broader impacts of this project also include: (1) individual development plans, (2) regional, national, and international collaborations, (3) internship opportunities at universities, national labs, and companies, and (4) mentoring opportunities to ensure students receive both a depth of technical training as well as a breadth of professional training to launch their careers. The PIs’ commitment to mentoring, undergraduate research, and innovation ensures the research will have the broadest possible impacts. This fundamental research aims to design and synthesize azaphosphinines as new fluorophores and as recognition motifs in supramolecular chemistry, organic materials, and molecule/ion recognition. The aims of this project involve study of: (1) quadruple hydrogen-bonded azaphosphinines, (2) azaphosphinine/phenylurea hybrid hosts for oxoanion binding, (3) reduction to PIII azaphosphinines, and (4) azaphosphinines in higher order supramolecular structures. The goal of our research program is to expand the fundamental understanding of our PN-heterocycles and extend these studies into supramolecular chemistry and molecular recognition. These uncommon heterocycles have the advantage of a very strong hydrogen bonding motif within an inherently fluorescent scaffold, putting both chiral recognition and signal transduction elements directly at the site of recognition and assembly. This research employs a combination of methods (including NMR spectroscopic and UV-Vis spectrophotometric titrations) to determine the binding properties of the supramolecular receptors and to gain a better understanding of how structural changes influence their binding affinity, selectivity, and optoelectronic properties. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Large earthquakes can cause devastating damage, particularly in regions where soft sediments amplify shaking. Many major cities around the world, including those in the Pacific Northwest of the United States, are built on sedimentary basins that can trap seismic waves and greatly increase both their intensity and duration of shaking. Over 12 million people live in this region, which has the potential to produce both a megathrust great earthquake (potentially M9+) and also smaller crustal earthquakes that occur closer to population centers. This project aims to improve our understanding of how local geological structures affect earthquake ground motion amplification in the Pacific Northwest, particularly in densely populated sedimentary basins. The researchers will develop new ways to constrain the subsurface structure of Cascadia forearc basins to provide better information that can guide estimates of ground motions from seismic hazards. All data, methods, and results will be openly shared to support the broader scientific community and regional velocity model-building efforts, including collaboration with the Cascadia Region Earthquake Science Center (CRESCENT). This study will develop and apply two complementary passive seismic techniques to characterize the shallow subsurface structure of the Cascadia forearc basin, where most of the population in the Pacific Northwest lives. The research team will use particle motion analysis from teleseismic earthquakes to help define shallow shear-wave velocity structure inside and outside the basin. Then, using horizontal-to-vertical spectral ratios from local earthquakes and ambient noise, basin geometry will be constrained. The results will be incorporated into regional-scale seismic velocity models such as the Cascadia Region Earthquake Science Center (CRESCENT) Community Velocity Model (CVM). Numerical simulations will help assess how the newly defined basin structures amplify ground motion during earthquakes. This research addresses a key gap in understanding how local geology influences seismic hazard at a regional scale—an issue of critical importance for earthquake-prone areas globally. The methods developed here are globally applicable and will represent a new approach to determining seismic shaking potential in basin settings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Plants have a unique life cycle that allows natural selection to affect the adult stage, as well as the earliest stages of reproduction—when pollen delivers genetic material and seeds begin to develop. This project explores how plants may improve the quality of their offspring by favoring certain genetic traits during these stages of reproduction. By influencing which traits are passed on to subsequent generations, these processes may help eliminate harmful mutations and promote characteristics that increase survival under challenging environmental conditions. Understanding how selection works at these critical early points in development sheds light on how plants adapt to changing environments and maintain the genetic diversity necessary for long-term evolutionary success. In addition to contributing to our knowledge of plant evolution, this research has potential applications in crop improvement and will support extensive training of graduate and undergraduate students and outreach through public presentations of topics related to this research. This research combines experimental manipulations and genomic analyses in the model plant Mimulus guttatus to investigate how natural selection during two early reproductive stages, haploid gametophytic selection and selective embryo abortion, influences patterns of inheritance, seedling fitness, and the potential for adaptation. Through a series of controlled crosses between homozygous and heterozygous lines grown in varied