University Of Wisconsin-Madison

NIH Research Projects · FY 2026 · 2026-02

Project Summary/Abstract Ocular Herpes Simplex Virus 1 (HSV-1) is a leading cause of blindness in the US and results from repeated reactivation of latent virus from reservoirs established in host sensory neurons. Latent HSV-1 reservoirs are created when virions infect neuronal axons and travel by retrograde transport to the sensory neuron. While the latent stage of HSV-1 is dormant and not associated with disease, latent virus presents a significant clinical challenge since virus in those reservoirs can reactivate, replicate, and transmit virus to new hosts. During a reactivation event, limited numbers of latently infected neurons produce infectious virus that is transported to the cornea by anterograde transport. That virus can then be spread to other hosts. Nonetheless, mechanisms that govern initiation and completion of reactivation events are unknown, impairing the development of novel therapeutics that can deplete reservoirs or prevent reactivation then transmission of virus to new people. In our proposed research we have identified cellular elements and viral elements that are required to start and then complete the process of reactivation from neurons. We have combined a new human neuronal platform with novel technology known as Chromosome Conformation Capture circular-sequencing to identify virally encoded chromatin loops that can further be targeted for disruption to prevent HSV reactivation and transmission. These new methods have allowed us to generate a novel and paradigm shifting hypothesis. We hypothesize that the function of chromatin insulators in the HSV-1 genome silences gene expression to establish latency, while the initiation of reactivation from latency ameliorates the chromatin insulator function to allow gene expression and subsequent reactivation. We have designed three aims that will allow us to 1) fully define the mechanisms for how this happens during latency and in reactivation and 2) to develop novel therapeutics in accordance with the strategic priorities of the NIH HSV strategic plan. Our novel therapeutic arm of this proposal combines mechanistic data with treatment of infections in the eye by depletion of viral proteins using rAAV-delivered siRNAs or editing of viral genomes using rAAV-delivered CRISPRs. Collectively, our proposal will leverage mechanisms involved in reactivation with targeting those mechanisms to therapeutically block reactivation or deplete latent reservoirs.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY/ABSTRACT The Centers for Disease Control and Prevention classifies Clostridioides difficile (Cd) as an urgent threat to the nation's health, as it causes 450,000 infections, 15,000 deaths, and 1 billion dollars in excess healthcare costs per year in the United States. The status quo as it pertains to treating Cd infections (CDIs) is antibiotic use and, in recurrent cases, microbial replacement therapy (MRT). Antibiotics contribute to antibiotic resistance and recurrent CDIs. Although MRTs (e.g., defined consortia of microbes or fecal transplant) are increasingly accessible, the long-term sustainability and accessibility of these treatments remain to be determined. These limitations highlight the need for new and more precise strategies for coping with CDI. Because a disrupted (dysbiotic) gut microbiome is the primary risk factor for CDI, a better understanding of the interactions between Cd, the microbiome, and the host will aid development of such treatments. However, against the backdrop of the complex microbial and metabolic milieus of the gut, a major challenge is to identify the interactions that merit deeper investigation and eventual therapeutic targeting. Diet is emerging as a significant risk factor for CDI. In particular, dietary fiber can improve CDI in animal models and high fiber intake in humans is associated with lower odds of Cd colonization. However, there remains an unmet, critical need for a mechanistic understanding of how dietary fiber (and the related impacts on the microbiome) affect CDI. The overall objective of this grant application is to gain a better understanding of how butyrate impacts Cd. Butyrate is a prominent microbiome- host co-metabolite that is influenced by host dietary fiber intake and differentiates healthy from dysbiotic gut ecosystems. Based on our preliminary data and the work of others, our central hypothesis is that butyrate is a key determinant of Cd fitness and pathogenesis during CDI. In the proposed work, we will address our central hypothesis through three independent aims. We will use methods including bacterial cell culture, bacterial genetics, proteomics, metabolomics, transcriptomics, ribosome profiling, a variety of molecular biology techniques, and conventional/gnotobiotic murine models of CDI. Our study team is uniquely poised to use these methods to define mechanisms by which butyrate impacts Cd sporulation & toxin production/release and to determine the direct effects of butyrate on Cd fitness and pathogenesis in mice. The proposed work will therefore significantly advance our understanding of how butyrate impacts CDI. The work is aligned with our long-term goal to define key aspects of Cd biology and to develop new concepts and approaches for excluding Cd from the gut. Our results are expected to have an important positive impact, as they will be a foundation for developing targeted treatments distinct from antibiotics or MRT (e.g., dietary intervention, precision probiotics, or new Cd/microbiome-targeting drugs) to mitigate CDI in at-risk human populations.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY Non-typhoidal Salmonella enterica (NTS) is a leading cause of bacterial foodborne gastroenteritis and leading cause of death amongst foodborne pathogens. NTS elicit neutrophilic inflammation both during gut colonization and in systemic infection. Neutrophils produce toxic products to kill invading pathogens. One toxic product produced by activated neutrophils during severe bacterial infection is sulfite. Sulfites are reactive sulfur species that are toxic to all life forms. In addition to their presence during severe bacterial infection, sulfites are endogenously produced during metabolism of sulfated amino acids and are ingested in food products. Sulfites are also added to food products as antimicrobial agents. Therefore, enteric pathogens such as NTS must resist sulfite toxicity in several stages of infection. Our preliminary data link yeiH with sulfite stress resistance in Salmonella Typhimurium. We show a ∆yeiH mutant is defective for growth in sulfite stress conditions and yeiH expression is specifically activated by sulfite. yeiH encodes a highly conserved putative inner membrane protein with no documented function. The purpose of the proposed work is to establish the role of YeiH in sulfite stress resistance. We hypothesize that YeiH exports sulfites to allow Salmonella to resist neutrophil-derived sulfite stress during infection. We will test our hypothesis in two aims. In Aim 1, we will establish the role of yeiH in infection. We will use animal models of colitis and sepsis to establish whether yeiH is needed for Salmonella fitness during infection. Using a yeiH transcriptional reporter as a novel sulfite biosensor, we will determine the tissues in which yeiH is expressed to establish the spatial organization of sulfite stress during enteric and systemic salmonellosis. In Aim 2, we will determine how YeiH contributes to sulfite stress resistance. We will determine whether the proton motive force drives YeiH function and establish the amino acid residues important for YeiH role in sulfite stress resistance. We will also establish whether YeiH function is to export sulfite from the cell. YeiH orthologs are present in many bacteria, including in different pathogens with importance to human health. Successful completion of the proposed experiments will allow us to establish how YeiH contributes to Salmonella sulfite stress resistance in vitro and in vivo. This work will lead to future studies to define the mechanism of YeiH function and establish how sulfites contribute to human health and resistance to bacterial infections.

