Grand Valley State University

NSF Awards · FY 2026 · 2026-10

This Research Experiences for Undergraduates (REU) Site project is focused on the training of students at the intersection of Computer Science and Digital Evolution. The students in this program conduct interdisciplinary research under the supervision of faculty members from the GVSU College of Computing, the GVSU Annis Water Research Institute, and external experts from the Van Andel Institute, an independent biomedical research institute. The site supports 10 undergraduate students for 10 weeks during the summers of 2027-2029, where participants work on projects spanning digital evolution, evolutionary computation, search-based software engineering, cell and molecular biology, and ecology. The project’s novelties are in the advancements of evolutionary theory where students are developing new techniques for solving real-world problems. Students work on multi-disciplinary research teams, guided by mentors, to advance and exploit evolutionary theory in solving complex, computational problems. The project's broader significance and importance are in preparing the next generation of interdisciplinary scientists to bridge computational problem solving with real-world challenges. The REU site intersecting computing and evolution offers a rewarding research experience for students interested in complex problems that may not have clear solutions. The students work at the frontiers of computer science, digital evolution, software engineering, biology, and mathematics, and gain critical experience for the future workforce through interdisciplinary presentations, workshops, student-driven discussions, and hands-on fieldwork under mentor supervision. Students participate in professional development activities via training on empirical research methods, ethics, and methods of communicating their findings to both the general public and scientific experts. They acquire new skills that are in demand in a broad range of technical careers. To support these activities, students meet regularly as a cohort and with mentors and GVSU graduate students to ensure continuing progress and growth on their respective research projects and training activities. 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

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project focuses on issues of economic impact: improvement of the software and systems that underpin our national infrastructure. By adopting the proposed technology, software development teams may avoid critical quality and security issues. This intelligent refactoring technology enables organizations to better maintain their software as it ages and better align their maintenance efforts with their priorities. This innovation seeks to deliver continuous will also provide training opportunities for students in technological innovation and entrepreneurship. This project focuses on developing scalable methods to determine when and how to integrate developer feedback to semi-automate code refactoring for continuous integration environments while adhering to industry standards to align the effort with their commercialization objectives. Software refactoring is recognized as the key component for maintaining high quality software by restructuring existing code and reducing technical debt. Refactoring requires programmers to review, detect, and fix quality issues to improve software performance. However, refactoring is difficult to achieve and often neglected not only due to a pressure to meet release deadlines, but also due to the constraints imposed by manual refactoring as well as lack of technical skill in restructuring complex systems. The traditional root-canal refactoring process is not practical since it is time consuming and hard to integrate in the development pipelines. Hence, new refactoring tool must deliver timely support for code repair. The goal of this technology is to clearly exhibit the feasibility of combining interactive, semi-automated, refactoring technology with continuous integration via an artificial intelligence-based bot and demonstrate the implemented concept at large-scale. The effort will also support multiple programming languages including quantitative (such as accuracy, relevance, and performance) and qualitative (such as programmers' comments) aspects. 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

This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at Grand Valley State University. A total of 24 undergraduate scholars pursuing Bachelor of Science degrees in Biomedical Engineering, Computer Engineering, Electrical Engineering, Interdisciplinary Engineering, Mechanical Engineering, and Product Design & Manufacturing Engineering will receive scholarships averaging $10,648 per year for up to five years. Scholars will receive faculty mentoring, and the project will build strong scholar cohorts through a four-week residential summer camp featuring content delivered through social activities, workshops, and classroom experiences designed to help students adapt to the college learning environment. Scholars will also engage in a year-long, faculty-mentored Technology Career Program that includes collaborative technical projects and professional development workshops. Additional activities will include individualized tutoring, targeted seminars and workshops, conference participation, and a Family and Community Support Group. The overall goal of this Track 2 Scholarships in STEM project is to increase STEM degree completion of academically talented, low-income undergraduates with demonstrated financial need. There is a significant national need to grow the STEM workforce and nurture key talent that will ensure economic competitiveness and provide domestic leadership across critical sectors. This project directly speaks to this need by supporting STEM student success, which will strengthen the workforce in engineering and other key areas of need. The project will be assessed by an experienced evaluator who will use mixed methods to assess project outcomes and impact, and the data generated will contribute to the knowledge base regarding effective strategies to support talented, low-income students in STEM. This project is funded by NSF's Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of academically talented, low-income students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students. 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

