University Of Washington

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Transplant is a valuable treatment option for many people with kidney failure, but in order to receive a kidney, patients must first be referred to a transplant center and complete a process of physical and psychosocial evaluation. Nephrologists and dialysis organizations are increasingly incentivized to refer greater numbers of patients with kidney failure to transplant centers in an effort to improve equitable access to this treatment. Such efforts can also be expected to increase the number and clinical complexity of patients engaging in the evaluation process. However, many patients will not ultimately receive a kidney and the evaluation process itself can be demanding, opaque, and lengthy and can take an emotional and psychosocial toll for patients and families. As more patients are drawn into this care process, multiple national stakeholder groups have emphasized the importance of minimizing burdens and improving patient experience. However, efforts to improve this patient experience are hampered by a lack of validated measures. In recent years, leading professional societies, regulators, and patient communities have called for the development of patient-reported outcome measures of the pre-transplant process. The aim of the proposed work is to develop and establish the content validity of a Kidney Transplant Evaluation Patient Reported Experience Measure (KTE-PREM). In Phase 1 (concept elicitation), we will perform a structured literature review, analyze existing qualitative interview transcripts, and conduct focus groups with patients who were referred to a transplant center, their family members, and clinicians who care for these patients (including primary nephrologists, social workers, and transplant team members). Patients will be recruited from Northwest Kidney Centers (a large non-profit dialysis organization based in Washington state which typically refers patients to three regional transplant centers) and the University of Washington. These sequential steps will result in a comprehensive set of concepts potentially relevant to a KTE-PREM. In Phase 2 (concept prioritization), we will identify items most relevant to patients to be included in a KTE-PREM by conducting a national survey among patients receiving care at two large non-profit dialysis organizations (Northwest Kidney Centers and Dialysis Clinic, Inc) who were referred to a kidney transplant center. In Phase 3 (instrument construction and refinement), we will design a draft KTE-PREM and iteratively refine the instrument through cognitive interviews with a local group of patients who were referred to a kidney transplant center. The proposed work directly extends from Dr. Butler’s recent NIH/NIDDK supported research (K23DK129777), which has identified a need and opportunities to improve person centricity of the kidney transplant evaluation process. Following development of the KTE-PREM, additional funding will be sought for validation. We anticipate that this validated instrument will have applications in clinical, research, and policy work intended to measure and improve patient experience in the kidney transplant evaluation.

NIH Research Projects · FY 2025 · 2025-09

Project Summary: The overall premise of this research is that copper (Cu) status is a previously under-recognized and potentially modifiable risk factor in cirrhosis, the most advanced stage of chronic liver disease. In the United States, chronic liver disease affects 4.5 million people and accounts for over 41,000 deaths per year. Cirrhosis requires high rates of healthcare utilization compared to other diseases with an annual cost of approximately $21 billion. Malnutrition is one of the few modifiable factors that have been associated with poor prognosis. Current guidelines in nutritional intervention focus on protein and calorie intake, and give little consideration to trace elements, which have wide ranging physiological effects. Cu deficiency in the absence of liver disease compromises Cu dependent enzyme functions which can cause iron overload, tissue fibrosis and susceptibility to infections – pathologies also observed in cirrhosis. Our recent large cohort study identified Cu deficient cirrhosis patients, as defined by low serum Cu concentrations, had higher infection rates and a 3.4-fold increased risk of death compared to patients with normal Cu levels. Our preliminary findings and the well- established importance of Cu in human health raise several important questions: Does reduced circulating Cu, the standard definition of Cu deficiency in the general population, similarly reflect a deficiency state in cirrhosis? Is the higher infection and mortality risk observed among patients with low serum Cu mediated by Cu dependent enzymes and immune cells? Is reduced circulating Cu a secondary response in cirrhosis, therefore should be “left alone,” or should patients receive Cu supplementation in order to improve functional Cu store and its associated physiological functions? In an attempt to answer these questions, we designed a pilot randomized, placebo-controlled, crossover trial to determine the effect of Cu supplementation on Cu dependent biochemical changes, patient safety and patient reported outcomes.

NIH Research Projects · FY 2025 · 2025-09

This proposal for an NIDDK Research Education Program has an overarching goal to further the development of individuals into future surgeon-scientists engaged in urology research careers. The planned Program reflects the commitment of the University of Washington Department of Urology to the current and future research workforce needs in Urology. This Program will capitalize on unparalleled resources including a committed Department, a robust research environment, dedicated and experienced faculty, data and research support resources, and a structured curriculum. These resources include research mentors who are practicing urologists, near-peer mentors who are current residents and fellows to act as career development mentors, and a biostatistician to facilitate maintaining the timeline for the Program by working with the participants on research study analyses. This Program leverages the success of the Department’s past mentored research experiences to refine and expand the scope and breadth of research opportunities in areas of urologic disease from earliest prenatal development to the commonest aging associated problems. The objective of this application is to train medical students in benign clinical and health services research, seek out residency positions with dedicated research experiences, all with the long-term goal to support the career development of individuals into urology research careers and to create novel research solutions to benign urological conditions with high public health impact. To achieve this objective, program participants will pursue the following Specific Aims: 1) To gain exposure to methodologies for conducting contemporary clinical and health services research in benign urologic diseases; 2) To conduct a hypothesis-driven research project through which they will develop sophisticated skills in applying clinical and health services research methods; 3) To gain skills in analysis of study data and presentation of research results through manuscripts, scientific presentations, and patient-centered research dissemination strategies; and 4) To prepare trainees for careers in academic urology through dedicated mentorship that includes career and leadership development. Supported by the mentoring and resources of this program, the overarching goal of this NIDDK Research Education Program is to ignite these participants to initiate and retain an excitement for urological research and carry it with them throughout their entire careers.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Bacterial biofilms are microbial communities with aggregates of bacterial cells enclosed in an extracellular matrix. Biofilms present a significant healthcare challenge because of their prevalence in infectious diseases and resistance against treatment. Second messengers, which are critical intracellular signaling molecules that are produced in response to environmental stimuli, play a key role in biofilms. The regulation of these signaling pathways is a fundamental question in microbiology and biofilm research. In particular, the second messenger molecules cyclic diguanylate monophosphate (c-di-GMP) and cyclic adenosine monophosphate (cAMP) play critical roles in biofilm formation in many bacterial species. The opportunistic pathogen Pseudomonas aeruginosa is a model species for studying biofilms. My postdoctoral work has developed a tricolor reporter system to simultaneously study c-di-GMP and cAMP signaling at the single cell level in P. aeruginosa. Using this system, I found that c-di-GMP and cAMP signaling are activated under distinct surface conditions during the initial stages of biofilm formation, when bacteria attach and respond to a surface. This proposal aims to elucidate the molecular coordination between c-di-GMP and cAMP signaling and their roles in later stages of biofilm formation. Aim 1 will characterize how cAMP influences the enzymatic activity of c-di-GMP cyclase and phosphodiesterase, identify the enzyme targeted by cAMP, and investigate the role of an unknown protein PA3413. Aim 2 will examine how c-di-GMP impacts the three key proteins controlling cAMP signaling and employ an unbiased screen to identify additional genetic factors involved. Aim 3 will elucidate the coordination of c-di- GMP and cAMP signaling during biofilm maturation and dispersion, particularly under host-related environmental conditions. These aims will reveal the regulatory mechanisms between these two critical second messengers, deepen our understanding of phenotypic heterogeneity within biofilm communities, and are expected to facilitate future research into the broader regulatory networks of second messengers. This proposal also includes a career development plan for me to successfully transition to an independent faculty position. I will leverage the guidance of highly experienced mentor and co-mentors during the K99 mentored phase, gaining training in 1) second messenger signaling, 2) biofilm cultivation and dispersion, and 3) live cell confocal microscopy. I will also enhance my skills in mentoring, lab management, and scientific communication. In transition to the independent R00 phase, I will apply these skills and use the data generated from the proposed studies to position myself for a successful R01 grant prior to the end of this award.