NSF Awards · FY 2026 · 2026-02

This award supports the Geometry Labs United (GLU) conference, to be held in Madison, WI, in June of 2026. The conference will bring together approximately 130 members of the 20 labs in the GLU network. The primary aim of the conference is to discuss the research produced by the labs, share expertise in activities developed at the labs, and discuss the creation of new labs with prospective network members. This will be the fourth GLU conference, following GLU 2015 at the University of Illinois Urbana-Champaign, GLU 2017 in University of Washington, and GLU 2020 held online by the George Mason University in collaboration with ICERM. The Geometry Labs United network brings together institutions in the United States, Canada, and Europe that share the vision of vertically-integrated research conducted by undergraduates, graduate students, and faculty, with extensive use of computer-based experimentation and visualization. Research projects at the labs, while often geometric in nature, encompass all fields of mathematics. The research component of the conference will bring together researchers---from undergraduate to faculty---to share their work in experimental mathematics. Expertise in relevant tools (e.g. 3D printing, cloud computing, quantum computing, AI) will be shared through formal talks and informal conversations. The conference website is at https://sites.google.com/view/geometrylabsunited2026/home 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.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY/ABSTRACT Clostridioides difficile is a diarrheal pathogen that causes significant human morbidity and mortality. The status quo as it pertains to treating C. difficile infections (CDIs) is antibiotic use and, in recurrent cases, microbiome restoration therapy (MRT). Antibiotics contribute to antibiotic resistance and recurrent CDIs. Although MRTs (e.g., defined consortia of microbes or fecal transplant) are increasingly accessible, the long-term sustainability and accessibility of these treatments remain to be determined. These limitations highlight the need for new and more precise strategies for coping with CDI. One framework for developing such strategies is to better understand key metabolic processes of C. difficile and use this understanding to develop ways to reduce its fitness and pathogenesis in the gastrointestinal (GI) tract. C. difficile is a cysteine auxotroph and the GI tract contains low levels of cysteine, highlighting gaps in our understanding of how C. difficile acquires this amino acid during infection. One possible source of cysteine for C. difficile during infection is glutathione (GSH). GSH is the most abundant low molecular weight thiol within mammalian cells, where it serves as an antioxidant. GSH is also produced, consumed, and sensed by phylogenetically diverse bacteria, where it can be used as a source of amino acids, nutritional sulfur, and as a signaling molecule to modulate gene expression. Our data indicate that C. difficile consumes GSH as a source of cysteine in vitro. Our data also suggest that GSH levels increase in the GI tracts of mice with CDI relative to uninfected mice and relative to mice colonized with avirulent C. difficile. Despite these observations, detailed knowledge of the C. difficile-, microbiome-, and host-based determinants of GSH levels in the GI tract under homeostasis and during CDI remain unclear. In the proposed work, we will use a mouse model of CDI to define how C. difficile-mediated inflammation impacts GSH concentrations in the distal GI tract. In addition, we will generate targeted mutations in C. difficile to disable its ability to metabolize GSH. These mutants will allow us to determine how C. difficile GSH utilization impacts CDI in mice. Upon successful completion of the proposed work, we will have generated foundational data on how C. difficile acquires and metabolizes GSH during murine CDI. This will build the foundation for future R01-funded work, which will provide deeper mechanistic insights into GSH acquisition and utilization by C. difficile during CDI. We anticipate that these insights will allow for the development of drugs to disable C. difficile GSH metabolism, probiotics that impact C. difficile's ability to acquire GSH, or diet-based strategies to alter available cysteine and GSH in the distal GI. The proposed work will therefore be an important foundation for developing new approaches to target C. difficile metabolism and to mitigate CDI in at-risk human populations.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY The mission of the American Medical Society for Sports Medicine (AMSSM) is to be the pre-eminent organization for primary care sports medicine in the United States. In the past six years, the AMSSM Collaborative Research Network (CRN) has developed and hosted three research summits to highlight research needs, best practices, and resources on pertinent topics in sports medicine to its membership. Tangible outcomes from these summits have included peer-reviewed manuscripts, national and international presentations on summit conclusions, and the creation of collaborative research groups to further research in these areas. In April 2026, the AMSSM CRN, housed at the University of Wisconsin-Madison, plans to host a research conference titled Orthobiologics for Sports Medicine Physicians: Bridging the Gaps. The use of orthobiologics treatments in the field of sports and exercise medicine (SEM) is a complex topic, and their use remains polarizing among sports medicine physicians. Many sports medicine physicians have adopted orthobiologics into their practice, while others remain on the fence regarding their clinical efficacy or are simply unsure of how to approach the often-complex process of adding orthobiologics to their clinical repertoire. Indeed, the evolving clinical hypotheses on which orthobiologics clinical studies are predicated, the inherent heterogeneity of conditions treated, and the sheer volume of published studies in this area in recent years make it, perhaps, one of the most difficult and nuanced areas of current practice in sports medicine. This research conference will be held as a pre-conference to the AMSSM’s Annual Meeting in Seattle, Washington on April 23rd and 24th, 2026. Before the conference, writing groups will work on a synthesis of current research and identify knowledge gaps within their topic areas for presentation at the research conference. Topic areas include platelet-rich plasma for tendinopathy, platelet-based therapies for muscle injuries, and cell-based therapies for osteoarthritis, all areas of high relevance to the clinical practice of sports medicine. The research conference itself will include several sessions, including basic science and translation talks, and allow for thoughtful interaction and open-ended discussion via a consensus-building process to identify future research priorities. The research conference aims to attract 300 multi-disciplinary individuals, and results will be disseminated through academic journals, websites, social media postings, and podcasts. After the conference, conference leaders will synthesize the consensus-building process research priority-setting results to finalize a consensus statement on AMSSM-identified research priorities in orthobiologics for the clinical practice of sports medicine. These research priorities will be essential for sports medicine physicians looking to provide clarity to health care providers and their patients on the appropriate use of orthobiologics.