A population’s ability to adapt to new or changing environmental conditions can be an important factor impacting species success. Adaptation is frequently associated with high levels of genetic variation, and when populations with limited genetic variation experience new or changing environments, it may be difficult to respond to these conditions. Nevertheless, many species not only survive, but thrive after a small group of individuals are introduced to new habitats. This can be the case for invasive species; one of the primary threats to biodiversity due to their impacts on native biota and their ability to alter ecosystems. Invasive species provide an optimal system to study evolutionary processes since they are ‘real-life’ experiments allowing researchers to assess mechanisms shaping how species respond to environmental change. Hemlock woolly adelgid (Adelges tsugae) is one of the top invasive threats to forest ecosystems in eastern North America. Hemlock woolly adelgid populations in eastern North America are invasive and display rapid population growth and range expansion, while western North American populations are native, and population growth is limited by natural predation. This research project compares eastern and western hemlock woolly adelgid populations to explore how invasive traits, such as rapid range expansion and population growth, influence genomic structure and adaptive potential as invasive populations expand their distribution range. The data collected will improve hemlock woolly adelgid management by identifying dispersal patterns and improving future range expansion models. This project will also result in the development of advanced genomic-based courses for undergraduates. The specific goals of this project are to (i) assess the population structure of invasive and native HWA populations in North America, (ii) evaluate how population demographics influence genetic diversity and genetic load, and (iii) understand the molecular processes contributing to increased cold tolerance of some northern invasive populations. For the first goal, the researchers will collect individuals from across the western and eastern North American distribution ranges and use low coverage whole genome sequencing (lcWGS) to evaluate genetic diversity and population structure. For the second goal, the researchers will use the genomic data to evaluate how range distribution patterns and differences in selection processes impact the accumulation of deleterious mutations throughout invasive populations. For the third goal, individuals will be collected across different climate regions where populations differ in their cold tolerance. The researchers will evaluate differences in cold-induced mortality among populations and use RNA-sequencing to identify differentially expressed genes associated with variation in cold tolerance. The combined datasets will evaluate how population dynamics impacts novel mutation accumulation, genetic load, and adaptive responses to new selection pressures. Overall, this project will increase our understanding of the genomic mechanisms influencing the rapid success of invasive species to novel ecosystems. 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 ExLENT Beginnings Tack project addresses a critical national need by developing, delivering, and assessing an experiential training program in the rapidly evolving field of marine technology. Coastal communities, home to 40% of the US population, are vital to the nation's economy and depend on the skilled marine technology workforce to monitor, maintain, and rebuild essential coastal infrastructure. Yet demand for these services is outpacing workforce growth. Importantly, advances in robotics and artificial intelligence (AI) are transforming the field. Smart deployment of autonomous underwater vehicles (AUVs) now enables real time decision making and complex, observation-dependent tasks. While these AI enabled technologies offer tremendous potential, existing professionals need opportunities to upskill, and students entering the field must be equipped for success in this new technological landscape. This initiative brings together a cross-sector partnership that includes colleges and universities, marine technology manufacturers, industry employers, and regional entrepreneurship leaders driving the water-based economy. Grounded in this strong foundation, the project immerses participants in hands-on learning, offering meaningful opportunities to deploy AUV projects for clients in authentic real-world settings. The project pursues two overarching goals: 1) create opportunities for skill development in emerging areas of marine technology, with an emphasis on artificial intelligence and smart deployment of AUVs, and 2) strengthen students' and early career professionals' confidence in their career preparation. To support these goals, the initiative offers a six-week hybrid course that integrates online and in-person instruction, emphasizing both the theoretical foundations and practical applications of smart AUV deployment. A team of collaborating researchers with expertise in marine technology, AI, autonomous systems, and aquatic ecology facilitates this experience for 72 participants over three years. Participants complete 4-weeks of foundational training followed by two weeks of hands-on project-based work aboard a research vessel. During the immersive phase, small groups plan and execute AUV deployments aligned with model client needs, such as lake bottom surface mapping, water chemistry analysis, and shipwreck investigations. An external evaluator collects both formative and summative data to inform continuous refinement of the project and to contribute new insights to the marine technology education literature. Dissemination occurs through local and national venues, including publications and professional conferences. Collectively, this work contributes to the development of a collaborative, adaptable model for advancing both technological innovation and workforce preparation in the field. The NSF ExLENT Program, supported by the NSF TIP and EDU Directorates, seeks to support experiential learning opportunities for individuals to increase their interest in and their access to career pathways in emerging technology fields. 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 goal of this research project is to gain insight into the growth and decline of cities through the examination of animal management and distribution within urban areas. There are a variety of definitions for urban centers and cities, and each emphasizes different factors such as geography, economics, demographics, and/or social aspects. However, these approaches do not consider that cycles of urbanism exist as cities grow or diminish in size and complexity and so change in form, function, or status over time. This research examines the changing nature of cities through archaeology, a discipline that is particularly well placed to provide relevant insight because it can trace changes over extended periods of time. The emergence of one set of Iron Age sites provides an excellent opportunity to study the fluidity of urbanism and the emergence of internal growth, shifting populations, and new political systems. All these factors impact the size and character of settlements. This study will extract and analyze stable isotope data. Stable isotope data is based on chemical variations in the chemical element (same number of protons but different number of neutrons). The stable isotope data is analyzed with mathematical models that rely on the use of artificial intelligence. Moreover, stable isotope data and methods relate to biotechnology as they assess data from non-radioactive element to examine and identify biological processes (e.g. food chains, migration, site of origin). This research builds a detailed picture of animal management systems during the phases of the Iron Age at four “urban” sites. These sites provide large, well-dated faunal assemblages from well-documented sites within a regional context. Researchers analyze archaeological domestic animal remains using both zooarchaeology and archaeological science. Zooarchaeology, the study of animal remains, determines species preferences, changes in the age and/or sex composition of herds and/or increased culling of select ages or species, as well as changes in butchery pattern and intensity and modifications. The differences in relative frequency of animal species demonstrate the differing preferences of animal husbandry and use practices at those sites, potentially related to different production strategies and levels of urbanization. Analyses (carbon, oxygen, and strontium) to characterize the diet of individual animals, management strategies (including birth and cull seasons, the contribution of grazing/browsing/foddering and water management) as well as animal mobility are also conducted. The research provides a robust understanding of human-animal interactions at this time as well as further information on the larger themes of foodways and trade which have not been fully explored for this period. 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 · 2025-02