NSF Awards · FY 2025 · 2025-09

This award supports participation in the "Seattle Noncommutative Algebra Conference" that will take place December 15-19, 2025 at the University of Washington in Seattle. Noncommutative algebra is the study of algebraic structures in which the commutative law of multiplication does not hold, that is, multiplying x by y may yield a different result than multiplying y by x. This framework is particularly effective in the study of symmetry, quantum phenomena, geometry and more. The conference will bring together researchers from across these areas, along with graduate students and early-career researchers, to survey current progress, highlight open problems, and foster new collaborations and directions for future research. Activities will include expository and research lectures, student presentations, problem sessions, and discussions on computational techniques. The conference aims to stimulate progress on key structural questions in the field and build bridges between a broad range of noncommutative perspectives across mathematics. In more detail, the five-day conference will focus on several active research programs in noncommutative algebra, with connections to representation theory, algebraic geometry, Poisson algebra and Poisson geometry, quantum groups, category theory, topology, and combinatorics. A central theme is noncommutative projective geometry, with particular emphasis on two major classification problems: (i) the classification of Artin-Schelter regular algebras of global dimension four, which geometrically correspond to three-dimensional quantum projective spaces; and (ii) Artin's conjecture on division algebras of transcendence degree two, which seeks a birational classification of noncommutative projective surfaces. Additional topics include Calabi-Yau algebras, noncommutative invariant theory, and emerging methods in computational algebra. The conference website is https://sites.google.com/uw.edu/seattlencalgebra2025. 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 project develops tools to read expanded genetic alphabets that contain bases other than A, T, G, and C, and studies how natural biological systems interact with these unnatural DNA letters. This research contributes to transformative applications in nucleic acid biotechnology, and has the potential to improve diagnostic assays, lead to the discovery of novel therapeutics, and enhance biomanufacturing techniques. The project integrates these research activities with robust educational objectives: preparing a globally competitive workforce through workshops for industry professionals, fostering public engagement with hands-on community activities, and developing online resources for data science education. Graduate and undergraduate students participating in the project will gain valuable skills and mentorship experience, contributing to STEM workforce development. This research addresses key challenges in expanded genetic alphabets, focusing on three objectives. First, it aims to improve generalizability (and accuracy) of next generation sequencing for unnatural base pairs through deep learning. Second, it develops single-context sequencing models that enable high accuracy measurements of polymerase replication fidelity for unnatural bases. With this new methodology, the project measures polymerases replication fidelity of various polymerase for these unnatural bases in various model in vitro systems - such as PCR and LAMP. Lastly, the project investigates the biocompatibility of unnatural base pairs in a microbial host by examining metabolic processes, replication fidelity, error repair pathways, and host responses. These approaches promise to bridge key technological gaps and knowledge gaps in expanded genetic alphabets, helping bridge this area of research towards transformative applications in biotechnology. 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 · 2025-09