NSF Awards · FY 2026 · 2026-02

The project investigates the cause of a recent increase in volcanic activity at the Laguna del Maule volcanic field, Chile, which has in the past produced voluminous and explosive volcanic eruptions.  Starting in September 2025, the ground surface has been rising ~4.5 cm per month, double the rate observed there over the last 15 years.  The number of earthquakes has also increased and appear clustered above or near a growing magma body.  This volcano has a series of 31 marked stations where gravity measurements have been repeatedly measured since their installation in 2013, with the most recent measurements taken in 2024.  Changes in the gravity measurements in this case are likely caused by addition of magma below the ground surface.  By repeating gravity measurements in 2026, the team can determine the amount of magma added in the last two years. The team will also deploy seismometers for two weeks to determine the precise location of the earthquakes, which likely occur at the edges of the growing magma body.  Together, these data will reveal if there was a recent influx of magma and if so, provide information on the size, shape, and chemistry of the growing magma body.  The team will evaluate the present volcanic hazard at the Laguna del Maule volcanic field.  Then, they and others can apply new insights to other similar volcanoes, including the Cascades volcanoes in the western United States. This team is investigating the cause of recent unrest at the Laguna del Maule volcanic field (LdMvf), which hosts extensive rhyolitic lava flows. Uplift rates of ~2.6 cm/month since 2007 are interpreted to be caused by addition of magma ~5 km below the volcanic field. Starting in September 2025, uplift rates have nearly doubled to ~4.5 cm/mo. Also, several swarms of seismic events have been detected, including some of the largest earthquakes recorded at LdMvf.  Together, these data suggest magma addition to the magma body beneath the lake.  A network of gravity stations designed to measure microgravity will be remeasured. Those results will be compared to the last measurements taken in January 2024. The gravity work will be complemented by a short (2 week) deployment of seismic nodes, installed at a subset of stations.  The seismic data will provide insight into the extent to which faults are accommodating this intrusion of magma and constrain near-surface velocity changes that will improve gravity modelling. Modelling will constrain the composition of the intruding magma, which impacts the projected eruption style. This work will improve understanding of the mechanisms that control magma emplacement, and their impacts on hazards, at silicic volcanoes on human timescales. 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 · 2026-02

This grant will provide partial travel support to about 10 U.S.-based students to attend the Human-Robot Interaction (HRI) Pioneers Workshop, to be held in March 2026 conjunction with the ACM/IEEE International Conference on Human-Robot Interaction (HRI 2026). HRI is a selective venue that bridges robotics, human factors, artificial intelligence, behavioral sciences, and related fields to advance knowledge around designing effective interactions with robots. The HRI Pioneers Workshop provides a forum for undergraduate and graduate students to present their work, learn about the current state of HRI, and network with one another and with select senior researchers in a relaxed and interactive setting associated with the conference. Workshop participants will discuss important issues and open challenges in the field, encouraging the formation of collaborative relationships across disciplines and geographic boundaries. Alumni from prior years of the workshop will be invited to participate in a forum with current attendees to further develop these professional relationships. The availability of travel funding will be widely advertised to bring in a large and pool of potential student awardees. Criteria for selection include having the need for funding, the timing in the student's career, the estimated benefit to the attendee and to the workshop as a whole, and the quality and fit of the application to conference topics. In alignment with the workshop's overall goal to bring together a variety of academic and industry researchers, the selection committee will also seek to fund students from a wide range of disciplinary, institutional, and topical backgrounds. Participation in the workshop will provide an opportunity for participants to increase their knowledge of the current state of the field of human-robot interaction and to encourage them to continue their career as HRI researchers in academia, government, or industry. 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.

NIH Research Projects · FY 2026 · 2026-02

ABSTRACT Human aging is accompanied by a loss of skeletal muscle mass (sarcopenia) that is vastly exceeded by the ability to generate power (dynapenia), and the problem is exacerbated by the increased fatigability (activity- induced reduction in power) when older adults perform dynamic exercise. This is an important health care problem because the impaired power generating capacity can result in limited mobility, increased risk of falling, and a reduced quality of life. Despite the clear clinical significance, the cellular and molecular mechanisms underlying the complex aging skeletal muscle phenotype are poorly understood. A key issue contributing to this problem is likely the divergent effects aging has on slow versus fast muscle fiber types. However, despite ~25 years of research, the extent that fiber size (atrophy) versus altered intrinsic contractile function are contributing to contractile dysfunction with aging remains unresolved, and the mechanisms for the divergent effects aging has on slow and fast fibers, particularly fiber power and size, are poorly understood. Thus, the overall objective of this proposal is to discover the molecular mechanisms that mediate fiber type-specific aging in males and females. Our central hypothesis is that the intrinsic contractile function of both fiber types is preserved with aging, and the selective atrophy of the fast fibers coupled with fiber type-specific metabolic changes drive the complex aging phenotype of sarcopenia, dynapenia and increased fatigability. The central hypothesis will be tested by pursuing three aims: (1) quantify proteome changes with fiber type-specific atrophy in older males and females, (2) determine the cross-bridge mechanisms for the fiber type-specific impairments in contractile function of older males and females, and (3) identify the fiber type-specific proteomic profiles that predict whole muscle dysfunction in older males and females. In aim 1, novel approaches for single fiber proteomics and 3D morphology will be performed on the same muscle fibers to reveal how the proteome changes with fiber size. In aim 2, single fiber contractile function will be paired with either 3D morphology or proteomics of the same fibers to reveal if the age-related loss of power is driven primarily by fiber size or altered cross-bridge mechanics and identify the key proteins contributing to age differences in fiber contractile function. In aim 3, we will use machine learning to determine how fiber type-specific single fiber proteomic profiles determine age-related whole muscle dysfunction. The rationale for this research is that measuring pairwise combinations of single muscle fiber 3D morphology, contractile function, and proteomes will reveal mechanisms of fiber type-specific aging. This approach is innovative, because it departs from the status quo by integrating novel analytical approaches by collecting fiber type-specific molecular data with gross biological measurements of single fiber and whole muscle function and morphology, which will likely allow us to answer long standing questions in the field. This contribution will be significant because it is expected to reveal novel therapeutic targets that can be manipulated to treat sarcopenia, dynapenia and fatigability to improve the quality of life in older males and females.