Evidence from ice cores in Antarctica has shown that the carbon dioxide (CO2) content of the atmosphere has changed systematically with Earth’s climate over the last 800,000 years, with lower atmospheric CO2 concentrations in cold (glacial) intervals. Because the oceans must maintain a balance between alkalinity supplied by continental weathering, and alkalinity removed by calcium carbonate burial, at least over long time periods, a reduction in the burial of calcium carbonate on continental shelves would induce an increase in the carbonate ion concentration of seawater to preserve more calcium carbonate in deep sea sediments. If seawater had a greater carbonate ion concentration than today, then it would absorb more CO2 from the atmosphere. However, the exact mechanism(s) responsible for this CO2 variability remain(s) to be determined. To address this key knowledge gap, the investigators seek to test a method for estimating the carbonate ion concentration of seawater in the past. Existing methods for estimating carbonate ion concentration are labor-intensive and expensive. This proposal aims to test a method that would be much faster and much less expensive. The scientific goal is to combine estimates of carbonate ion concentration from marine sediments with the other geologic evidence to determine the relative importance of biological processes and of changes in sea level as factors that contributed to lower atmospheric CO2 concentration during glacial intervals. Broader impacts activities include training, mentoring, and the involving undergraduate students in research, community outreach events, and workforce development. The investigators plan to advance the calibration of an existing proxy for calcium carbonate (CaCO3) dissolution, and to determine if the proxy also provides reliable estimates of bottom water carbonate ion concentration. Calcium carbonate dissolution in the deep sea is sensitive to changes in bottom water undersaturation (expressed as Delta [CO32-]), so a proxy method for CaCO3 dissolution (Globorotalia menardii Fragmentation Index – MFI), if rigorously calibrated, should provide a measure of bottom water Delta [CO32-]. The MFI method is rapid, inexpensive, only requires a microscope, and is suited to the involvement of undergraduate students in research on the global carbon cycle. The immediate goal is to determine if the MFI method can be used to provide a reliable measure of Delta [CO32-] through a 3-pronged calibration effort with previously collected samples: (1) Determine the MFI across a range of water depths in the Eastern Equatorial Pacific, where Delta [CO32-] and the rate of CaCO3 dissolution have been measured independently; (2) conduct a global survey, including the Eastern Equatorial Pacific, to compare MFI against climatological Delta [CO32-] to assess potential regional variability in the relationship between Delta [CO32-] and MFI; and (3) determine the MFI from marine sediments from the Central Equatorial Pacific, covering the last 160,000 years, in two cores where Delta [CO32-] has already been measured using B/Ca ratios in epibenthic foraminifera. 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 · 2025-02

