Author: orandall

People make complex decisions throughout their lives and often seek out evidence to help them understand their options. In areas such as finance and health, some of the most useful information for decision-making is presented numerically and requires mathematical and statistical reasoning to make sense of. For example, it is important in medicine to quantify the risks and benefits of a treatment to help people decide whether to accept it. Related to health and wellness, the decision whether to drink alcohol or how much to exercise also relies on understanding the magnitude of risks and benefits to make decisions aligned with one’s personal values and goals. As a final example drawn from everyday living and financial decision making, deciding to rent or buy a home entails making sense of complex mathematics that is influenced by day-to-day changes. This project will support the public’s quantitative reasoning about critical personal health and finance decisions by (1) designing representations of real-world data that are accessible to people with a wide range of educational backgrounds. The project will (2) expand our knowledge of how adults use mathematical and statistical reasoning by studying how people use the representations of data to make decisions. In turn, this project will (3) support pre-service and in-service mathematics teachers in teaching mathematical and statistical ideas that are critical for decision-making This project will curate quantitative data from published, peer-reviewed research on topics of broad interest that people learn about to make decisions. People are interested in understanding more about the risks and benefits of alcohol, exercise, and various commonly used medicines. People also use tools such as rent versus buy calculators to make decisions. In this study, Quantitative Data Representations (QDRs) will be designed to help make data accessible to people who have a wide-range of mathematics backgrounds. For instance, comparing the relative size of two fractions is difficult for many. This is important when trying to represent the magnitudes of risk visually for activities like drinking alcohol, physical activity, and selecting the best mortgage. This project will explore the use of AI to reduce the cost of coding QDRs and investigate the constraints and affordances of using AI to transform peer-reviewed results into QDRs. The project team will conduct interviews with individuals while engaging them with the QDRs in efforts to iteratively improve them and to create models of mathematical thinking of people engaged in real-world decision making. The interviews will also be used to create hypotheses and design surveys given to representative samples of US residents. Randomized controlled trials will be used to test the understandability of QDR design and hypotheses about mathematical thinking used in decision making. Exploring quantitative reasoning in real-life contexts will provide valuable insights for improving the relationship between what is taught in mathematics classrooms and what knowledge adults use in life. This work will expand the utility of models of mathematical thinking, which were often limited to researchers studying reasoning in classroom contexts, by refining those models via studying quantitative reasoning in real-world contexts. Generating knowledge about how people use data representations to support their reasoning will inform improvements in the design of data representations about critical topics such as health risks and finance. The project will contribute to improving STEM education and educator development by preparing in-service and pre-service mathematics teachers to teach new financial literacy standards. The project will contribute to the lives of all Americans by designing QDRs that are accessible to people with a variety of mathematics, financial, and health backgrounds and support their quantitative reasoning.

Funder: NSF 

Amount: $626,531 

PI: Cameron Byerley, Mary Frances Early College of Education

Understanding how water and other fluids move through and interact with rocks is essential for managing groundwater, energy, and mineral resources. This project will undertake laboratory observations to improve understanding of rock structure, flow properties, and mineral reactions. The project will train students in cutting-edge methods and create an interactive virtual fieldwork experience for geoscience education. It will investigate pore-scale processes to improve the predictive capabilities of multiphase reactive transport models. The research will combine advanced flow experiments with high-resolution X-ray imaging to capture 3D changes in pore structure, fluid distribution, and mineral surfaces during dissolution. The resulting datasets will support the development of new mathematical equations for large-scale simulations, advancing modeling capabilities across geosciences and engineering fields.

Funder: NSF 

Amount: $737,228 

PI: Charlotte Garing, Franklin College of Arts and Sciences, Department of Geology

Fox squirrels are widely distributed throughout much of the eastern U.S., but southeastern subspecies appear to be declining due to habitat fragmentation and loss. Conservation and management efforts of fox squirrels in Georgia have been limited by a lack of information regarding their distribution. Furthermore, fox squirrels can be legally harvested in Georgia, but the influence of hunter harvest on populations is unknown. This proposal will define the current distribution, including occupancy by land cover type, habitat use, and influence of harvest on fox squirrels in Georgia to provide Georgia DNR biologists information needed to make informed management decisions regarding fox squirrels across the state.

Funder: Georgia Department of Natural Resources 

Amount: $825,480 

PI: Elizabeth Pienaar, Warnell School of Forestry and Natural Resources 

This award will protect U.S. interests by building Sierra Leone’s capacity to combat child trafficking in gold mining regions, disrupting criminal networks and ensuring ethical mineral supply chains critical to U.S. economic security. The specific objectives of the program are to 1) strengthen policy and legal frameworks, 2) expand survivor-centered protection services and promote survivor sustainability; 3) strengthen prosecution capacity, and 4) build community-level prevention and awareness.

