Grants $100,000 to $250,000

NYC Department of Cultural Affairs

Home for Contemporary Theatre & Art, Ltd.

Vernon

Replacement Vernon Police Department

NSF

This Engineering Research Initiation (ERI) grant will support fundamental research that aims to improve reliable coordination for a team of autonomous mobile robots operating in realistic and possibly adversarial environments. Robots that can collaborate have shown great potential in many applications from search and rescue missions to precision agriculture. Due to limited sensing, communication, and processing capabilities, autonomous robots in a collaborating group often need to make collective decisions through communications in proximity. For example, exchanging sensing data or control commands with neighboring robots through range-constrained wireless communications. The integral role of wireless communications requires robots to coordinate and react to the changing environment for reliable information sharing in addition to their original tasks. However, existing research paradigm often assumes that the communication environment is well modeled and can be pre-programmed into robotic systems for effective coordination without disruptions. This significantly limits the capabilities of robot teams and makes them vulnerable in real-world environments that can often be unpredictable. To address the challenges, this project seeks to create a set of methods and tools that may augment many multi-robot coordination tasks, by enabling robots to learn the environment on the fly, adapt their motion to environmental changes, and maintain communications when unexpected robot failures happen. The project will also support education and outreach activities such as curriculum development, broadening participation of students from underrepresented groups, and local community engagement in the Charlotte metropolitan area. The objective of this project is to create novel methods and algorithms that enable the co-design of learning, communication, and motion control for mobile robot teams. This may allow for robust operation of robots with provable assurances on communication capabilities and multi-robot network resilience adaptive to uncertain environments, positively supporting the primary task execution. In pursuit of this goal, the project will make two main contributions: (i) Developing data-driven methods for robots to collaboratively learn the spatially varying realistic communication performance online, and (ii) Developing new approaches that specify the impact of realistic communication constraints and network resilience on the task-related robots’ motion, to enable joint optimization for more efficient multi-robot coordination with performance guarantees. The work will be evaluated in simulations and experiments on physical robotic platforms. This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE). 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

Modern science and engineering increasingly rely on extracting meaningful information from large and noisy datasets, such as those arising in medical imaging, environmental monitoring, telecommunications, and numerous other disciplines. This project develops advanced statistical methods that improve signal recovery and noise reduction through innovative shrinkage and thresholding techniques applied in multiscale domains like wavelets. In addition to classical computational tools, the project explores emerging directions involving quantum computing simulators to prototype quantum-inspired shrinkage methods, aligning with growing national and institutional emphasis on quantum technologies. These approaches simplify complex data by selectively attenuating noise while preserving essential features, leading to more accurate and interpretable results. The project integrates education by mentoring students at multiple levels, incorporating findings into graduate and undergraduate courses, and creating open-source software tools that promote reproducible research and broad access to cutting-edge statistical techniques. This research advances the theory and application of shrinkage estimation in multiscale settings, with a particular emphasis on quantum-inspired methodologies that complement classical Bayesian and frequentist frameworks. It develops adaptive block-shrinkage procedures employing priors that capture dependence among wavelet coefficients and introduces absolutely continuous shrinkage priors that maintain computational tractability without relying on spike-and-slab or point-mass priors. The project also devises novel thresholding strategies informed by refined extreme-value approximations and Bayesian decision rules based on Bayes factors. Computational implementation includes efficient posterior simulation algorithms and exploratory shrinkage techniques using quantum computing simulators. These innovations will contribute to foundational methodology for nonparametric regression, signal processing, and scalable high-dimensional inference. 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.

Albertsons Companies - Site 813

Commercial

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

PROJECT SUMMARY/ABSTRACT Lower urinary tract symptoms (LUTS) are common and have a significant negative impact on the lives of adult men and women. The Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) was formed in 2012 to address research gaps related to the care of patients with LUTS. The long-term goals of the University of Iowa LURN Research Site are to better treat and prevent lower urinary tract dysfunction in men and women. Toward this goal, additional research is required to better characterize and understand clinically-useful LUTS patient subtypes and to better measure the full patient experience related to the broad range of LUTS. The Iowa Research Site thus proposes to perform multicenter and multidisciplinary research with other LURN sites to 1) Test and refine LURN symptom-based clusters including a wider range of symptom severity and a wider range of physiological measures than performed in prior studies, 2) Assess the relationship between physical activity and sleep (important non-urologic factors related to LUTS) and LUTS and LUTS treatment response, 3) Determine phenotypic characteristics of women with LUTS by measuring the functional components via urodynamic testing, 4) Identify protein biomarker signatures contained within plasma of specific subgroups of men and women with LUTS, and 5) Validate a comprehensive outcome tool for men and women with LUTS. To address these aims, several distinct but complementary studies are proposed. LURN will perform a 3-year cohort study of men and women with a diverse spectrum of LUTS severity and characterize them with standardized clinical evaluations, self-reported symptoms and associated conditions, quality of life, voiding diaries and detailed information on treatments and treatment response over time. Wearable health tracking devices and smartphone text messaging technologies will be utilized to collect objective physical activity and sleep quality data from cohort study participants. Additionally, participants will complete the LURN Comprehensive Assessment of Self-Reported Urinary Symptoms – Outcome Measure (CASUS-OM) to test its internal consistency, validity and responsiveness to change after LUTS treatments. In another study, women with urgency and urgency urinary incontinence will undergo a battery of standardized urodynamic tests focused on sensory and motor functions of the urethra and bladder. Lastly, analysis of protein biomarker signatures will be performed, using plasma samples previously collected from men and women with LUTS. Important findings from these significant LURN research efforts will help improve the clinical care of LUTS patients and will inform the development of future LUTS clinical studies.