Project Summary Alzheimer’s disease (AD) is a prevalent chronic neurodegenerative disorder, projected to affect between 11 to 16 million individuals in the US by 2050. Neurodegeneration in AD initiates with the formation of amyloid beta (A) plaques decades before observable symptoms. This latent, pre-clinical phase represents a crucial "window of opportunity" when new A lowering therapies can slow the disease progression and mitigate its clinical impacts. However, existing biomarkers of preclinical AD, such as cerebrospinal fluid (CSF), plasma and positron- emission tomography (PET), face significant limitations. This underscores an urgent need for readily available and noninvasive biomarkers capable of detecting AD at its latent, preclinical, stage when disease-modifying therapies are most effective. Resting state functional MRI (rs-fMRI) is gaining recognition for its potential to provide non- invasive biomarkers for AD pathology, particularly through the assessment of alterations in functional connectivity (FC) dynamics and networks related to A deposition. However, current computational approaches for analyzing rs-FC networks and their dynamics have notable limitations, including the use of ad-hoc or black-box analytical methods, over looking heterogeneity in rs-fMRI data and dynamic FC across subjects and populations, and limited sample sizes, impacting the applicability, generalizability, and replicability of existing biomarkers and their ability to reveal underlying disease mechanisms. This project aims to rectify the deficiencies in current computational methods and is grounded in the fundamental hypothesis that improved biomarkers for early detection of AD and related dementias (ADRD) can be obtained by leveraging the dynamics of rs-fMRI data and FC, while accounting for heterogeneity across subjects and studies. To achieve this goal, the first aim develops a new model to comprehensively capture the dynamics of FC and offer robust biomarkers for AD pathology by assessing the accumulation of 𝐴. To account for individual level heterogeneity, the second aim develops a multivariate dynamic models featuring both local and global structures to incorporate heterogeneous brain connectivity among different brain states in different individuals. The third aim then develops effective techniques for detecting alterations in brain connectivity networks, while accounting for subject-level heterogeneity through random effects, helping uncover underlying processes of ADRD initiation and progression. Finally, to address the limited sample sizes in individual studies, the fourth aim proposes an innovative transfer learning framework that leverages the inherent similarities among multiple datasets to improve the reliability of connectome-based ADRD biomarkers. Upon evaluation and validation, the above methods will be implemented as efficient, open-source software tools in form of R-packages and python libraries, accompanied with extensive documentations, illustrative examples, and interactive visualization capabilities, to maximize the adoption of the proposed methods by the broader community.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT K99 training: The goal of the proposed K99/R00 Pathway to Independence Award is to provide Dr. Jonas Dora with training needed to launch his career as an independent scientist. Following his PhD in cognitive psychology, Dr. Dora has already started to make important contributions to the field of alcohol use research as a postdoctoral research fellow in the Department of Psychology at the University of Washington. The proposed K99 training period builds on Dr. Dora’s PhD background and his current training in the study of alcohol use in natural environments. The K99 phase will provide a period of intensive training in the combined study of alcohol use with experimental, ecological momentary assessment, and computational approaches, and will position Dr. Dora to make substantial contributions to the field of alcohol research over the course of his career. Dr. Dora will learn from the proposed mentor (Dr. Kevin King), local collaborators (Drs. William George, Mary Larimer) and external collaborators (Drs. Matt Field, James Murphy, Katie Witkiewitz), who are leading experts in the field of alcohol use research using both experimental and ecologically valid approaches, as well as the advanced computational modeling of behavioral and subjective data. In addition, Dr. Dora will attend courses, scientific conferences, and workshops to meet his training objectives. The University of Washington is a world-class research institution that provides an optimal environment, the necessary resources, and a stimulating intellectual space to facilitate successful completion of this project. K99 research: Together with his mentor and collaborators, Dr. Dora will conduct controlled experiments in a simulated bar environment as well as studies in people’s natural drinking environment to test the idea that negative and positive reinforcement of alcohol can be observed when heavy drinkers with and without symptoms of alcohol use disorder (AUD) make decisions between alcohol and substance-free reinforcers. R00 research: Dr. Dora will translate the K99 research using a task involving hypothetical choices between alcohol and substance-free reinforcers into an ecologically valid test of the hypothesis that positive and negative affect differentially motivate real-world value-based decisions to consume alcohol (vs regulate affect via alternative emotion regulation strategies) in heavy drinkers with/without symptoms of AUD in everyday life. Significance: By combining methods from cognitive psychology and alcohol use research, this research will provide a novel test of the idea that alcohol use is reinforcing in the face of positive and negative emotions, and in that way will advance NIAAA’s strategic aim to identify mechanisms that contribute to AUD. By studying alcohol use as a form of value-based decision-making, the insights from this project will suggest new possibilities to target people’s emotions in the prevention and treatment of alcohol use disorder.

NSF Awards · FY 2025 · 2025-09

Polymer foams are essential in industries like packaging, electronics, and healthcare due to their low cost, lightweight nature, insulating properties, and energy absorption. However, current foaming methods offer limited flexibility for material customization, rarely introduce new functions to meet specific application needs, and often lack environmental sustainability. This Faculty Early Career Development (CAREER) grant supports fundamental research to establish an innovative manufacturing method for on-demand foaming of polymers and composites. The project aims to advance scientific understanding of selective foaming, which could enable applications such as miniaturized sensors and wearable electronics, benefiting US industries ranging from aerospace to medical devices. The project also looks to lay the groundwork for a sustainable manufacturing approach, promoting the use of recyclable materials in advanced technologies like flexible electronics. By improving material performance and advancing sustainable production methods, the research can contribute to national prosperity and environmental sustainability. Additionally, the project integrates research and education to cultivate a skilled US workforce. Targeted outreach efforts leverage the multidisciplinary nature of this research to inspire students and encourage them to pursue studies and careers in advanced materials and manufacturing, building a more innovative workforce for the future. This CAREER project looks to build understanding of solid-state foaming and microstructure engineering in thermoplastic composites through laser-induced foaming. This direct-foam-writing technique enables selective surface engineering and controlled microstructure modification within polymer composites to create locally tailored structural, thermal, and electrical properties. The mechanisms of cell nucleation and growth and the effects of filler properties will be systematically studied to establish relationships between composite properties, process parameters, and cell microstructures. Mechanical, thermal, and electrical properties of the microcellular composites will be experimentally characterized, while physics-based models will be developed to predict the effective properties of the foamed regions. These findings look to elucidate process-structure-performance relationships, resulting in an efficient, scalable, high-resolution fabrication process for devices with spatially tuned properties. This program also integrates research and education to train new workforce members in manufacturing practices that emphasize recyclable materials. A new course will be developed to equip students with expertise in sustainable electronics, multifunctional polymer composites, advanced image processing, and laser-matter interactions. Outreach activities will engage K-12 students in communities across Washington state, sparking early interest in STEM and demonstrating feasible pathways to the University of Washington, empowering them to become future leaders in manufacturing innovation. 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 · 2025-09