nutrient and salinity conditions, the researchers will identify deviations from expected patterns of genetic transmission (transmission ratio distortion) that indicate selection. Whole-genome sequencing of pooled offspring will pinpoint genomic regions affected by gametophytic selection and selective embryo abortion. Follow-up experiments will measure the fitness consequences of these genetic differences during seedling growth and assess whether selection at early stages helps remove deleterious mutations or promotes the spread of beneficial alleles. The project will also evaluate whether the same genetic variants influence traits across different life stages and how this shapes evolutionary outcomes. This is the first study to assess genome-wide developmental selection across plant life stages and will provide insights into how early reproductive processes contribute to evolution, genetic diversity, and environmental adaptation. Undergraduate and graduate students will gain hands-on experience in experimental and genomic research, and a new course-based undergraduate research experience will be developed to engage students in exploring plant reproduction and evolution in college biology classrooms. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Pollinators, such as bees and other insects, are essential to ecosystems and agriculture, yet their populations are in decline. Understanding why this is happening, and how we can help, requires long-term data on their interactions with plants. However, historical records of these relationships are rare. The research team has uncovered a unique dataset from over 50 years ago, documenting thousands of plant-pollinator interactions across California, from coastal regions to mountain peaks. By revisiting these locations and comparing past and present data, the team will investigate how pollinator communities have changed over time and which species are most at risk. This study is the first to examine multiple locations, providing critical insights into how long-term environmental change reshapes communities. By making data publicly available and collaborating with community scientists, the research will help ensure ongoing monitoring of pollinators in California. The study will also provide hands-on learning experiences for students and volunteers, fostering the next generation of environmental scientists. Given California’s role as a global bee biodiversity hotspot and key pollinator-dependent agricultural area, the insights gained from this research will have far-reaching implications for pollinator conservation and food security. The research will provide the first multi-site, longitudinal study of the interacting effects of environmental change stressors on plant-pollinator interactions. The research will answer three key questions: (1) How have plant and pollinator communities changed over the past half-century? (2) Do certain species’ interaction patterns make them more vulnerable to environmental changes? (3) How can public interest in pollinators help engage and educate future conservationists? To address these questions, the researchers will facilitate community and student involvement in testing hypotheses related to the theories of interacting stressors, biodiversity, and ecosystem function and how species interactions affect population vulnerability. The research will use standardized surveys, network analyses, and structural equation modeling to quantify 50-year changes in plant–pollinator communities. Because the research investigates communities of plants and pollinators, two ecologically distinct and ubiquitous taxa across terrestrial ecosystem, this proposed research will yield a generalizable framework for understanding the influence of environmental change across other interacting species. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

The NSF ECR Building Capacity in STEM Education Research (BCSER) program contributes to the NSF mission (42 U.S. Code Chapter 16) by building the U.S. workforce undertaking STEM education research. The BCSER Individual Investigator Development in STEM Education Research (IID) track supports individual investigators who are new to STEM education research to develop foundational skills and gain practical experience to advance STEM education knowledge through mentored professional development and pilot research activities. STEM education research generates the knowledge, theories, and understandings on which viable strategies for improving STEM education and workforce outcomes are based. This project will investigate student motivation in introductory general education astronomy courses, focusing on skills in written communication and critical thinking. This BCSER IID project will allow the principal investigator (PI) to develop foundational skills and gain practical experience in designing and implementing cutting-edge STEM education research using innovative methods and tools. The project will help the PI to develop new expertise in STEM education research, including mixed methods approaches to studying motivation (e.g., latent cluster analysis, qualitative coding), and deepen theoretical knowledge in expectancy-value theory and self-determination theory. The PI will be mentored by experts in quantitative and qualitative methods, gaining skills in designing interview protocols, coding qualitative data, and analyzing motivation-related constructs in science and engineering education contexts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Seed production by trees plays an essential role in the ecological and economic