NIH Research Projects · FY 2026 · 2026-02

Project Summary/Abstract The complexity of the HIV-1 transcriptome has been progressively revealed throughout recent decades using increasingly advanced RNA sequencing technologies. However, knowledge of the RNA primary sequence alone has not been sufficient to determine the importance or function of each of the over 40 highly conserved HIV-1 splice variants, which code for nine known proteins and polyproteins. RNA-protein interactions are fundamental to RNA fate and function. From transcription to cellular localization to translation of the gene product, and many steps in between, proteins interact with RNA to regulate gene expression and, in the case of HIV-1, viral replication. Notwithstanding the high significance of these splice variants in the HIV-1 life cycle, technologies for interrogating the functions, interactions, and cellular localizations of individual splice variants are woefully lacking. We propose to develop and validate a suite of powerful new tools to interrogate the functions, interactions, and cellular localizations of individual splice variants of HIV-1. For Aim 1, we will develop sensitive and multiplexed assays (HyPR-MS) to elucidate the protein interactomes of up to 20 conserved HIV-1 mRNA splice variants and advance mechanistic studies of newly identified viral RNA regulatory co-factors. In Aim 2, we will determine which HIV-1 splice variants are most critical to HIV-1 replication using virological assays and measure single- cell viral RNA abundance and subcellular localization using a multiplexed branched DNA fluorescence in situ hybridization technique (SV-FISH). These powerful new tools and strategies will be used to elucidate previously unobtainable information about HIV- 1 replication. Once developed, these same novel technologies will comprise a powerful new toolset that can be applied to splice variant investigations in other viral and cellular systems.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY Neisseria gonorrhoeae releases large amounts of pro-inflammatory peptidoglycan and lipooligosaccharide during infection. The inflammatory response to these molecules in the human Fallopian tube causes the death and sloughing of the ciliated cells and scarring of the tissue, making it nearly impossible to move an egg down the oviduct. This tubal-factor infertility, together with chronic pelvic pain, and risk of ectopic pregnancy make up the severe sequelae of gonococcal infection. While the effects of gonococcal secreted products in Fallopian tube damage have been known for over forty years, the mechanisms involved have not been determined. In our recently-published RNA-sequencing study, we found that treatment of Fallopian tube tissue with gonococcal supernatants or N. gonorrhoeae infection resulted in a strong inflammatory cytokine response including increased IL-17C, CCL4, IL-1b, and TNF-a. Transcripts for cell-cell junction proteins were decreased, and transcripts for matrix metalloproteinases were increased, suggesting mechanisms for ciliated cell sloughing. Furthermore, the decreases in cell-cell junction protein transcripts were not seen if the gonococcal soluble products did not contain GlcNAc-anhydro-MurNAc-tripeptide (TriDAP), the NOD1-agonist form of peptidoglycan fragments. This proposal will determine mechanisms involved in ciliated cell sloughing and tissue damage using human Fallopian tube tissue in organ culture. We propose a model of tissue damage in gonococcal pelvic inflammatory disease in which peptidoglycan fragments and lipooligosaccharide induce inflammatory cytokine responses and cause increases in matrix metalloproteinases and decreases in cell junction proteins allowing detachment of ciliated cells. Programmed cell death, possibly pyroptosis, kills the ciliated cells, and they slough from the epithelium. We will test this model by performing a comprehensive analysis of ciliated cell sloughing using high-resolution live cell imaging as well as super-resolution microscopy to examine matrix metalloproteinases, cell junctions and cell junction proteins, cell morphological changes, and markers of cell death pathways following gonococcal infection or treatment with gonococcal soluble products. We will use spatial transcriptomics to determine how cellular responses in ciliated Fallopian tube cells differ from those of secretory cells, examining different time points in infection or following treatments with gonococcal products as the ciliated cells die and are lost from the epithelium. These studies will reveal why ciliated cells are destroyed in various bacterial infections, and this knowledge will be useful for designing treatments for gonococcal pelvic inflammatory disease.

NSF Awards · FY 2026 · 2026-01

Computational imaging is a rapidly growing area that seeks to enhance the capabilities of imaging instruments by viewing imaging as a computational problem. There are currently two distinct approaches for designing computational imaging methods: model-based and learning-based. Model-based methods leverage analytical signal properties and often come with theoretical guarantees and insights. Learning-based methods leverage data-driven representations for best empirical performance through training on large datasets. This project reconciles both viewpoints by formulating a unifying framework that provides a learning-based extension to the classical imaging theory. The results will have broad use and transformative effects across a wide range of scientific, engineering, and biomedical applications, such as 3D live-cell imaging, structural analysis of complex materials, early diagnosis of Alzheimer disease, and improved patient comfort in magnetic resonance imaging. The project will also create unique opportunities for increasing research participation in computational imaging, improving engineering education, and engaging the academic community. The current theory of computational imaging is inadequate for analyzing recent learning algorithms. Current algorithms are also impractical for processing 3D (space), 4D (space-time), or 5D (space-time-spectrum) datasets containing billions of variables. The framework developed in this project addresses this gap by integrating physical and learned models for fast processing of massive datasets. The framework also offers new theoretical insights and rigorous performance guarantees when combined with mathematical conditions on the underlying models. The framework will enable high-resolution computational imaging in emerging applications, such as dynamic and quantitative magnetic resonance imaging, x-ray microscopy, and cryogenic electron microscopy. While this project explicitly seeks impact on computational imaging, it has the potential to transform broader signal and information processing via generalizations to audio and speech, communication theory, and graph structured signals. 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 · 2026-01