Funder: U.S. Department of State 

Amount: $2,375,000 

PI: David Okech, School of Social Work 

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are still life-threatening diseases in critically ill patients. Despite diagnosis and therapy for ARDS having been developed steadily over the last 50 years, its mortality has remained static at 30%-to-40% in the last decade. To date, no specific pharmacological interventions have been shown to improve outcomes. Thus, there is an urgent need to reduce the morbidity and mortality associated with ARDS, alleviate the burden on patients and their families, and save lives by improving lung health. In ALI/ARDS, endothelial cell death is a critical pathological event. Damage to pulmonary capillary endothelial cells compromises the integrity of the alveolar-capillary barrier, resulting in increased vascular permeability, pulmonary edema, and impaired gas exchange. Given the central role of endothelial injury in the pathogenesis of ALI/ARDS, therapeutic strategies that preserve endothelial cell viability and restore barrier function hold significant promise. Targeting mechanisms of endothelial cell death may offer a novel and effective approach to improve outcomes in patients with ALI/ARDS. Long noncoding RNAs (lncRNAs) have emerged as key regulators of gene expression, influencing a wide range of physiological and pathological processes. Increasing evidence suggests that lncRNAs play critical roles in the pathogenesis of ALI and represent promising targets for diagnosis and therapy. In our study, we identified an lncRNA, Lncenc1, that is markedly upregulated in murine lungs following bacterial infection. Notably, Lncenc1 deficiency conferred protection against Klebsiella pneumoniae (K. pneu)-induced lung injury and pulmonary edema. Mechanistically, we observed a significant increase in CD59 expression in lung tissues of Lncenc1- deficient mice compared to wild-type controls. CD59 is predominantly expressed on vascular endothelial cells and acts as a “suicide inhibitor” by blocking complement activation and membrane attack complex (MAC) formation on the cell surface. Loss of Cd59 exacerbated K. pneu-induced ALI, resulting in increased pulmonary vascular leakage and mortality. Our central hypothesis is that Lncenc1 regulates endothelial cell death by modulating CD59-dependent complement activation and MAC formation during bacteria-induced ALI. We hypothesize that the Lncenc1–CD59– MAC axis constitutes a novel regulatory pathway and therapeutic target that governs complement-mediated endothelial injury in ALI. Building on this mechanistic insight, we will test whether targeting Lncenc1 and CD59 can restore endothelial barrier integrity and improve clinical outcomes in murine models of ALI.

Funder: NIH 

Amount: $2,785,420 

PI: Duo Zhang, College of Pharmacy 

For decades, a major challenge in the field of engineering education has been closing the gap between research on effective educational practices and the educational practices engineering

instructors actually use. This need has become more acute in recent years, as engineering faculty need strong support systems to gain the skills they need to prepare students for an AI-forward workforce. Fortunately, a handful of engineering education centers (EECs) have deployed faculty development approaches that take major strides in closing this research-and-practice feedback loop. Each EEC’s approach to faculty development is different, and each has found success at its home institution. Through this project, I will study six of these EECs to understand what about their institutional contexts has allowed their faculty development approaches to be successful in closing the research-and-practice feedback loop. I will develop the novel Model for the Context-Rich Integration of Scholarship and Practice (CRISP Model), a visual model that maps different kinds of faculty development approaches and outcomes to the institutional factors that support them. The CRISP Model will empower other EECs in the United States to develop programs that better support engineering faculty to close the research-and-practice loop. I will pilot the model’s use through yearlong, collaborative program development and deployment projects with two such EECs. The CRISP Model will form the foundation of my long-term career, where I aim to create a world in which every EEC in the U.S. has dedicated infrastructure to facilitate the integration of educational research and practice across engineering disciplines. The integrated nature of the project’s research and education plan, coupled with its connection to my career goals, aligns the project strongly with the purpose of the CAREER program. My research plan will use a qualitative multiple case study methodology to study six EECs with dedicated programs to support the integration of research and practice. I have already formed partnerships with all six EECs. I will visit each EEC to observe its programs and to interview center leadership and program participants to understand the EEC’s institutional context and how it contributes to the EEC’s success. I honed this case study methodology through my dissertation work as an NSF Graduate Research Fellow and through recent pilot work. The study is grounded in an appropriate theoretical framework (“Four Frames”) that identifies important categories of contextual factors to study. My education plan collaborates with EECs to create lasting and sustainable changes at their institutions. Following an application process, I will work with two EECs to co-design programs tailored to their institutional contexts, using the CRISP Model as a guide. Each EEC will receive a subaward to fund the development and implementation of its programs, and the project’s evaluation plan will collect data that EEC leaders can use to negotiate continued program funding with their institution’s leadership. This education plan will use a propagation-oriented approach and will take advantage of both my research plan findings and my experience as an EEC leader. In terms of intellectual merit, my research plan will develop the CRISP Model using well-established methods in which I have extensive experience, and the education plan will allow me to evaluate the model’s efficacy in real-world applications. In terms of broader impacts, the CRISP Model will establish infrastructure by empowering EECs to develop programs that support the integration of educational research and practice in a way that aligns with their institutional contexts. My education plan will improve STEM education by deploying the CRISP Model to develop new programs, potentially impacting thousands of engineering students through improvements to engineering education practice.