stability of future forests because seeds directly contribute to the growth of new trees. This is especially critical in boreal forests, which cover about 30% of the Earth’s area. Previous studies of the effects of environmental variability on boreal tree species have focused on tree growth and species’ range shifts, however a key gap in knowledge is understanding how tree reproduction is affected by abiotic conditions, such as temperature or precipitation. Advancing our understanding of the North American boreal forest is challenging because it is very large, the environmental conditions vary by region, and boreal tree species differ in their habitats and traits. Also, current forest models either ignore tree reproduction entirely or simplify it to assume that seed availability is constant. This project will test how abiotic factors (CO2 levels, temperature, water availability, nitrogen deposition, wildfire) interact to affect seed quantity and quality (seed mass, seed chemistry, seed germination rates). This information will be used in models to predict the future of boreal forests. This research will inform federal and state agencies about drivers of seed production and viability, increase public scientific literacy about tree dynamics and boreal forests, and add cone specimens from North American boreal forests to the Missouri Botanical Garden herbarium for future use. The project will train three graduate students and six undergraduates in conducting scientific research, as well as support a youth training program. Boreal conifer species with widespread distributions, including balsam fir, black spruce, eastern tamarack, jack pine, and white spruce, are ideal for investigating how abiotic factors affect seed production. This project will combine historical collections of cones and seeds in herbaria dating back to the 1820s, present day cone and seed collections across the distribution of boreal conifer species, and cones from trees in an ecosystem-scale experiment. The information from these field collections will be used in spatial modeling of landscapes from interior Alaska to the eastern North American boreal forests, in order to forecast the future composition of boreal forests. This research provides more than a snapshot in time or space, as it leverages specimens going back 200 years and then forecasts until the end of this century, as well as sampling vast regions of the continental distribution of the North American boreal forest and forecasts across regions totaling 18 million hectares (44 million acres). This research has important implications for understanding the future of boreal forests across North America, and for forestry and future timber production. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The initial discovery of gravitational waves in 2015 by LIGO confirmed a crucial prediction of General Relativity made by Einstein a century earlier. The gravitational waves observed by LIGO in 2015 resulted from the collision of two black holes, each roughly thirty times more massive than our sun. Although this was an amazing natural event, it was only observable by gravitational waves -- the ripples in spacetime which propagate outward across the cosmos for millions of light-years and may eventually be noticed by the LIGO observatories. It underscores the potential of LIGO to make unique contributions to astronomy, astrophysics, and cosmology. Since 2015, LIGO has recorded approximately 300 such collisions, mostly of pairs of black holes, but also of black holes with neutron stars, and pairs of neutron stars. Indeed, with this unique collection in hand, LIGO has been able to make new statements about the origins of massive stars in the universe, and, paired with more conventional astronomical observations, provided new insights into the origin of heavy elements, which are crucial to life on Earth. Meanwhile, the LIGO observatories have become increasingly sensitive to ever smaller spacetime ripples. This has enabled the potential for discoveries -- the observation of gravitational waves from different types of astrophysical objects, objects which are not pairs of black holes and/or neutron stars. This award will set up LIGO gravitational wave searches from two promising new sources, namely collapsing black holes and extremely magnetized neutron stars. The former are associated with the explosive phenomena known as (long) gamma-ray bursts (GRBs), while the latter are associated with magnetar x-ray flares and fast radio bursts. This award will support graduate students at University of Oregon (UO), who will develop new methods to carry out novel searches and to develop methodology to make astrophysical inferences from the results, i.e. what we have learned about the death throes of massive stars and the inner workings of neutron stars. It is expected that these students will either continue in the field or will enter the private sector, where they will carry their expertise in data science and analysis. The UO group will continue to carry out workshops for Oregon high school teachers, and this award will spawn a new activity in direct public outreach via “pub talks.” This award will combine two emerging areas of astrophysics to probe sources of gravitational waves from progenitors that are not compact binary mergers. The first area is multi-messenger astronomy (MMA). The second area is the search for gravitational-wave signals without waveform templates – the so-called burst analyses. The searches will fundamentally rely on MMA observational results. X-ray, gamma-ray, or radio transient signals from astrophysically