Modern imaging technologies are central to progress in science, medicine, and engineering. Yet, many advanced imaging systems operate under physical or resource limitations that make it difficult to directly acquire high-quality images. Computational imaging addresses these challenges by using algorithms to reconstruct images from incomplete or indirect measurements. In recent years, deep learning has enabled new capabilities in computational imaging, but current methods assume that the training and test data share the same conditions. This assumption often does not hold in real-world settings. This project addresses this critical gap by developing new methods to ensure that deep-learning models for image reconstruction remain reliable and accurate even when the data conditions shift. The outcomes of this research will have broad use and transformative effects across a wide range of scientific, engineering, and biomedical applications, where robust image reconstruction is essential. Broader-impact activities include the organization of special sessions, workshops, and journal issues for the computational-imaging community, dissemination via open-source code, and curriculum development at both institutions. This project focuses on score-based models — a class of deep generative models that solve imaging problems by learning the score function of the image distribution. The central goal is to develop a unified mathematical framework for analyzing and improving the robustness of these models under distribution shifts between training and test data. The project introduces Robust Score-based Inversion (RoSI) as a foundation for (i) quantifying the extent of such shifts using the model's own score function; (ii) characterizing the effect of shifts on reconstruction and sampling performance; and (iii) enabling principled adaptation of models to new imaging settings. The research will be validated in real-world imaging systems, including lensless cameras, computational microscopes, and magnetic resonance imaging, providing both theoretical insights and practical tools for reliable computational imaging. The project will also promote education and engagement in the areas of computational imaging and machine learning. 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 · 2026-01

Intensive agricultural production is necessary to feed a growing world population. Unfortunately, modern agriculture can degrade soil ecosystems in ways that compromise the other services we depend on soils to provide for us. Millions of acres of farmland have been retired from production in the Midwestern US in the last few decades, and this land provides an opportunity to restore soil services on a large scale. However, the legacy of agriculture may prevent the successful reestablishment of healthy soil ecosystems, especially when native tree species rely on specialized microbial associations to thrive. This project aims to fill gaps in our knowledge of how soil ecosystems recover, or not, when lands are retired form agriculture, or when trees are planted directly into agricultural systems (agroforestry). It will also develop new methods for enhancing the success of tree planting into formerly agricultural land. This project is a collaboration between researchers at the University of Wisconsin-Madison and the Savanna Institute, a non-profit dedicated to improving and promoting agroforestry practices in the Midwestern US. Societies depend on landscapes that serve multiple purposes, including food production and ecosystem services like carbon sequestration. However, long term studies find that despite regenerative practices, soil carbon is not effectively sequestered in annual row crop settings. Moreover, high input agriculture leaves soil legacies that can inhibit the establishment of plant communities and soil functions like carbon sequestration. This may be especially likely when incorporating trees reliant on unique plant-microbial interactions. This project will investigate the development of soil ecosystems after agricultural abandonment or the establishment of agroforestry practices, and test how coupled soil carbon and nitrogen cycles respond to variation in soil community states induced by different times since agricultural abandonment and restoration practices. Finally, it will develop restoration strategies that promote soil community structure and function recovery through alteration of tree nursery conditions. This project seeks to transform our understanding of how soil microbial communities and food webs drive carbon and nitrogen cycling by taking advantage of the disruptions caused by agricultural legacies and recovery following land restoration or agroforestry. This project will directly inform conservation practice by setting quantifiable targets for soil biodiversity and ecosystem function in restoration or agroforestry settings and by piloting new tree propagation methods to enhance beneficial microbial associations. 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.

NIH Research Projects · FY 2025 · 2026-01

Project Summary Falls are the second leading cause of unintentional injury deaths worldwide and are driven in part by vestibular ataxia, a major health issue characterized by dizziness, vertigo, and difficulty maintaining an upright posture while walking. Balance issues can arise from dysfunction of vestibular nuclei (VN), structures in the brainstem that process sensations of motion arising during walking, and treatment for dysfunctional balance is hindered by limited understanding of brainstem motion processing. During walking and other forms of locomotion, animals must adapt their movements to an unpredictable world, but sensing while moving faces the problem of disentangling sensation generated by self-motion (reafference) from that generated externally (exafference). Appropriately processing reafference may be essential for maintaining balance during locomotion, enhancing sensitivity to unpredictable motion and suppressing inappropriate responses. Isolating and responding to exafference involves making a prediction of the predictable element, the reafference, computed based on an internal representation of the intended movement called ‘corollary discharge’ (CD). CD has been shown to cancel reafferent signals in the VN during voluntary neck movements, but is locomotion processed similarly? A likely source of CD to VN during locomotion is the cerebellum, which innervates the VN, because damage to this pathway can cause ataxia. However, predicting and disentangling locomotor motion feedback is challenging given the heterogeneity of VN neurons coupled with the technical challenge of manipulating motion sensation during locomotion. Here, we mitigate these challenges by leveraging the simple locomotion of larval zebrafish. These animals possess the key neural architecture of the VN and cerebellum, and their approachable behavior and optical transparency affords neural recordings during locomotion (swimming) with precise control over motion sensation. We have developed a behavioral assay suitable for intravital imaging that reliably evokes voluntary swimming with predictable motion sensation. Our general approach combines imaging neural activity while manipulating motion sensation in anatomically and genetically defined cell populations, in order to determine how the VN and cerebellum interact to process motion sensation and incorporate information about ongoing locomotion. This research will take place at the University of Wisconsin-Madison, home to leading experts in the fields of kinesiology, sensorimotor integration, and zebrafish neural function and development. I will have ample opportunities to train through research, coursework, seminars, and collaborations. I will also travel to national conferences and intensive training courses to grow as a scientist, communicator, and future mentor. Together, these efforts will help define how animals use expectation to refine motion processing during locomotion, advancing understanding of the basic neurobiology of balance that may ultimately inform human walking balance. I will perform this research while developing my career as a vestibular neuroscientist.