Project Summary This project will establish a Type 1 Diabetes (T1D) Recruitment Site within the Kidney Precision Medicine Project (KPMP) at the University of Washington. We bring substantial experience conducting kidney biopsies among people with T1D, having already completed >130 biopsies as part of multiple successful T1D studies. Building on established infrastructure for patient-oriented research in T1D, we will obtain research kidney biopsies and comprehensive phenotyping from individuals with T1D who have or are at risk of chronic kidney disease (CKD). Our specific aims are to: (1) safely and ethically obtain research kidney biopsies from adults and adolescents living with T1D who have or are at risk of CKD through robust community engagement and standardized protocols; (2) robustly phenotype the clinical presentation through advanced imaging (multiparametric kidney MRI, retinal imaging) and vascular assessment; and (3) actively contribute to enhanced understanding of CKD pathophysiology through collaborative participation in KPMP team science. We will integrate expertise from two premier research centers - the University of Washington Medicine Diabetes Institute (UWMDI) and Kidney Research Institute (KRI) - to enroll 15-20 participants annually. Starting in Year 2, pending careful ethical consideration with patients and the broader KPMP consortium, we propose expanding enrollment to include adolescents ≥16 years. Together, this work will advance understanding of kidney disease in T1D while maintaining the highest standards of patient safety and ethical conduct. By integrating with KPMP’s existing infrastructure and protocols, our site will contribute to the development of precise, mechanistic definitions of kidney disease in T1D, ultimately enabling more targeted diagnosis and treatment.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT Kidney diseases, including chronic kidney disease (CKD), acute kidney injury, and glomerulonephritis, impact nearly 850 million people worldwide, leading to significant morbidity, mortality, and rising healthcare costs. While spatial transcriptomics has offered valuable insights by mapping gene expression within specific kidney niches, a comprehensive understanding of kidney disease requires spatial multiomics approaches that can detect both RNA and protein at single-cell or subcellular resolution. However, current spatial omics technologies struggle to analyze the kidney's complex structure and diverse cell types, and integrating RNA and protein assays at high resolution remains both technically challenging and costly. The overall goal of this project is to address these limitations by optimizing Pixel-seqV2, a submicron-resolution spatial transcriptomics assay, and developing ProteoPixel-seq for integrated co-profiling of transcriptomes and proteomes in human kidney disease. Building on Pixel-seqV1, which uses 1-µm-resolution "polony gels", as capture DNA arrays for spatial RNA sequencing, we will enhance its resolution to 0.6 µm through a scalable "polony gel stamping" method, reducing the array fabrication cost by over 100-fold. In Aim 1, Pixel-seqV2 will be optimized for spatial transcriptomics of the kidney at single-cell resolution. Sub-Aim 1A focuses on integrating 0.6-µm-resolution polony gels and optimizing assay conditions to improve RNA capture sensitivity and spatial resolution, while Sub-Aim 1B involves applying the optimized assay to both mouse and human kidney samples, refining cell segmentation algorithms to accurately delineate complex cell boundaries and detect rare, pathologically relevant cell populations. In Aim 2, ProteoPixel- seq will be developed for integrated spatial co-profiling of transcriptomes and proteomes. Sub-Aim 2A aims to expand Pixel-seqV2 with high-plex proteomic analysis using DNA-tagged antibodies, optimizing tissue assay conditions for simultaneous RNA and protein detection. In Sub-Aim 2B, we will apply ProteoPixel-seq to CKD patient biopsy samples, focusing on interactions between kidney stroma and infiltrating immune cells to reveal molecular pathways involved in disease progression and identify potential therapeutic targets. This project will yield catalytic tools for spatial multiomics tissue mapping, offering the first demonstration of integrated spatial transcriptomics and proteomics in kidney disease, significantly enhancing our understanding of kidney pathology and supporting the development of novel diagnostics and therapeutics.

NIH Research Projects · FY 2025 · 2025-09

Abstract: Over 30% of patients who develop acute hypoxemic respiratory failure (AHRF) and require ventilator support will die in the hospital. Treatment for AHRF remains extremely limited, as nearly every clinical trial in the last 20 years has failed to demonstrate improvements in mortality. A major obstacle for these trials is that most patients improve with existing care; this dramatically limits our ability to detect benefits for the remaining patients with persistent HRF, who are the ones most at-risk for death and in-need of new therapies. Currently, there are no accurate ways to distinguish patients with persistent HRF early, when trial enrollment and intervention is critical. The goal of this project is to develop robust models to identify patients at high risk for persistent HRF early, by using innovative opportunities in data science and machine learning to capture complex data sources (text and imaging) and accurately predict risk. The project will also allow Dr. Neha Sathe, an early career investigator and Pulmonary & Critical Care physician, to gain expertise in state-of-the- art methods to develop, evaluate, and improve multisource prediction models in real-world settings. In Aim 1, Dr. Sathe will develop and validate models that identify patients at high risk for persistent HRF, by integrating retrospective data from electronic health records, chest radiograph reports, and banked blood at two medical centers. In Aim 2, she will evaluate and explain these models in a new prospective cohort, to develop strategies and infrastructure for deploying and monitoring these models in future work. In Aim 3, she will develop novel methods to analyze sources of data with high potential to improve prediction of persistent HRF (chest radiograph images and tracheal aspirates, which are readily collected but under-leveraged). This work will yield models that improve the ability of trials to identify effective therapeutics for high-risk patients, minimize exposure to potentially costly or toxic therapeutics in patients likely to resolve, and provide significant insights to advance precision medicine. This work will also yield research infrastructure that can be adapted to rigorously develop and test predictive models for other clinical problems in critical care. To achieve these aims, Dr. Sathe will have complementary mentorship across the thriving ecosystem at the University of Washington for translational AHRF research, medical data science, and informatics. Altogether, this proposal aligns with NIH strategic objectives to leverage new opportunities in data science, and will support Dr. Sathe's long-term goal of understanding how to best use these opportunities to individualize and improve the care of patients with AHRF.

NSF Awards · FY 2025 · 2025-09

When the ocean loses heat to the atmosphere, a small but important difference in temperature occurs between the ocean surface and the water about 1 mm below the surface. This temperature difference of 0.2 to 0.5 °C plays a significant role in how much carbon dioxide is absorbed by the ocean. The only way to measure the temperature right at the surface, dubbed the “skin” temperature, is with an infrared radiometer that measures the ocean surface radiation. Because the ocean surface reflects some infrared radiation, a correction for the sky radiation reflected from the ocean surface into the sensor is required. Standard infrared measurements of the sea surface use a wavelength band for which the atmosphere is transparent in the infrared. Using this waveband, an additional measurement of the downwelling radiation from the sky is necessary because of the large difference of sky temperature between clear and cloudy conditions. This research implements a simplified technique using a special infrared wavelength band that significantly reduces the difference of sky temperature between clear and cloudy conditions and thus eliminates the need to make the sky measurement. The waveband is in a semi-transparent region, which results in the sky radiance coming from the water vapor in the atmosphere from 3 km above the sensor. The awardees have shown that the sky radiance in this band can be modeled using the air temperature and relative humidity in the vicinity of the sensor. The result is that a sky radiance measurement is not necessary. This also reduces the complexity of the calibration method by using one internal reference target rather than two. These simplifications make possible routine measurements of infrared sea surface temperatures from buoys and uncrewed surface vehicles. An early career scientist and an undergraduate student will be actively involved in research and gain hands-on experience through mentorship programs . Over the past five years, the Principal Investigator (PI) has developed an instrument called IRISS-OPT (InfraRed Instrument for Sea Surface temperature-Optimal Band) for measuring ocean surface skin temperature. IRISS-OPT combines a simplified one-point in situ calibration with the so-called optimal band technique, which eliminates the need for a sky radiance measurement. IRISS has demonstrated an accuracy comparable to the proven instrument known as ROSR (Remote Ocean Surface Radiometer) from a research vessel. Modeled profiles of air temperature and water vapor are used to replace the sky radiance measurement. The combination of the simplified calibration and elimination of the sky measurement using IRISS-OPT now makes it practical for deployment on Uncrewed Surface Vehicles (USVs) and buoys. This research will transition the current design to a stand-alone version with internal power and recording and optional external power and output dubbed IRISS-USV. Two existing IRISS-OPT units will be upgraded for use on buoys. Two new units with a reduced form factor to fit on the saildrone Uncrewed Surface Vehicles will be designed and fabricated. The units will be validated at sea on a research vessel and buoys. The research to develop a stand-alone version of the IRISS sensor to measure the ocean surface skin temperature is timely, innovative, and transformative. The combined simplification of a single ambient temperature calibration and no sky measurement will significantly increase the practicality and accessibility of ocean surface skin temperature measurements. The activity is transformative because it will, for the first time, make it possible to measure skin temperature from USVs and buoys with an accuracy comparable to proven ship-based instruments. 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 · 2025-08