energetic events provide a time and sky location that also mark an episode of putative gravitational-wave emission. These provide the so-called triggers for the gravitational-wave data analysis, which labels the time near the trigger as the “on-source” (or signal) data segment, and the off-source data as the background. Excess signal power relative to background is an indicator of a potential gravitational-wave detection in association with the triggering gamma-ray burst (GRB), magnetar x-ray flare, or optical supernova breakout observation. This method does not rely on any predetermined mathematical form for the gravitational waves. Astrophysical inference with gravitational waves to date has involved analyses that rely on systems of compact (black hole or neutron star) binary systems. The team will explore a new pathway for astrophysical inference, one involving the gravitational wave burst analyses of non-binary systems. It is crucial to not only develop methods to confidently detect gravitational waves from novel sources but also to infer new and unique statements about the astrophysical properties of the emitting systems. This new window of opportunity is made possible by its reliance on multi-messenger data, including new observations by the Vera Rubin Observatory, and by the ever-increasing sensitivity of the LIGO, Virgo, and KAGRA gravitational wave observatories. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The flight path of an airplane, the shape of a DNA strand, and the arc of a bridge are all described by curves in 3-space. In each case, it is natural, and often important, to understand how those curves can move or vary. Over time, curves that move, and perhaps coalesce, sweep surfaces. These surfaces lie not in the familiar 3-dimensional space, but in 4-space, with time as the fourth coordinate. This project develops several tools, all centered around understanding curves in 3-space and surfaces in 4-space. One project studies techniques called Floer homology, that use the global behavior of partial differential equations to study curves. Those tools encode a lot of information, but are hard to compute; the project studies properties that let one extract information from them in a practical way. Another project uses techniques from high-dimensional topology to study a particular class of curves that arise from wave fronts, called Legendrian knots. A third project focuses on the information contained in an algebraic invariant of surfaces, Khovanov homology. Broader impacts of this project include graduate training, seminars, and writing a textbook that would be a resource for students and early researchers in Khovanov homology. Heegaard Floer homology, Khovanov homology, and Floer homotopy theory continue to transform the understanding of low-dimensional topology. Their impact has faced certain limits, however. While the Khovanov invariants for surfaces distinguish some surfaces not visible to knot Floer homology, there are few tools for computing these Khovanov invariants, other than brute force and good fortune. There is also a lack of tools for computing the most refined Heegaard Floer invariants (e.g., the concordance invariant Upsilon) in natural settings, like for satellite knots. There is a lack of explicit examples in Floer homotopy theory, particularly of higher structures like the spectral Fukaya category, making it harder to understand, in detail, what structures should be sought and what information they likely contain. This project seeks to address these difficulties, by developing formal properties of the Khovanov invariants of surfaces, an extension of the "minus" variant of Heegaard Floer homology to 3-manifolds with boundary, and a stable homotopy refinement of Legendrian contact homology. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

This project explores exciting new interactions between two central areas of mathematics - algebra and geometry - and their unexpected connections through physics. Algebra and geometry are foundational tools in mathematics, widely used in numerous scientific and engineering applications, such as computer science, data analysis, robotics, and theoretical physics. Historically, the interplay between algebraic equations and geometric shapes has led to powerful methods and profound insights, shaping much of modern mathematics and technology. In recent decades, researchers discovered surprising connections linking algebraic geometry, which studies shapes defined by polynomial equations, to symplectic geometry, an area crucial to physics and engineering. This project leverages these emerging connections to develop new mathematical tools that bridge algebra and geometry. Broader impacts of this research include significant training and mentoring activities. The project supports early-career researchers and graduate students, providing extensive professional development through workshops, virtual seminars, public lectures, and the creation of publicly available computational tools. On the technical side, the project aims to advance understanding in multigraded commutative algebra, toric geometry, and symplectic geometry. It addresses long-standing gaps and open questions in commutative algebra and toric geometry by introducing methods inspired by recent advances in homological mirror symmetry into purely algebraic contexts. The P.I.’s will explore new approaches to studying multigraded polynomial rings, aiming to uncover deeper structural properties that parallel classical results for standard graded polynomial rings. The project will develop algebraic analogues of effective symplectic geometry techniques, such as "stop manipulation," adapting these symplectic methods to algebraic settings. The project will also extend foundational results, including Orlov’s Theorem, to multigraded and toric settings, construct novel categorical structures that unify algebraic and geometric perspectives, explore applications to virtual resolutions and other questions involving shortest resolutions, and investigate extensions to broader classes of geometric objects through toric degenerations and natural generalizations from toric varieties. Furthermore, by establishing explicit links between algebraic constructions and Fukaya categories, the project will introduce new computational tools and theoretical approaches in symplectic geometry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