Grand Valley State University will deploy and evaluate an Algebra 2 extension of the Bootstrap:Data Science curriculum across Michigan. Michigan faces logistical challenges in providing widespread Computer Science (CS) education: only 55% of high schools offer it at all, much less to all students. At the same time, data science — with its job prospects and ties to artificial intelligence—is vying for the same attention. Ideally, the two subjects could be taught together while meeting relevant standards and supporting diverse students in learning both subjects. The practitioners in this Research-Practice Partnership (RPP) — state education leaders in Michigan—see opportunity in Algebra 2. It is a graduation requirement that many students struggle to pass and many teachers see as needing reform. At the same time, state data show that college enrollment has risen since the requirement was adopted, especially for students from historically underrepresented groups in computing. Algebra 2 prepares students for calculus and many science, technology, engineering, and math (STEM) subjects in college. This RPP will address problems of practice for CS and mathematics education by integrating computing as needed for Data Science into Algebra 2. The project team will offer professional learning workshops and ongoing support to teachers across Michigan. The research team will use a mixed-methods design to study the factors that motivate districts and teachers to explore, adopt, and deepen their use of the project’s materials, with an eye towards how this differs across regions and student demographics across Michigan. This RPP will also study the impact of this curriculum on girls and students from rural areas. If successful, the project will provide a model for expanding access to computing and data science while improving student outcomes in Algebra 2. It might also impact students’ confidence and perceived relevance of Algebra 2 (issues that are known to affect girls and rural students in particular), which could in turn influence students’ future course and career interests. The Bootstrap:Data Science curriculum is a mature program with STEMworks certification and an underlying research foundation that covers significant portions of the standards from the Computer Science Teachers Association (CSTA), mathematics, and Next Generation Science Standards (NGSS). It is customizable across a wide array of datasets, thus enabling districts to select topics that are culturally relevant to students and their communities. The project team will use a combination of lightweight classroom activities and validated instruments about math confidence and math relevance to study the project’s impact on students, contrasting the experiences of rural students and girls with those of the broader student population. Deliverables include research-backed models for including computing and data science in Algebra 2, Michigan-focused datasets targeted to regional issues and career pathways, 150 trained teachers and Michigan-based facilitators, case studies in adoption by districts and teachers, and findings on the impact of this approach on students from two under-represented populations. 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 2024 · 2024-09