Project Summary: This pre-doctoral Pharmacological Sciences Training Program (PSTP) is a cross-disciplinary program that represents a merger of research training opportunities in the Schools of Medicine (Pharmacology) and Pharmacy (Medicinal Chemistry and Pharmaceutics) at the University of Washington. The mission of the PSTP is to train PhD-level scientists with broad expertise that spans the spectrum of pharmacological sciences, who will become leaders in the varied specialties of pharmaceutical sciences while acknowledging the value of diverse ideas and methods. The rationale for this program is that there is an endless need for improved medications, a basic understanding of disease mechanisms, expert analyses of pharmaceutical and clinical data, and scientific leaders in these areas of research. This focus distinguishes training provided by the PSTP from other pre-doctoral training grants available at UW. The primary objective of the PSTP is to develop scientists, equipped with the necessary background and training in the application of modern tools of research and instrumental techniques, to undertake and direct fundamental research related to drug action, metabolism, and pharmacokinetics. Trainees follow tracks that emphasize training in four broadly defined areas: (I) cellular and molecular pharmacology, (II) drug metabolism and toxicity, (III) drug pharmacokinetics, disposition, and delivery (IV) biological structure and drug design, which exist in the Departments of Pharmacology, Medicinal Chemistry, and Pharmaceutics. Didactic components involve individualized, highly multidisciplinary programs of coursework and seminars that are centered on the pharmacological and chemical sciences. Non-didactic training activities include a PSTP-specific journal club that includes sessions devoted to training in entrepreneurship, biotechnology career seminars, grant writing, formal presentations, and synergistic activities in training in rigor and reproducibility with other training programs. Career development activities include 'career' days that bring scientists from varied 'nontraditional careers' to speak with trainees, one-on-one industry mentors from Pharma and Biotech, and industry internships. The program brings together 34 well-funded faculty members whose research emphasizes training in mechanisms and regulation of cell signaling, neuropharmacology, structural analysis of pharmacologically relevant protein-ligand interactions, mechanistic and bio-analytical aspects of drug metabolism and toxicology, pharmacogenetics, and pharmacokinetics/dynamics. Underrepresented and disadvantaged students are actively recruited through several activities. In this competitive application to continue the PSTP at UW, support is requested for 14 pre-doctoral trainees per year, which will be split between two cohorts of 7 trainees in the 2nd and 3rd year of graduate training. The selection of trainees will be on a competitive basis from the pool of students in years 1-3 while prioritizing candidates from underrepresented backgrounds.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Wildfires are an emergent environmental health threat in the U.S. as climate change contributes to increased wildfire activity and severity. Wildfire smoke represents a growing contribution to overall fine particulate matter (PM2.5), with distinct physicochemical properties that may lead to higher toxicity. Ambient PM2.5 is recognized to adversely impact airway health, particularly among children. However, research on the early life respiratory impacts of wildfire-specific PM2.5 is limited and predominantly focused on postnatal short-term exposure and acute health effects. The potential impacts of prenatal exposure to wildfire smoke PM2.5 on early life airway health remain largely unknown. In fact, there are currently no published studies of prenatal wildfire smoke exposure and children’s airway health in prospective U.S. cohorts. The proposed Aims will evaluate associations between prenatal wildfire-specific PM2.5 exposure and airway outcomes in children under 24 months of age in the nationwide cohorts of the Environmental influences on Child Health Outcomes (ECHO) Program (N~10,000). Aim 1 will evaluate risk of airway symptoms (wheezing and asthma-related symptoms) and hospitalization (bronchiolitis and other acute respiratory infection) associated with average smoke PM2.5 and days with smoke PM2.5 during pregnancy. Aim 2 will explore the role of wildfire smoke exposure intensity, duration, and timing during pregnancy by evaluating how risk may vary in association with “smoke days” of increasing intensity and “smoke waves” of increasing duration and intensity. Aim 2 will also evaluate potential critical windows of exposure during different stages of fetal lung development. Aim 3 will identify vulnerable sub-populations with disproportionate risk of airway outcomes by exploring effect modification by fetal sex, geographic region, and neighborhood poverty rate. This research will be among the first to evaluate associations between wildfire smoke exposure and child airway health in the U.S., leveraging a geographically and socioeconomically diverse study population. The proposal directly supports the mission of the National Institute of Environmental Health Sciences to advance environmental health science, identify individual susceptibility, and conduct translational research to promote environmental justice.

NIH Research Projects · FY 2025 · 2025-08

ABSTRACT Therapy for tuberculosis (TB) is an enigma of ineffectiveness. Despite prolonged treatment times, about 5% of TB patients endure poor outcomes, including treatment failure or relapse. Implicated in these failures is the presence of drug-tolerant Mycobacterium tuberculosis (Mtb) subpopulations, also known as "persisters". In an effort to eliminate these bacilli, we developed a drug screening assay targeting Mtb persister cells that survive high concentrations of two front-line anti-TB drugs, isoniazid (INH) and rifampicin (RIF). We found that netupitant (NTP), an FDA-approved oral antiemetic drug with a good safety profile, prevented the regrowth of INH/RIF persisters. We then showed that NTP enhanced the bactericidal activity of a broad spectrum of anti- TB drugs and had excellent activity in other models of Mtb bacteriostasis. Here we seek to assess the potential of NTP for TB drug development. We will adopt molecular genetic and biochemical strategies to define the mechanism of NTP action and resistance on persister bacilli. We will also test the ability of NTP to improve outcomes in a mouse model of TB treatment and relapse. Altogether this study will assess the potential for advancing NTP as a novel anti-persister agent, and enhance our understanding of Mtb persister biology, furthering the important goal of reducing TB treatment duration and improving outcomes.