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

Project Summary Chronic kidney disease (CKD) poses a major global health burden, yet therapeutic options remain limited and largely repurposed from other diseases. A key barrier to therapeutic progress is the incomplete understanding of CKD’s molecular and genetic mechanisms. Genetic factors explain 30–50% of CKD risk, but genome-wide association studies primarily identify non-coding variants, complicating functional interpretation. Most gene expression studies in CKD have focused on total gene expression, overlooking alternative splicing. Short-read RNA sequencing of 404 human kidney samples showed alternative splicing explains an additional 5% of CKD heritability. However, short-read sequencing fragments RNA, limiting full isoform characterization. Long-read sequencing of 8 kidney samples identified 67% novel isoforms and revealed significant isoform differences between CKD and control samples. Given the limitations of short read sequencing, I will employ long read sequencing to comprehensively characterize the role splicing in kidney disease. I will first employ this in bulk kidney tissue to identify novel isoforms, compare the isoform expression between CKD and controls and to compare the identified isoforms with mass spectrometry data to clarify the relationship between the spliced isoforms and protein levels. I will then perform single cell long read sequencing to generate the first isoform-resolved atlas of kidney cell populations, enabling identification of cellular states associated with disease. Differential isoform usage at single-cell resolution will clarify which kidney cell types and isoforms drive disease pathology. This project will comprehensively characterize the splicing events in the kidney and the role in kidney disease.

NIAMS - National Institute of Arthritis and Musculoskeletal and Skin Diseases

PROJECT SUMMARY Rotator cuff tendinopathy is a prevalent chronic disease that is painful, debilitating, and reduces the quality of life. Physical therapy (PT) is an effective first-line treatment, but the non-response rate to PT is still high. Long- term recovery is further limited, and the reason for pain recurrence is poorly explained. It is possible that the in- clinic gains of PT fail to translate to good real-world mechanics and are overwhelmed by the pathomechanical shoulder movements in activities of daily living. Clinical and basic science both suggest shoulder overuse and motion-driven pathomechanics are causal factors of rotator cuff pathology. These biomechanical mechanisms are unconfirmed in patients partly due to the complex interplays among pathology, mechanics, and treatment, in addition to a paucity of methods to quantify the highly variable real-world motion and in-vivo tendon loading. My overall goal is to discover how real-world shoulder biomechanics interact with the clinical outcomes of PT in rotator cuff tendinopathy. This research progresses from a cross-sectional [K99] to a longitudinal cohort study [R00]. My cross-sectional Aim 1 [K99] will use 1) wearable sensors to track 7-day bilateral shoulder cumulative motion in daily living; 2) motion analysis and musculosketeal models to identify motion-driven pathomechanics specific to daily living functional tasks; and 3) machine learning to combine sensor-detected activities with motion-driven biomechanics to quantify real-world cumulative rotator cuff tendon loading. My mentored K99 will validate research tools and define how patient shoulder motion and tendon loading deviate from normal status. The longitudinal Aim 2 [R00] will link the real-world biomechanics established in Aim 1 with changes in clinical outcomes, including pain, shoulder function, and tendon structure, through a 3-month PT protocol followed by the first 6 months after PT completion. These Aims will clarify the mechanical mechanisms on how real-world shoulder motion and loading alter the course of PT clinical outcomes in rotator cuff tendinopathy. Findings will inform data-driven continuous rehabilitation paradigms that monitor and modify daily living activities to maintain long-term shoulder health. This research will also serve as the foundation of Dr. Ke Song's career development plan to acquire 2 years of mentored training [K99] and prepare for transition into independence [R00]. Through the guidance of his experienced and interdisciplinary mentoring team, Dr. Song will perform hands-on training with field-leading experts in shoulder biomechanics, physical therapy, orthopaedics, wearable sensors, data science, and biostatistics to maximize the impact of his proposed research. Dr. Song will also learn from formal courses and professional training activities to ensure his career progress, develop clinical research proficiency, improve grant writing, mentoring, and leadership skills, and secure an independent tenure-track faculty position at a clinical research-intensive institution. The scientific training, professional development, and research plans will guide Dr. Song through a pathway to independent research in translational musculoskeletal biomechanics that help patients with rotator cuff tendinopathy and related shoulder diseases improve long-term outcomes.