A species will not survive if it does not reproduce. Successful reproduction in fish combines the quality of eggs and sperm with behaviors that result in mixing of these two types of reproductive cells. Observations suggest that changes in temperature and environmental toxins may critically impact reproduction of many fish species by shifting the ratios of males to females in the population, by affecting sperm and egg quality, and by changing reproductive behavior. Understanding how environmental variables affect these aspects of reproduction has broad impact because a decrease in reproductive efficiency of pivotal fish species would imperil important human food sources and damage the ecology of many aquatic environments. This project examines the effects of elevated temperatures and the pollutant dioxin on reproductive success of zebrafish as a stand-in for many fish species. These studies have scientific importance and are novel because the interactions of temperature and pollutants on fish reproduction have not previously been investigated. Results will inform on the mechanisms of reproductive resilience in fish and help predict how resilient fish species will be to future changes in the environment. The project also includes public outreach in the form of a museum exhibit and engaging educational material for children. Acute temperature changes of ~10°C can alter fish sex ratios and reduce gamete quality. Similar temperature changes can also alter neuronal function and synaptic transmission in most vertebrates. How ‘subtle,’ yet persistent, average temperature changes (2-6°C) might affect these properties to modulate reproduction remain unknown. Pollutants such as 2,3,7,8 –tetrachlorodibenzo-p-dioxin (TCDD, dioxin) affect signaling of estrogen, an important hormone for gonad development and for establishing sex-appropriate reproductive behaviors. The researchers hypothesize that temperature rise and low-level pollutants impact the same or interacting neural and/or gonadal pathways to affect fish sexual reproduction. As a consequence, subthreshold perturbations, meaning modest temperature rise and low-level dioxin exposure, combine to produce significant effects on reproductive success. Leveraging the genetic and experimental tractability of the zebrafish, proposed studies examine changes in behavior, neuronal development and function, and sex phenotypes caused by a 2-6°C average increase in temperature over an individual’s lifetime. They also examine the effect of environmentally relevant levels of dioxin on these same variables, and whether temperature rise and dioxin exposure synergize to detrimentally affect zebrafish reproductive efficiency at the neuronal, behavioral, and gonad development levels. This research will provide critical information on the potential of a critical decrease in reproductive efficiency of pivotal fish species, which could reduce an important human food source and damage the ecology of many aquatic environments. This project is supported jointly by Division of Integrative Organismal Systems in the Directorate for Biological Science of NSF and the Kavli Foundation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Solutions to real-world problems, such as scientific document question-answering, cybersecurity diagnosis, and e-commerce personalization, can often be improved by augmenting the underlying generative artificial intelligence-based (Gen-AI) systems with retrieved external knowledge. Much of this external knowledge is organized in graph-structured formats that encode unique relational signals. For example, citation links among scientific papers reveal their deep intellectual dependencies across different fields. Recurring co-occurrences among software components and vulnerability reports can reveal latent causal chains triggering security flaws. Online human interactions, such as liking, commenting, or reposting, reflect individual traits and preferences. This project pioneers retrieval techniques that locate the appropriate graph-structured knowledge and infuse it to assist Gen-AI systems with solving downstream problems, closing critical knowledge gaps, and enabling more useful, trustworthy, and diverse predictions, discovery, and decision-making. In personalization, the proposed retrieval techniques could give a social e-commerce platform a holistic view of each customer and support highly personalized recommendations. In cybersecurity, hidden dependencies among vulnerabilities and defenses could be exploited, allowing security operators to trace multi-step attack chains and harden critical systems against emerging threats. In scientific discovery and innovation, the relational knowledge in our proposed graph-level retrieval could facilitate exploration of multifaceted