Building Institutional Capacity for External Partnerships (BICEP) is a team of four universities with the shared goal of collaboratively building their institutional capacity and knowledge for growing external partnerships that advance key technologies within their innovation ecosystems. Team members include Santa Clara University, Lawrence Technological University, Grand Valley State University, and Minnesota State University Mankato; each member is both a Primarily Undergraduate Institution (PUI) as well as an Emerging Research Institution (ERI). To address common challenges to participating in their regional innovation ecosystems, the BICEP team has identified three specific objectives on which to collaboratively focus through this proposed project: a) Operational Maturity in establishing institutional policies and structure to enable efficient and professional partnering, b) Professional Development to enhance the knowledge of faculty and staff to be better equipped to participate in and contribute to technology partnerships with external organizations, and c) Partner Engagement activities to support managing and strategically evolving partnerships over time. While the benefits of and strategies for developing partnerships are well documented, knowledge on how PUIs/ERIs can best grow a comprehensive array of external technical partnerships is very limited. Focusing on the areas of Operational Maturity, Professional Development and Partner Engagement, BICEP team members will identify a set of strategies, practices, and lessons learned relevant to how PUI/ERI institutions can, in general, build their capacity to support their regional innovation ecosystems. This new knowledge will be codified, documented, and disseminated through publications, workshops and a toolkit with resources that may be used by other PUI/ERI universities. In conducting this work, each institution will benefit from an increase in the number and quality of external partnerships, the ability to secure external funding and resources, and the capacity to grow programs in workforce development, use-inspired research and development, and research translation. This will catalyze faculty research opportunities, increase engagement of underrepresented and economically disadvantaged students within the federal STEM-related funding portfolio, enhance skills within the workforce, and contribute to the economic health of the BICEP team innovation ecosystems. 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 2024 · 2024-08

This project aims to advance our understanding of hydroclimate, water cycling, and ecosystem interactions by precisely measuring natural variations in the mass of water molecules caused by different isotopes of hydrogen and oxygen. It brings a cutting-edge isotopic water analyzer to Grand Valley State University. The instrument enables researchers and students to investigate climate change impacts on water cycles, the health of freshwater ecosystems like wetlands, and groundwater resource contamination. The ability to track isotopic "fingerprints" in water will allow the research team to study where ground- and surface waters are sourced from, as well as track geochemical processes occurring in those waters. This project will provide hands-on training for the next generation of water scientists while directly benefiting West Michigan communities through educational outreach. The project brings a Picarro L2140-i Isotopic Water Analyzer to Grand Valley State University (GVSU), a primarily undergraduate institution, for use in geoscience, ecology, and climate research. This device will primarily be used to facilitate novel investigations into water movement between freshwater and coastal systems, including analysis of precipitation, ocean, lake, and aquifer waters to understand their hydrology, geochemistry, and climate. Initial investigations will specifically focus on: 1) Water oxygen-18 isotopic variability in lacustrine and coastal marine carbonate forming environments, with an eye towards paleoclimate applications; 2) High-resolution oxygen-17 and hydrogen isotope monitoring in precipitation and surface waters to better estimate Great Lakes basin moisture recycling; 3) Oxygen isotopes as an ecosystem metabolism proxy in monitored wetlands; and 4) Pilot exploration of nitrate contamination sourcing via water isotopes. Each study has been designed to advance scientific understanding by leveraging the interdisciplinary expertise at GVSU. The project will build pioneering and publicly available water stable isotope datasets that can be utilized in related research globally. These efforts will also result in high-impact publications that will raise the profile of this primarily undergraduate institution, while simultaneously providing hands-on experiences for students. 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.