NIH Research Projects · FY 2025 · 2025-12

PROJECT SUMMARY Visual tasks, like reading print or recognizing faces, often require detailed spatial information collected under changing lighting conditions. In the retina, as light intensity varies so do the gain and kinetics of neural responses—a process called adaptation that prevents saturation and supports a consistent perception of contrast. A significant gap in knowledge is how light adaptation functions in the fovea—the central most region of retina responsible for high-acuity vision. Retinal circuit adaptation relies on signal pooling, and therefore adaptation may vary between foveal and peripheral regions that differ in convergence. Additionally, cone photoreceptors in peripheral primate retina are known to be asymmetric in their sensitivity to light increments vs decrements. Therefore, circuit adaptation may differ in ON and OFF visual pathways. The objective of this project is to use distinct primate retinal circuits—foveal vs peripheral and ON vs OFF—to determine how circuits with differing signal to noise ratios modulate gain and kinetics across light conditions. Aim 1 will determine the impact of convergence on properties of retinal circuit adaptation (gain, kinetics, noise, and time course) in the primate foveal vs peripheral midget and parasol pathways, as well as the contribution of synaptic inhibition as a potential mechanism for circuit adaptation to luminance. Aim 2 will determine how asymmetries inherited from cone photoreceptors shape the functional properties of adaptation in the primate ON vs OFF peripheral midget pathway. Given the importance of the fovea for our everyday vision, this work will bridge a gap in our knowledge of how foveal circuits adapt to changes in contrast over varying background luminance, critical for the function of high-acuity vision. These results will positively impact the pursuit towards prosthetic retinal implants that can recapitulate properties of foveal circuits by providing a template for function in diverse retinal circuits. The training plan described in this proposal is designed to enable me to develop the skills necessary to reach my career goal of an independent investigator. By following this plan with the guidance of my sponsor and co-sponsor, I will continue to learn new electrophysiology techniques to build a strong foundation in retinal circuit research. I will develop my writing, communication, teaching, mentoring, networking, and scientific outreach skills. This research will take place at the University of Wisconsin-Madison where the strong intellectual environment and availability of primate tissue from the Wisconsin National Primate Research Center will be leveraged.

NSF Awards · FY 2025 · 2025-12

Tree species can occur across wide ranges that vary greatly in temperature and precipitation. How can a single tree species tolerate such a wide range of conditions? It is increasingly recognized that microbial associates can affect how plants tolerate stressful conditions, which may contribute to their broad geographic ranges. However, very little is known about the mechanisms by which microbes change how trees grow and function under stress. This project seeks to increase the understanding of why trees grow better in certain locations than others, and whether microbial associations from different locations alter plant responses to the environment. Experiments will test whether microbes sourced from colder, hotter, and/or drier locations can promote tree seedling growth and survival under those conditions. Additional measurements will determine the source of this enhanced tolerance through shifts in plant growth, physiological function, and by turning on or off key plant genes during development. This project will directly apply this knowledge to reforestation efforts by working with tree nurseries to promote microbial associations and test the impact on tree seedling survival in restoration plantings. Additionally, this project will continue to support a volunteer led tree root sampling program to map the distribution of tree-fungal associations across the eastern United States. Prior results indicate that tree seedlings inoculated with microbial communities sourced from dry, hot, or cold locations improved seedling survival under those respective stresses. However, we have little understanding of the physiological, morphological, or transcriptional mechanisms underlying these effects. This project seeks to integrate an understanding of broad biogeographic patterns in species interactions with a detailed understanding of plant physiological responses and underlying gene regulatory mechanisms. Microbial mediation of plant abiotic stress tolerance has been documented in a wide variety of systems, but often with little or no understanding of how the microbial interaction changes plant phenotypes or gene expression to result in enhanced stress tolerance. This project will experimentally manipulate soil microbial inocula and environmental conditions, then measure morphological, physiological, and gene regulatory responses in tree seedlings. Additionally, this project will test whether microbial stress mediation occurs in real-world situations by working with tree nurseries to promote fungal associations, then testing the impact on tree seedling growth, survival, and physiological function in outplanting conditions. Finally, this project will continue a volunteer-led project to map the geographic distribution of root-associated fungi across eastern temperate forests. By interrogating plant phenotypic and transcriptomic responses to geographically varying microbial communities in an ecologically informed framework, this project will ensure that this understanding directly connects to our ability to understand and predict natural patterns. 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 · 2025-11

This project will investigate questions in arithmetic statistics, an area of mathematics concerned with determining the "typical" properties of objects in number theory. In practice, many questions in arithmetic statistics can be fruitfully understood by studying how the underlying objects decompose into simpler objects. Much of the research in this project will be aimed at studying these kinds of decompositions and, particularly, the process of assembling properties of these simpler objects to provide answers to complex questions. The PI will also continue his established record of undergraduate and graduate mentorship. He will also organize special sessions and workshops aimed at bringing together early career researchers in both analytic and algebraic number theory. More technically, this project will focus on the development of uniform bounds (both upper and lower) on number fields and class groups. It will consider the applications of these bounds to central problems in arithmetic statistics, like Malle's conjecture on the number of fields with a given Galois group and the ell-torsion conjecture on the size of the class group. Another focus will be the development of zero density estimates for Artin L-functions. These density estimates will play a role in the proofs of the uniform bounds and will have other applications, for example, to irreducibility in certain families of random polynomials, which the PI will explore. 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 · 2025-11