content and provide diverse insights that push existing knowledge boundaries. To meet these goals, this project pioneers a transformative roadmap to build well-rounded graph retrieval techniques for retrieval-augmented generation (RAG) systems that advance three dimensions: (1) Improving utility by harmonizing knowledge between structured knowledge in graphs and neural knowledge in large language models via structured knowledge checking, aligning retrieval emphasis with user interests by estimating continuously evolving trends, and incorporating agentic planning and reasoning capabilities for intelligent multi-round graph-structured traversal; (2) Safeguarding trustworthiness by reliably retrieving error-controlled graph-structured knowledge, disclosing vulnerability by designing structure-informed threat models and improving safety with data-centric textual subgraph anomaly detection and model-centric neighborhood trend filtering; (3) Promoting knowledge diversity through multi-agent collaborative exploration at both the conceptual subgraph and individual entity level. Together, these innovations will yield theoretical advances in graph algorithms, retrieval modeling, and graph-structured knowledge representations, ultimately transforming how graph-structured knowledge is discovered, integrated, and applied in RAG and Gen-AI systems across impactful domains, such as healthcare, scientific innovation, personalization, cyber defense, and targeting. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The Major Research Instrumentation award is made to the University of Oregon to acquire a cold-field emission, aberration probe-corrected scanning transmission electron microscope (STEM) - the first of its kind at a university in the state of Oregon. This instrument advances materials research, enables next-generation electron optics, and provides training for graduate and undergraduate students. By integrating the electron microscope into the Center for Advanced Materials Characterization at Oregon, a comprehensive research core facility with open access and highly qualified staff, the microscope is accessible to academic and industry users across the Pacific Northwest, accelerating research across materials science, electron optics, quantum information sciences, and microelectronics. An aberration-corrected scanning transmission electron microscope is an essential and versatile analytical tool for characterizing atomic structures and properties of matter at the highest spatial resolution. Specifically, a STEM with a spherical aberration corrector for the probe is required for research efforts in materials science and quantum physics conducted at the University of Oregon, Oregon State University and nearby institutions. This includes investigations into new physical phenomena that hinge upon measurements of atomic positions such as the relationship between structural chirality and charge density in Weyl-semimetals with novel topological magneto-electric responses or emergent behaviors at the atomic interface of magnetic topological skyrmions and superconductors, which differs greatly from its bulk constituents. The atomic-layered van der Waals heterostructures can be engineered in three-dimensions to encompass thermoelectric, photoelectric, or magnetic properties that depend sensitively upon the atomic nanoarchitecture. Here, the layer thicknesses and layer sequence can modify the amount of charge transfer between constituent layers leading to interfacial charge density and an alteration of the size and orientation of the polycrystalline domains. STEM imaging of these complex materials is critical for understanding how interfaces affect the function of these heterostructures. Only careful atom-by-atom characterization can provide suitable information about the underlying electronic properties of these systems. This tool also serves as a platform for developing new electron optics and imaging techniques such as STEM holography and interaction-free imaging that goes beyond conventional STEM imaging techniques. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

Food web links influence how energy flows through the ocean and are therefore of broad interest to marine scientists. One group of marine predators that are widespread but not well understood are jellyfish and other gelatinous animals that use tentacles to hunt and ambush their prey. Emerging evidence shows that through predation with specialized tentacles, different gelatinous predators hunt different prey types, and these hunting preferences vary widely even within closely related species. This project addresses how jellies with diverse body shapes, tentacle structures and ways of hunting impact the balance of marine food webs in distinct ways. The team is using cutting-edge techniques, such as underwater cameras, microscopy, laser-based scanning and machine learning, in novel and multi-scale ways to achieve unprecedented resolution of predator prey relationships in three dimensions. These approaches allow the team, for the first time, to accurately reconstruct the predation strategies across these gelatinous ambush predators from individual cells to whole ecosystems. This project includes research training for postdoctoral scientists and undergraduate students, and educational outreach to middle and high school students. Project results are being communicated to broad audiences by working with artists and leveraging the unique video and imagery created during the research process. Tentaculate ambush predators (TAPs) are a functional group of gelatinous marine organisms