Funder: NSF  

Amount: $501,998 

PI: John Morelock, College of Engineering 

Healthy oceans support economic stability, coastal communities, food security, and sustainable management of marine resources. Yet one of Earth’s largest and least understood ecosystems lies hidden beneath the sea floor, where microorganisms survive under extreme conditions of limited energy, high pressure, and scarce nutrients. This project investigates offshore freshened groundwater systems beneath the New England Shelf, a largely unexplored environment that links terrestrial, marine, and subsurface ecosystems. By studying how microbial communities survive and function in these hidden habitats, this project improves understanding of processes that influence nutrient cycling, water quality, and Earth’s long-term biogeochemical systems. Using samples collected during a recent ocean drilling expedition, this project examines the diversity, activity, and ecological roles of microorganisms living across subsurface salinity gradients. This project also trains undergraduate graduate and postdoctoral students, promotes workforce development, and makes all resulting data publicly available to support future discoveries in ocean sciences.

Offshore freshened groundwater reservoirs represent a poorly understood interface linking terrestrial, marine, and subsurface environments. Despite growing recognition of their global occurrence, the microbial ecology and biogeochemical functions of these systems remain largely unexplored. This project leverages sediment and porewater samples collected during the International Ocean Discovery Program (IODP)-NSF Expedition 501 on the New England Shelf to investigate how salinity gradients influence microbial community structure, metabolic potential, and ecosystem function in subseafloor environments. This project employs an integrated multi-omics framework combining metagenomics, metabolomics, viral ecology, and geochemical analyses to characterize microbial communities across contrasting salinity regimes. Metagenomic analyses resolve taxonomic composition, functional gene inventories, and metagenome-assembled genomes, providing insight into the evolutionary and metabolic strategies that enable microbial persistence in energy-limited subseafloor habitats. Metabolomic profiling, coupled with geochemical measurements, identifies active biogeochemical pathways and microbial transformations occurring across the freshened groundwater-marine transition zone. This project further incorporates viral diversity and viral-host interaction analyses to evaluate the role of viruses in shaping microbial community structure, metabolic function, and carbon and nutrient cycling within the deep biosphere. Together, these complementary datasets provide the first systems-level assessment of microbial ecology in offshore groundwater environments and establishes a mechanistic understanding of how salinity gradients influence microbial adaptation and biogeochemical processes beneath the seafloor. By advancing knowledge of microbial life in one of Earth’s least explored biomes, this research strengthens the scientific foundation of deep biosphere studies and improves understanding of the role of subseafloor microorganisms in global biogeochemical cycles.