Robotic systems that must operate in hazardous or remote environments, such as future extraterrestrial exploration vehicles, autonomous construction equipment, and search-and-rescue robots, cannot be designed safely and efficiently by trial and error. This project creates open instructional materials and trains thousands of learners in physics-based "Digital Twin" technologies, enabling engineers, scientists, and students to design and test robots through computer simulation before hardware is built. By lowering cost and risk, simulation accelerates innovation and discovery, strengthens U.S. leadership in advanced manufacturing and space technology, and expands economic opportunity. A key feature of the project is its anyone-anywhere-anytime approach to learning and training, that hones the modeling and simulation skills of participants ranging from California State University students to experts at NASA, Department of Energy, and other government agencies. The project's long-term impact is a workforce fluent in robotics simulation, Digital Twin technologies, and high-performance computing that gains hands-on experience with the open-source Chrono simulator, positioning these professionals to advance national prosperity and public welfare. This project executes a CyberTraining plan focused on enabling the use of Digital Twins in Robotics through two coordinated activities: (i) creating instructional material, and (ii) delivering a CyberTraining (CT) program. For (i), this project provides the opportunity to carry out an instructional-material tokenization process and flipping of three Chrono-enabled or Chrono-related classes; prepare Jupyter notebooks for self-paced training; and produce new widely available Chrono models and documentation that encourage CI tool use through smoother onboarding. For (ii), this team will facilitate CyberTraining via both synchronous and asynchronous instructional approaches. These "create content and execute training" activities will anchor a technical effort that has five CyberTraining components. The first CT component expands participation in computational science through a collaboration between project investigators from the University of Wisconsin–Madison (UW–Madison) and the California State University (CSU) System. Every 12 months, a cohort of students from four CSU campuses — Los Angeles, Northridge, Fullerton, and Pomona — will be trained in using simulation in lunar exploration robotics. These activities include a visit to NASA's Jet Propulsion Laboratory for a firsthand look at rover operations; online training on simulation use in robotics; and a two-week Summer School at UW–Madison that concludes with a robotics team competition. The second CT component will train practitioners in the use of Chrono via tutorials held in conjunction with an annual consortium meeting that fosters outreach to industry. The project also includes revamping three UW–Madison courses that underpin the concept of Digital Twins in robotics. The fourth CT component provides asynchronous training to thousands of anonymous Chrono users. This training draws on materials uploaded to the NSF's ACCESS ecosystem and the Project Chrono website and is further supported by a large language model expert agent piloted by this group. Lastly, the project engages students participating in NASA's Lunar Autonomy Challenge. Together, these activities create a scalable, reproducible pipeline that couples flipped-classroom pedagogy, cloud-ready software containers, and software-in-the-loop testbeds. Expected outcomes of this project include a curated library of Digital Twin models, freely available training artifacts hosted on the NSF's ACCESS ecosystem, and a measurable increase in CI-savvy robotics researchers capable of executing large-scale simulation studies on high-performance computers. 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 project will develop tools to enable genetic manipulation of bacteria to facilitate an array of biotechnology applications. The tools build on established methods to influence the production of protein from individual bacterial genes, including scaling up to impact all the genes in a bacterium within a single test tube. Furthermore, advances to the technology will expand to enable more precise alterations to turn genes “down” or “up,” decreasing or increasing production of proteins encoded by those genes on a broad scale. Previously, such approaches were limited to a small number of targeted bacterial strains. This work seeks to expand the biotechnological reach of available bacteria with a generalized approach that will be tested in a group of marine bacteria called vibrios. Vibrios are important in our food supply, are prominent in causing animal and human disease, and are widely studied to understand animal-host interactions and basic microbiology. As such, they represent a valuable test bed in which to develop and deploy the new technology and assemble resources for laboratories to apply that technology in their own research and in classrooms worldwide. Sharing of the resources developed, including laboratory protocols, teaching materials, computer code, databases of DNA sequences to target bacterial strains, and the resulting bacterial strains themselves, will facilitate broadscale adoption and provide important tools toward growing our bioeconomy. The biotechnology tools developed will be made readily available to the research community, and the proof-of-concept experiments proposed here will be developed as part of a teaching curriculum that can be deployed in courses and workshops. Targeted gene perturbations using CRISPR technology have caused a paradigm shift in eukaryotic functional genomics, but comparable approaches for bacteria have lagged with a reliance on species and/or strain-specific genetic tools and a focus on laboratory strains. Thus, it is essential that bacteriologists extend their studies beyond lab strains and develop tools that can be readily deployed into environmental isolates. This project has two parallel goals: (1) to expand established tools for genome-wide gene knockdowns called CRISPR interference (CRISPRi), and (2) to develop novel bacterial CRISPR technologies for gene overexpression and gene interaction studies. This study focuses on the diverse bacterial group Vibrionaceae, which includes over 100 species that inhabit marine waters and can have significant effects on nutrient cycling and ecosystem health. Many bacterial species in the group cause vibriosis disease, leading to widespread mortality in marine organisms and impacting global aquaculture, disrupting the human food chain, and increasing risks to seafood consumption. The variety in this group is highlighted by the increasing application of Vibrio natriegens in biotechnology applications. Furthermore, Vibrio species serve as some of the most widely-studied model systems for understanding host-microbe interactions, in the context of both mutualism (e.g., V. fischeri) and pathogenesis (e.g., V. campbellii in marine animals, V. cholerae in humans). 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 NSF ECR Building Capacity of STEM Education Research (BCSER) program contributes to the NSF mission by building the US 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 how members of STEM-related teams build relationships through transfer of knowledge and practices from various professional development experiences. The findings of this project can impact the training and development of STEM teams in school settings, academia and industry This BCSER IID project will allow the 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 assist the PI to develop new expertise in qualitative research methods. The PI will work with a mentoring team with expertise in research teams, and qualitative methods. More specifically the PI will engage in training on qualitative interviewing, build knowledge on relations theory and learning transfer through reading and discussions and enroll in courses on qualitative methodology. The project will investigate how individuals within teams utilize prior professional development experiences to promote effective teamwork and how team members serve as boundary spanners in building team relationships. The findings will be shared through the facilitation of professional development workshops with STEM teams, presentations of various STEM-related conferences across multiple disciplines and higher education media outlets. The success of this project will be assessed through structured interactions with an external advisory board for formative and summative feedback. 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

Robotic-assisted surgery cyberinfrastructure combines advanced data analytics and decision making in the cloud with interconnected Internet of Things-based systems that has brought opportunities for advanced diagnostics, patient monitoring, and personalized medicine. However, the increased data and resource sharing enabled by these devices and artificial intelligence in the robotic-assisted surgery infrastructure has increased vulnerabilities and opportunities for cyberattacks. In particular, data-integrity attacks that interfere with critical real-time data can potentially disrupt surgical performance and compromise patient safety. Existing studies on cyberinfrastructure security in these environments do not fully consider users’ cybersecurity awareness and knowledge or evaluate training and mitigation for cyberattacks. This project aims to create a Human-Centered Cybersecurity in Robotic Surgery (HCCRS) framework by integrating data analytics and healthcare human factors to design new human-centered algorithms to detect, identify, and mitigate cyberattacks in the robotic surgery cyberinfrastructure. The HCCRS framework will lead to sustained impact that can be translated to other digital health technologies and generalized to the National Initiative for Cybersecurity Education Cybersecurity Workforce Framework. This work addresses the critical gap in cybersecurity for surgical care. Specifically, the following research aims are studied: (1) identify robotic surgery cybersecurity perspectives of stakeholders through qualitative research approaches; (2) design a data-driven human-centered attack detection and identification framework using Graphical Neural Networks-based impact quantification and multimodal high-dimensional data fusion techniques; and (3) develop and validate robotic surgery cybersecurity training materials and an cyberattack intervention system. This work enhances the performance and usability of current and future heterogenous robotic surgery cyberinfrastructures. 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