that wait motionless to capture their motile prey through contact with sticky and/or stinging tentacles. TAPs comprise three distantly related taxa–siphonophores, cydippid ctenophores, and hydromedusae–and are ubiquitous and abundant throughout coastal, open ocean and midwater ecosystems. TAPs may be critical for structuring marine communities, but knowledge of their feeding impacts and mechanisms is limited. Quantifying trophic effects has been hampered by the challenge of working with fragile gelatinous organisms, which are often absent or underrepresented in net samples and do not behave naturally in the lab. This project uses new in situ imaging techniques that minimally disturb fragile plankton to quantify: 1) tentacle array structures, 2) prey-capture cell distributions, 3) tentacle deployment behaviors, 4) prey capture location, 5) prey encounter rates and ingestion, and 6) ecosystem level predation impacts of TAPs. The resulting mechanistic basis for prey capture are applicable to current and future measurements of tentaculate prey abundance, improving predation impact estimates and parameterization of food web models ranging from regional to global scales. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

Interesting and impactful mathematics often arises when new connections are made between different fields of math. While even heuristic connections can be fruitful, mirror symmetry provides a fascinating direct connection, originating from modern physics, between algebraic geometry and symplectic topology that has led to major advances in both areas. Algebraic geometry is a rich and classical field of mathematics that explores shapes called algebraic varieties described by polynomial equations. Symplectic topology is a younger area that studies shapes built from a geometric formalism for classical mechanics by packaging solutions to certain partial differential equations into algebraic invariants. This project aims to deepen our understanding of the mirror symmetry phenomenon by building on new insights in a special case where the algebraic varieties are particularly symmetric. This will be done with the aim of verifying new cases of the homological mirror symmetry conjecture, exploring structural aspects of a symplectic invariant known as the Fukaya category, and investigating arithmetic aspects of mirror symmetry. The project will also involve undergraduate research projects on combinatorial problems coming from mirror symmetry. The first technical goal of the project is to further develop functorial aspects of the toric homological mirror symmetry equivalence by enlarging the list of sheaves and functors that can be provably described in terms of Lagrangian submanifolds and geometric operations on them. These geometric functors will give a better understanding of homological mirror symmetry for singular varieties obtained by gluing toric varieties along toric strata, which can then be deformed to obtain new cases of the homological mirror symmetry conjecture. In the other direction, the project will seek to leverage the geometric flexibility of the Fukaya category to construct new group actions on derived categories of toric varieties. The project will also aim to determine when symplectic fibrations can be described in terms of cornered Liouville sectors resulting in a gluing formula for their Fukaya categories. Finally, the project will explore the extent to which the toric Frobenius morphism and its simple geometric description on the mirror can be extended to other classes of varieties with an eye towards generation time in the derived category. This project is jointly funded by Topology and Geometric Analysis program and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-03

No two people speak exactly alike. As a result, one person’s "pole" might sound like another person’s "bowl." The difference between such minimally different words comes down to small details in how they are pronounced. Some of these details vary across accents. However, no matter who the speaker is, listeners can quickly adjust to novel accents. This project examines how people adapt to talker differences in speech production and tests the hypothesis that people adapt by shifting their attention to different acoustic cues when it improves accuracy. The research is guided by a computer model that predicts how this process works. Societal benefits include a training app, training for graduate and undergraduate students, and publicly sharing available materials. This project combines computational modeling and behavioral experimentation to test key predictions of a computational model of accent adaptation. The model is built on the ideas of learned selective attention theory and reinforcement learning, representing a novel application of these theories to speech perception. The central hypothesis of the model is that listeners use reinforcement learning from prediction error to rapidly reallocate attention across perceptual dimensions. This project tests (1) whether focusing attention on a perceptual dimension makes it easier to learn about that dimension’s relationship to speech categories, (2) whether individuals who weight a dimension highly are the individuals who find it easiest to change the weight of that dimension, and (3) whether variability along a dimension has a different effect on learning rate depending on whether the dimension is to be up-weighted or down-weighted. In doing so, this project advances an account of learned selective attention theory for speech perception. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.