Funder: NSF 

Amount: $588,284 

PI: Avishek Dutta, Franklin College of Arts and Sciences, Department of Geology 

Successful preparation of PhD-trained biomedical researchers is essential to advance human health and well-being, yet high rates of attrition and deteriorating student well-being in PhD programs undermine preparation of this important workforce. A PhD student’s relationship with their faculty research mentor is the single most influential factor in the quality and success of their graduate training, both positively and negatively, such that negative experiences with mentors undermine students’ personal and professional growth. My research program addresses these issues by understanding factors that promote and hinder effective research mentoring relationships and using this knowledge to develop novel interventions to enhance faculty mentoring abilities and bolster graduate students’ experiences and success. Our research has revealed two avenues with strong potential to improve mentoring effectiveness: (1) cultivating a sense of similarity between faculty mentors and student mentees and (2) coupling a shift in faculty beliefs about mentoring with skill-building to communicate more productively about conflicts. These avenues leverage extensive research in social psychology and communication that has yet to be applied to research mentoring relationships. Over the next five years, I will evaluate two research-based interventions with strong potential for replication and scaling: a similarity-promoting intervention and a beliefs and skills intervention. Studying these interventions will yield insight into their effectiveness for improving mentoring relationships and their outcomes, including students’ research productivity, faculty and student well-being, and students’ time-to-degree and degree completion. This research will also produce mechanistic insights about research mentoring relationships by addressing two key research questions: (1) How can we foster high quality, productive mentoring relationships between faculty advisors and their PhD students through increasing perceived similarity? and (2) How can we sustain positive graduate mentoring relationships and outcomes by promoting faculty motivational beliefs and building their communication skills? I will accomplish this by conducting a series of randomized controlled trials that involve collection and analysis of longitudinal data from local and national samples of biomedical research faculty and their PhD students. This research will yield much needed knowledge about the development and maintenance of research mentoring relationships; address important limitations in the study of mentoring; and provide the foundation for large-scale interventions to advance the biomedical research enterprise by equipping faculty with dispositions and skills to mentor effectively.

Funder: NIH 

Amount: $1,710,000 

PI: Erin Dolan, Franklin College of Arts and Sciences, Department of Biochemistry and Microbiology 

This proposal seeks to develop the theme of the restriction of side chain conformation as a broad and general means of enhancing the potency and selectivity of glycoside hydrolase, nucleoside hydrolase, nucleoside phosphorylase and glycosyltransferase inhibitors. It builds on extensive work in the Crich laboratory that unearthed the principles by which the side chain of glycosyl donors contributes in a conformation‐dependent manner to their reactivity and selectivity, resulting in the formulation of a set of simple predictive guidelines. The proposal innovates by applying these guidelines to the design of new and improved inhibitors for a wide range of carbohydrate processing enzymes through the preorganization of the inhibitor side chain to that exploited by the said enzymes. Multiple ways to limit side chain conformation in multiple classes of such inhibitors will be explored with the hope of improving both efficacy and selectivity. The significance of these investigations derives not only from the obvious development of improved and more selective inhibitors, but also from the building of bridges between carbohydrate chemists and biochemists through the demonstration of the common principles of reactivity employed by nature and synthetic chemists alike. This in turn places the subject on a much more solid physical organic basis, thereby demystifying it for non‐specialists and facilitating their entry into the ever more important glycoscience field.

Funder: NIH 

Amount: $2,052,103 

PI: David Crich, College of Pharmacy 

Emerging infectious diseases are among the greatest threats to global health, as shown by recent emergences of Ebola, Zika, avian influenza, and coronaviruses. Although zoonotic outbreaks are recognized as a One Health challenge, most research has focused on single pathogens, retrospective studies of animal hosts, or on human-centered transmission dynamics. This siloed approach neglects how upstream drivers such as wildlife epizootics and hidden host- specific zoonotic burdens influence spillover risk, as well as the ecological and social conditions that transform small spillover events into large epidemics. Without an integrated framework linking animal and human health, pandemic preparedness remains largely reactive rather than preventive. My proposed R35 MIRA program will develop a comprehensive, predictive framework for zoonotic emergence spanning the full cascade from wildlife epizootics to human spillover and outbreak amplification. My hypothesis is that explicitly incorporating animal health measures into models of human disease risk will significantly improve forecasts. To test this, my team and I will integrate large-scale host–virus networks, ecological and demographic data, and advanced statistical and machine learning approaches. We will: (1) identify ecological and environmental drivers of wildlife epizootics, (2) estimate hidden or unsampled viral burdens as well as true total zoonotic burden across animal host taxa, and (3) quantify spillover and amplification risk through a novel standardized epidemic potential parameter that extends beyond R₀. Results will be synthesized into agent-based models, predictive risk maps and early- warning tools validated with influenza and coronavirus datasets. By explicitly linking animal epizootics, host zoonotic burden, spillover dynamics, and amplification risk, this program will generate a multi-stage, data-driven framework for pathogen emergence. Expected outcomes include transformative insights into the upstream drivers of diseases, identification of early warning signals in wildlife health and actionable forecasting tools to strengthen One Health surveillance efforts and pandemic preparedness. Beyond scientific impact, this program will also establish generalizable methodologies and train researchers in advanced modeling, which aligns with the NIGMS MIRA mission to support sustained, flexible, and impactful research with broad relevance to human health.

Funder: NIH 

Amount: $2,414,038 

PI: Mekala Sundaram, College of Veterinary Medicine