NIH Research Projects · FY 2025 · 2025-08

Enter the text here that is the new abstract information for your application. International and Kenyan guidelines recommend TB preventive therapy (TPT) for people with HIV (PWH) and other people at high risk for TB, including close contacts of people with TB. Despite the evidence for reduced morbidity and mortality for people with HIV (PWH) who receive TPT, and guidelines recommending use, there remains a substantial gap between people recommended to receive and people who actually receive and complete a course of TPT. The 2022 WHO Global TB Report highlighted the growing gap in access and provision of TPT, which has been aggravated by the COVID-19 pandemic. Bridging this gap is a Kenyan and global priority. With the recent availability and evidence for newer, shorter regimens of TPT, a transformation of HIV care delivery models (in part forced by the COVID-19 pandemic) and evolving national guidelines for TPT, it is increasingly urgent to explore new person-friendly models of TPT delivery to inform programmatic guidance that results in greater uptake, adherence, and completion of TPT. HIV care transformed to adopt “differentiated service delivery” (DSD) models, which encourage community-delivered care, infrequent clinic/facility visits, multi- month dispensing, limited laboratory monitoring, and task-shifted treatment models to deliver comprehensive HIV care to stable adults in community settings. These successful models for differentiated HIV care delivery may be able to be adapted to include TPT. The availability of safe, effective, short-course TPT (i.e. 3HP, 3HR) with limited monitoring requirements suggests that similar community-based and multi-month dispensing models may be adapted to scale essential TPT to populations who most need it, including PWH, young child contacts, and all household contacts of people with TB. We will explore two approaches of adapting HIV differentiated services to TB prevention. We hypothesize that people who receive differentiated TPT delivery have higher rates of completion of a course of TPT than people who receive standard-of-care clinic-based TPT. We will 1) conduct a randomized controlled trial of DSD care (multi-month dispensing) vs. clinic standard-of-care TPT delivery in two priority populations for TPT in Kenya: household contacts of people with TB and PWH, 2) investigate the impact of DSD TPT on household and community TB transmission with follow-up testing and mathematical modeling, and 3) examine preferences, barriers and facilitators of TPT completion and TPT implementation using qualitative research. Together, this research will establish the foundation for implementation studies of optimized patient and community-friendly, differentiated TPT delivery approaches to increase TPT uptake and completion in Kenya and ultimately decrease morbidity, transmission, and mortality from TB.

NIH Research Projects · FY 2026 · 2025-08

Project Summary Age-related vocal atrophy (ARVA) affects a substantial portion of the population. ARVA impairs voice, swallowing, and communication, and is associated with social isolation, depression, and reduced quality of life. Vocal fold muscles are thin, bowed, with an incomplete closure during voicing. The underlying reason individuals experience ARVA is not well understood, and current treatments are often ineffective. Moreover, the diagnosis of ARVA is largely subjective and shows overlap with Alzheimer’s disease-related vocal atrophy. Motor evoked response studies are considered the gold-standard test to diagnose many neuromuscular disorders. This electrophysiologic study produces a compound motor action potential (CMAP), which is a summation of muscle fiber action potentials upon electrical stimulation of the motor nerve. The CMAP assesses the integrity of the nerve, neuromuscular junction, and muscle. The candidate has previously used the CMAP to quantify the degree of injury to the recurrent laryngeal nerve (RLN), which is the primary motor nerve to the larynx, in an animal model. The CMAP has been shown to detect acute changes in laryngeal innervation, measure conduction time changes, and quantify the degree of recovery after injury. The candidate has developed a reliable method to perform laryngeal evoked response studies in an aging rat model and human subjects. Pilot data have led to the central hypothesis that there is progressive desynchronization of efferent nerve-muscle signal in the aging larynx. The overall goal of this proposal is to quantify the neuromuscular changes in the aging larynx. The laryngeal evoked response study is the primary outcome measure and will be performed in a rat model (Aim 1) and in human subjects (Aim 2). The rationale for this proposal is that measuring neuromuscular changes in the aging larynx can lead to targeted treatments for this condition. This proposal combines an animal model and human subjects. While the two aims are not dependent on the other, the animal and human studies help to inform one another. The candidate’s primary mentor is David Marcinek, PhD, and he investigates aging muscle physiology and mitochondrial energetics. Jay Rubinstein, MD, PhD and Randal Paniello, MD, PhD are both co-mentors for this proposal. Both Dr. Rubinstein and Dr. Paniello are surgeon-scientists with expertise in computational neurophysiology and laryngeal injury and recovery, respectively. All three mentors have successfully mentored post-doctoral researchers and physician-scientists in career development programs. Local coursework and training programs in neuroscience, cellular biology of aging, instrumental measures of voice production, and biostatistics will allow for the candidate’s ongoing career development. This proposal will provide a strong foundation for independent investigations testing treatments for ARVA.

NSF Awards · FY 2025 · 2025-08

This award supports research aimed at uncovering the fundamental laws of nature by studying the Higgs boson and searching for new particles at the Large Hadron Collider (LHC) at CERN. By looking for unique signals in the ATLAS experiment's detector, and improving the precision with which we measure current known particles, this work seeks to answer deep questions about the origins of mass, dark matter, and the imbalance between matter and antimatter in the universe. This award will support the training of undergraduate and graduate students as well as post-doctoral scholars. This award will further the computing tools that the field of high energy physics uses for physics analysis and high speed detection of interesting physics. The University of Washington team will analyze data from LHC Run-3 and prepare for the upcoming High-Luminosity LHC. The research focuses on precision measurements of Higgs boson properties, including the self-coupling, and on searches for new physics using novel techniques such as machine-learning-enhanced reconstruction of long-lived particles, and searches for mono-jet signatures. Contributions also include development of upgraded detector components and improvements to simulation and analysis software. A collaborative effort with Tel Aviv University will integrate machine learning into the real-time Level-1 trigger system, boosting sensitivity to unconventional signatures. Together, these activities enhance ATLAS's discovery potential while advancing detector and computing technologies essential for the future of high-energy physics. 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 · 2025-08