Changes in climate are significantly altering the freshwater habitats of inland lakes and rivers. Despite concern over the impacts of a changing climate on aquatic ecosystems, some lakes and rivers are holding up surprisingly well. The aquatic ecosystems of northern Mongolia represent one such “bright spot.” While air temperatures in the region have warmed almost three times faster than the global average, coldwater fish populations in northern Mongolia appear to be surprisingly robust. This project builds on nearly 20 years of ecological research, monitoring, and sample collections to understand the factors underlying the resilience of Mongolia’s lakes, rivers, and fish populations. Each summer, four undergraduate and four graduate students travel with American and Mongolian scientists to Lake Hovsgol and the Eg River in Mongolia to engage in research for six weeks. Here, they conduct field ecology research projects in two-person grad-undergrad teams. Student participants hone their research project proposals and outreach plans through a pre-trip distributed seminar and present results after the expedition at an online virtual symposium. Student research teams investigate three broad hypotheses about the factors contributing to resilience of aquatic ecosystems. First, via “behavioral thermoregulation,” fish may be able to select microhabitats where temperatures remain more favorable to growth and survival. Second, intra-specific variation in characteristics such as temperature tolerance may allow populations to persist in warming waters. Third, changing ecological interactions, including predator-prey and host-parasite relationships, may either offset or exacerbate the direct effects of warming. Experiments and observational studies test these hypotheses using cutting-edge tools such as DNA metabarcoding to investigate diets and microbiomes of endangered fishes, electronic tags to track fish movements, and data logging sensors to understand variation in the abiotic environment. The Intellectual Merit of this project is centered on improving our understanding of the effects of a changing climate on natural ecosystems. The Broader Impacts include improved management approaches for U.S. fisheries impacted by changes in climate and the training of 24 U.S. students in aquatic ecology research methods in an international setting. 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

Non-technical Description: The mass production of integrated circuits (commonly known as ‘microchips’ or simply ‘chips’) is a key driver for modern computational advances. Chip manufacturing requires a process called photolithography to template the intricate patterns of electronic components. This process uses patterns of light to selectively pattern a material known as a photoresist. New extreme ultraviolet (EUV) based lithography methods are poised to enable more powerful chips than ever before by packing higher volumes of smaller electronic components onto a single chip, making new photoresists essential to reaching the desired small features sizes. This Designing Materials to Revolutionize Our Future (DMREF) project combines chemistry, processing, and computation to design new photoresists to enable high-volume EUV lithography for chip manufacturing. This will be achieved by understanding how the local molecular structure of polymer-based photoresists defines the patterning at nanoscale dimensions, and how this translates to manufacturing outcomes. This interdisciplinary effort will bring together scientists and engineers from academia and the Air Force Research Lab with expertise in synthesizing materials, characterizing their physical properties, modeling their behavior with simulations, and predicting new materials with improved properties using AI. The new materials and patterning methodologies developed in this project will broadly benefit the US by enabling advanced manufacturing of next-generation computer chips with applications ranging from personal electronics and health care monitoring to supercomputers and generative AI. This research will further be combined with K-12 outreach and student training to prepare the next generation STEM workforce. Technical Description: This project will integrate combined expertise in polymer chemistry, physics, computation, and advanced manufacturing into a closed loop process to enable the design and implementation of crosslinkable polymeric photoresists for EUV lithography. Theory, molecular simulation, and data science will be combined with polymer chemistry and advanced metrology to understand how the sequence-specific molecular structure of copolymers translates to local patterning heterogeneity. Additionally, this effort will be combined with data science-enabled proxy measurements to rapidly and efficiently traverse an enormous chemical space for materials discovery. The ultimate goal of this work is to develop candidate chemistries that produce patterns with appropriate dimensions and fidelity under industrially-relevant EUV exposures. More broadly, workflows to aid the discovery-to-translation timeline of EUV lithography resists will be developed. Additionally, this research will be integrated with education and workforce development efforts to train students who can effectively communicate across the materials development continuum and contribute to the semiconductor industry. 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

Non-native species invasions are causing worldwide ecosystem degradation and economic loss, with average global economic costs exceeding 27 billion dollars per year over the past five decades. More urgently, both the number of non-native species and their impacts are projected to increase over the coming decades. For example, approximately an additional 1,500 non-native species are likely to establish in North America by 2050. Furthermore, the economic costs of biological invasions are predicted to increase threefold per decade. Government agencies, conservation organizations, and private citizens have spent significant resources to mitigate the impacts of species invasions, but the outcomes are far from satisfactory. One main reason is that we still do not have a holistic and predictive understanding of species invasion across scales. This project will compile an open-access, cross-scale database of species invasion centered around the datasets collected by the National Ecological Observatory Network (NEON). This database will be analyzed using advanced statistical methods to test theory on the relative roles propagule pressure, abiotic variables, and biotic variables on invasions for multiple taxonomic groups (plants, birds, and beetles) across spatial scales. Model results will be disseminated by building an online interactive application that can dynamically present and forecast risks of invaders at all NEON sites. This application will be updated automatically with new data to provide real-time management recommendations. One postdoctoral researcher and two undergraduate students will be trained in macrosystem biology, statistical, and data science skills during the project. The goal of this project is to test the relative importance of propagule pressure, abiotic variables (e.g., climate, land-use history), and biotic variables (e.g., species interactions) in driving species invasions across spatial scales in the context of community assembly. To achieve this goal, this project will improve the ability of phylogenetic generalized linear mixed model (PGLMM) to work with large datasets and then apply it to the integrated database of species invasions based on NEON to investigate patterns and mechanisms of biological invasions of different taxonomic groups across spatial scales. This project will address the following questions: 1) Do functional traits of non-native species interact with abiotic variables to determine their distributions? 2) Do biotic interactions between non-native and native species in the recipient communities affect the distribution of non-native species? 3) What is the relative importance of propagule pressure, abiotic variables, and biotic variables in determining the distribution of non-native species from local to continental scales? This project is jointly funded by the Division of Environmental Biology/Macrosystem Biology and NEON Enabled Science 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.