NSF

NON-TECHNICAL SUMMARY Aluminum-Magnesium (Al-Mg) alloys are commonly used as a lightweight alternative to steel in transportation applications and exposed infrastructure due to their excellent strength-to-weight ratio, weldability, and some of the highest resistances to corrosion damage amongst aluminum alloys. Prolonged exposure to elevated temperatures, however, leads these alloys to develop a serious problem known as sensitization that can eventually result in catastrophic failures. This project investigates the fundamental mechanisms controlling the sensitization process in Al-Mg, which are governed by complex atomic interactions with defects in the material’s internal structure created during manufacturing. These findings will ultimately guide the development of new material processing strategies that mitigate the sensitization process and extend the lifetime of these materials by several times their current limit. As Al-Mg alloys are already used extensively in critical transportation and energy infrastructure, this research presents immediate potential for large economic and sustainability improvements. The education and outreach efforts included in this project introduce materials science education in venues and contexts classically associated with the humanities. In an ongoing collaboration with the Cincinnati Art Museum, educational Science of Art programming is being introduced via QR-code links located alongside select objects within the museum, and a new interdisciplinary undergraduate course is being offered that uses the unique and publicly intriguing lens of sword-making to introduce fundamental concepts in physical metallurgy and materials science to undergraduates outside science and engineering majors. TECHNICAL SUMMARY This project tests three major hypotheses regarding the fundamental mechanisms by which microstructural features control the nucleation and growth of grain boundary precipitates in 5xxx series Al-Mg alloys, a defect-controlled precipitation process governed by complex diffusion pathways. Precipitation of the anodic Mg-rich beta-phase along grain boundaries in these super-saturated Al-Mg alloys leads to increased susceptibility to intergranular corrosion in a process known as sensitization, which can compound over time at environmental temperatures and result in catastrophic failures. Carefully designed experiments are employed that take advantage of novel characterization techniques to make statistically relevant direct observations of the nanoscale precipitates along the grain boundaries, addressing uncertainties regarding the underlying mechanisms and diffusion modes dictating the nucleation and growth, along with the precipitate distribution’s consequent impact on the sensitization response. Establishing the contributions that specific microstructural features play in the progression of this type of precipitation, notably as a function of temperature and configuration, enables the development of new processing strategies that lower long-term sensitization response in these alloys and increase service life. This research answers pertinent questions inherent to many systems possessing detrimental nanoscale precipitates that nucleate preferentially upon defect structures, and provides critical new experimental studies exploring the interplay between microstructural elements and multi-stage diffusion pathways. 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.

Valley Housing Foundation

Valley Housing Foundation is an active grantmaking foundation based in Pacoima, CA. Focus: health. Contact the foundation directly for current funding opportunities.

NSF

Each year engineering students enroll in college to gain knowledge and develop skills in preparation for their careers in the field. The successes and experiences of these students within their engineering education shape how they see themselves within the profession as they transition from “engineering student” to “engineer.” While the process of acquiring the engineer identity looks different for every student, there are certain complexities that emerge when the engineering student identity is intersected with other identities, including those that face unique challenges such as first-generation. Unlike continuing-generation peers, first-generation students who are the first in their families to attend college are progressing toward the engineer identity at the same time they are learning to navigate the landscape of higher education with its complex structures and jargon. These identities influence how students understand their position within engineering programs. Furthermore, the type of program a student enrolls in may impact how a student conceptualizes and consolidates the engineer identity. Engineering technology programs have historically been associated with a more hands-on approach to engineering education. As such, the process of acquiring the engineer identity may look different for engineering technology students compared to peers in engineering science programs. This study will explore the question of how these two identities: first-generation and engineering technology students intersect to influence the formation of the engineer identity. This goal is directly aligned with research in the professional formation of engineers which seeks to better understand how engineering education programs develop future engineers. The research design for this project is a two phase, mixed methods approach. In Phase 1, we will survey approximately 500 engineering technology students across two and four-year institutions. Responses will address the research questions of how self-identified first-generation engineering technology students conceptualize and consolidate the engineer identity as part of their education across institutions, as well as address how first-generation participants understand and leverage forms of social capital in pursuit of their engineering degree as compared to continuing-generation peers. Additionally, performance metric data will be obtained and de-identified through the Office of Institutional Effectiveness at UNC Charlotte for local participants who have consented to participate as a way to investigate whether discrepancies exist between first-generation engineering technology students and continuing-generation peers in the same program. In Phase 2, we will employ qualitative interviews with a group of 35 first generation engineering technology students to secure a richer understanding of their experiences. This iterative approach will allow us to identify potential gaps in Phase 1 while the qualitative work in Phase 2 will then expand our understanding of the engineer identity acquisition process. The primary goal of this project is to contribute to the growing body of knowledge provided by engineering education researchers. At present, there is limited research exploring the consolidation of the engineer identity among first-generation students. No existing study has explored this phenomenon with engineering technology students. We hope to leverage our research to begin to close this knowledge gap and to disseminate our findings widely to other engineering educators who serve to support first-generation engineering technology students as they conceptualize their place within the engineering profession. 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.

NYC Department of Cultural Affairs

Vivian Beaumont Theater, Inc.