Cardiac sarcoidosis (CS) is both under- and over-diagnosed. While vigilance has increased, diagnosis of isolated CS (ICS) remains challenging as detecting granulomatous inflammation on endomyocardial biopsy (EMB) is low yield. Thus, ICS is often presumed based on positron emission tomography (PET), the use of which has been proliferating. Thus, in an attempt not to under-diagnose CS, we are: 1) mis-diagnosing patients with “ICS” who actually have genetic CMP (36% in our prior work), with major clinical implications including unnecessary immunosuppression and failure to screen family members 2) identifying a growing group of “idiopathic 18FDG-avidity” patients” (64%) who have neither CS nor genetic CMP in whom identifying mechanism of 18FDG-avidity will guide future therapeutic options In this “bedside to bench” translational proposal, we perform “deep phenotyping” with genetic testing, PET imaging, metabolomic studies, voltage-guided EMB (with advanced inflammation histology methods) to: 1) help clinicians decide in which patients to order genetic testing and PET scans 2) develop minimally invasive diagnostic tests to determine mechanism of 18FDG-avidity and therapeutic options in patients with “idiopathic” or genetically-driven 18FDG-avidity In Aim 1, a total 200 patients will systematically undergo PET and genetic testing to help determine revalence and predictors of true CS, genetic CMP and “idiopathic 18FDG avidity”, and we will develop a prediction model to guide clinicians when to order genetic testing and PET scans. In Aim 2.1, we will metabolically phenotype these patients by simultaneously sampling radial artery and coronary sinus blood and using mass spectrometry to quantify myocardial fuel use, testing our hypothesis that the 18FDG-avidity in genetic CMP and idiopathic 18FDG-avid patients is due to a “metabolic switch” from fatty acid (normal) to glucose metabolism, and not due to inflammatory cell infiltrate. We will also measure and correlate inflammatory cytokines and oxygen consumption rate and extracellular acidification rate with metabolic data to help develop a “non-invasive signature” of true inflammation versus metabolic switch. To test the inflammatory counter-hypothesis, in Aim 2.2 we will process EMBs of “idiopathic 18FDG-avidity” patients and positive (true CS) and negative (18FDG-negative) controls using multi-spectral immunostaining, spatial transcriptomics, and imaging cytometry, which historically differentiate CS from its mimicking conditions. In Aim 3, cardiomyopathy mouse models will be utilized on our 18FDG-PET scan protocol to allow us to further study this phenomenon with even greater anatomic detail and control than in humans, and eventually to allow testing of novel therapies for this condition. In addition to providing predictive tools and novel diagnostic tests, elucidating the mechanism of 18FDG-avidity will enable future animal and human studies of immunosuppression and/or metabolic therapies for this growing group of patients and their families.

NSF Awards · FY 2025 · 2025-08

The 90,000 different local governments in the USA provide essential services and protections for the American people, including running schools, libraries, and public parks, and delivering front-line services during emergencies. While governments strive for efficient use of time and resources, due to the variety of size, structure, and complexity of local governments, it is currently prohibitively difficult to collect data and study these functions comprehensively. As a result, much of the research into the effectiveness of service delivery focuses on institutions at the federal or state level. This project will improve the capacity for studying local governments service delivery by providing new datasets and tools that make it possible to do comprehensive, comparative research at scale. Doing so will empower local governments with new research at the intersection of public policy, civic engagement, and artificial intelligence. This proposal builds upon the team's current open-source testbed. The long-term vision for the testbed is to facilitate rigorous experimentation through the robust, secure, and safe deployments of AI. To achieve this vision the proposed planning grant will carry out four activities: 1. Prototype safely integrating AI in the current testbed; 2. Convene government staff and researchers across a variety of computational fields to build a research agenda; 3. Govern robust AI deployments to operate safely and manage risk; and, 4. Validate the ability of the prototypes to answer research questions. Collectively, these four activities will lay the foundation for a long-horizon project with the potential to catalyze the study of local government through robust AI. The existing testbed that this project builds on is an open-source software platform that provides federated search and retrieval of data about city councils in multiple major US cities. The project will build upon the current data retrieval and processing capabilities of this testbed by integrating novel AI prototypes - using techniques from machine learning to improve interaction with testbed data, and to produce valuable datasets for research and policymaking. 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 nature of dark matter is one of the biggest mysteries in fundamental physics. Observations from astronomers indicate that a large part of the universe is made up of unknown particles that mainly interact through gravity. Understanding what dark matter really is could have significant effects on fields like cosmology, astrophysics, and particle physics. One promising candidate for dark matter is called the axion. The axion is a theoretical particle that comes from some advanced ideas beyond the Standard Model of particle physics. These ideas aim to solve certain problems in a field known as quantum chromodynamics (QCD). Interestingly, axions might help explain not only the presence of dark matter but also why neutrons do not have a measurable electric dipole moment, which is a puzzling observation in physics. Axions may exist across a broad range of masses, which correspond to specific frequencies. The Axion Dark Matter eXperiment (ADMX) has ruled out key theoretical benchmarks around 1 GHz. Above frequencies of approximately 2 GHz, corresponding to axion masses in the range of several to tens of micro-electronvolts, there exists a large sensitivity gap between current measurements and theoretical benchmarks. This award supports researchers to develop novel “haloscopes” that will improve the search rate of axion dark matter experiments by more than three orders of magnitude over conventional cavities at these higher frequencies. The new haloscopes will be based on geometries that decouple the resonant frequency and the detector volume. Inspired by techniques from radio astronomy and cosmic microwave background (CMB) telescopes, the research team has already achieved promising early results and will continue refining their designs. These developments establish key preparations for future axion searches involving large-volume solenoid magnet systems like those currently utilized for the ADMX project. 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 · 2025-08

ABSTRACT Motor vehicle injuries (MVI) have been a leading cause of death in the United States since the 1930s. Fatalities had trended downwards from the 1970s until 2019; however, these trends appear to have reversed recently. Forty percent of crash decedents were alive when emergency medical services (EMS) providers arrived at the crash scene. Improved post-crash care may prevent MVI fatalities. The National EMS Information System (NEMSIS) contains EMS information from over 14,000 EMS agencies nationally. NEMSIS includes case definitions for EMS scenarios including crashes. However, NEMSIS lacks the level of detail available in EMS data systems and does not include information from other data sources such as crash records. Linking EMS to crash records and health outcomes can provide better alignment of MVI classification across all data sources. Washington State has linked the Washington EMS Information System (WEMSIS), which includes 95% of state EMS calls between 2020 and 2024, to crash reports records as part of the Traffic Records Integration Program (TRIP) program. In this project, we will complete TRIP’s integration of Washington’s Rapid Health Integration NetwOrk (RHINO), a syndromic surveillance system containing ED, urgent care and primary care medical encounter data, and Washington Comprehensive Hospital Abstract Reporting System (CHARS), which collects hospital discharge data. We will then develop a technical report explaining the processes of building TRIP, including both a quantification of linkage failure rate and potential for selection biases and a qualitative guide to data governance discussions. We will also explore the governance steps necessary to submit a de-identified limited data set of the TRIP repository to an NIH data repository. Next, we will conduct several data science-driven analyses. We will use the TRIP to identify crashes, then compute sensitivity and positive predictive value of the current NEMSIS case definition. We will use data science, including machine learning variable importance metrics, to identify elements that can improve NEMSIS crash case definitions. We will also use the same linked data and data science approaches to explore predictors of 30-day mortality to improve NEMSIS’s injury severity scoring algorithm. Finally, we will leverage outcome information from linked ED and vital statistics data to explore associations between time to care, transport time, care facility, and crash victim mortality. Specifically, carefully considering Washington’s trauma triage protocol, we will estimate the impact of EMS response time (scene response time, scene time, and transport time) and ED facility trauma designation status (trauma level I through V or non-trauma center), on 30-day post-crash mortality.

NSF Awards · FY 2025 · 2025-08

Distributed acoustic sensing is a technology that turns the optical fibers used for telecommunications into dense arrays of virtual microphones or seismometers. The method works by converting changes in the pattern of light that is scattered back by imperfections in the fiber into measurements of vibrations all along the fiber. In the oceans, the technique can detect a variety of signals including earthquakes, whale songs, and ocean waves. It is a particularly attractive approach in this setting because it has the potential to take advantage of the existing network of submarine telecommunications cables, whereas conventional sensors are expensive to operate in the ocean. However, traditional distributed acoustic sensing cannot go beyond the first optical repeater typically located 50–100 km offshore. This project will test a new type of distributed acoustic sensing, termed multi-span distributed acoustic sensing, that has been developed by Nokia Bell Labs to see through optical repeaters so that observations can cross the oceans. The project will collect three months of data on the National Science Foundation’s Ocean Observatories Initiative (OOI) cabled scientific ocean observatory which extends off the coast of Oregon. The study will look for signals from earthquakes, ocean waves and currents, whales and ships. The observations will be compared to traditional distributed acoustic sensing collected at the same time and to the conventional sensors attached to the cabled observatory. The approach has the potential to contribute to earthquake early warning, tsunami detection, and marine ecosystem monitoring. Early warning can save lives and potentially reduce the impact of earthquakes and tsunamis. The project will support a graduate student and a postdoctoral researcher. Distributed Acoustic Sensing (DAS) is emerging as a revolutionary technology in marine geophysics, providing new capabilities to monitor seismic, oceanographic, and acoustic processes over large areas. By leveraging standard telecommunications optical fibers, DAS enables high-resolution, real-time measurements of strain variations, allowing scientists to detect earthquakes, ocean currents and waves, and marine mammal vocalizations. However, traditional DAS is limited to about 150 km range or the first optical repeater typically 50–100 km offshore, restricting its application for deep-sea monitoring. To overcome this limitation, this research will test a multi-span distributed fiber sensing approach developed by Nokia Bell Labs that extends sensing capabilities beyond the first optical repeater. The method utilizes the high-loss loopback couplers in the optical repeaters and is based on polarization-resolved optical frequency domain reflectometry. It represents a potential breakthrough in long-range fiber sensing with a spatial resolution of about 100 m. The experiment will take place on the two cables of the Ocean Observatories Initiative Regional Cabled Array, a well-instrumented offshore network that extends from Pacific City, Oregon, to the Cascadia margin and Axial Seamount. This test will generate a three-month public-domain dataset, allowing direct comparisons between multi-span DAS, nearshore multiplexed DAS and the seismometers, hydrophones, pressure gauges, and oceanographic sensors on the Regional Cabled Array. The study will evaluate the system's sensitivity to seismic activity, oceanographic phenomena, and acoustic signals while also exploring its potential contributions to earthquake early warning, tsunami detection, and marine ecosystem monitoring. 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 2025 Quality and Productivity Research Conference on Statistics in Quality, Industry and Technology (QPRC 2025) will be held in Seattle, Washington from June 15-18, 2025 at the University of Washington. This meeting will be the 41st research conference sponsored by the American Statistical Association (ASA) Section on Quality and Productivity. The theme of QPRC 2025 is “Industrial Innovation in the Era of AI.” QPRC 2025 aims to bring together researchers and practitioners from the world who use statistics in quality, technology, and industrial contexts. The conference promotes communication among researchers and practitioners to enable and ensure the development and widespread use of novel insights and methodology. The conference’s focus is on recent advancements in methodology, best practices and innovative applications. 80-85 conference attendees are anticipated and will have access to three plenary presentations, 18 invited paper sessions, four contributed paper sessions, a technical tour, and a one-day short course. Participation in QPRC 2025 has the potential to advance knowledge and understanding of topics related to data science, statistics, and machine learning, and how they can be relevant for industrial innovation. This conference traditionally attracts prominent statisticians, data scientists, quantitative analysts, and others who have an established record of highly influential, methodological, and interdisciplinary research. These individuals will have the opportunity to discuss the current progress made in statistics and machine learning, such as big data technology, text modeling, the use of generative AI in industrial innovation, and exchange novel ideas and experiences in working with modern data science to discover knowledge and apply it to numerous fields. Hence, this conference has the potential to 1) disseminate new methods and data-driven approaches, the evaluation of previous findings, and the validation of theoretical approaches, 2) stimulate further investigations regarding the benefits of working with statistics and machine learning methods for industry, and 3) increase the awareness of the need to use data science approach in industry. QPRC 2025 is committed to providing an environment where participants from academia and industry will be able to discuss research and ideas. The conference website is https://www.qprc2025.org/ . 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.