University of Minnesota-Twin Cities

NSF Awards · FY 2025 · 2025-05

This project, in collaboration with researchers at the University of Cambridge, aims to investigate a highly sensitive, low-cost sensor platform to detect circulating tumor DNA (ctDNA), a key biomarker for early cancer diagnosis, particularly in non-small cell lung cancer (NSCLC). By combining microwave photonics (MWP) with polymer-based micro-ring resonator technology, the platform addresses current limitations in cancer diagnostics, such as high costs, slow processing times, and the bulky nature of existing systems. This innovation promises to make cancer screening more accessible, offering a portable and affordable solution for point-of-care testing. Beyond healthcare, the sensor's versatility enables applications in environmental monitoring, agriculture, and other fields, delivering significant societal and economic benefits through improved efficiency and global resilience to emerging challenges. This project leverages microwave photonics (MWP) and polymer-based micro-ring resonator technology to create a precise, low-cost sensor platform for detecting ctDNA in human blood. The system is designed to address the limitations of current diagnostic tools by replacing expensive tunable lasers with a microwave frequency sweep modulated on an optical carrier. This approach dramatically reduces costs while enhancing precision and scalability. Polymer micro-ring resonators are ideal for this application due to their low manufacturing cost, compatibility with biomolecule functionalization, and ability to integrate seamlessly with microfluidics for lab-on-a-chip applications. These features make the technology suitable for multiplexed analyses of biological samples. However, achieving the high optical quality factor (Q-factor) required for high sensitivity poses significant challenges due to material imperfections, such as surface roughness and optical losses in the polymer resonators. To address these issues, advanced nano-imprint fabrication techniques are employed to minimize surface roughness, improve light confinement, and enhance light-analyte interactions. Additionally, the project employs co-design methodologies that integrate the MWP readout system with the polymer resonator design, ensuring optimal sensitivity and noise performance. Functionalized resonators with DNA-specific probes will enable selective and accurate detection of ctDNA, while integrated microfluidic channels allow for multiplexed analysis of biological samples. This design can achieve detection limits as low as tens of nanograms per milliliter, enabling reliable identification of ctDNA even in trace amounts. Validation of the platform will be conducted through rigorous testing against commercial ctDNA reference materials to ensure reliability and reproducibility. Collaboration among experts in photonics, polymer manufacturing, and oncology ensures a multidisciplinary approach to addressing both technical and clinical challenges. Beyond healthcare, the versatile platform’s modularity allows for adaptation to other fields, including environmental monitoring of pollutants and detection of pathogens in agriculture. This project advances interdisciplinary research in photonics, nanofabrication, and microfluidics while providing a scalable and cost-effective solution for global challenges. By addressing critical technological barriers, such as optimizing Q-factors and employing innovative nano-imprint methods, this project not only enhances the capabilities of polymer resonator technology but also establishes a robust framework for next-generation sensing platforms. This collaborative U.S.-U.K. project is supported by the U.S. National Science Foundation (NSF) and the Engineering and Physical Sciences Research Council (EPSRC) of United Kingdom Research and Innovation, where NSF funds the U.S. investigator and EPSRC funds the partners in the United Kingdom. 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 · 2025-04

In many species, females are choosy about with whom they mate. Variation in how selective females are, termed choosiness, is common. Choosiness shapes which males' genes enter the next generation and plays a key role in speciation. However, despite its central role in numerous evolutionary processes, basic questions about variation in choosiness and its genomic basis remain poorly understood. Using crickets as a study system, this project aims to examine whether females differ reliably in their choosiness for male song and how much of those differences among females reflect their genetics. Using gene expression and genetic mapping experiments, this project also aims to identify candidate genes underlying variation in choosiness. One of the broader impacts of this project explore the use of alternative tools (dance) for teaching animal behavior to college and K-12 students as a complement to typical written and spoken approaches. Choosiness describes how discerning an individual is in mate choice, and the dramatic differences animals demonstrate in choosiness has major implications for selection and speciation. Yet our understanding about variation in choosiness remains poor compared to our understanding of which traits are favored. This imbalance hinders our ability to answer crucial questions about individual differences and whether reinforcement selection could impact choosiness. This project focuses on crickets, in which pulse rate of the male song and female preference for pulse rate are species-specific and under natural selection. The proposed work will estimate intraspecific variation in choosiness for song pulse rate, examine whether there is repeatable individual variation in choosiness, and understand its relationship with variation in other preference traits. This project also aims to quantify heritability in choosiness and to identify the genetic basis of variation in choosiness variation using differential gene expression and genetic mapping experiments. 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 · 2025-04

This I-Corps project focuses on the development of an intelligent, chatbot-based, learning assistant designed to enhance student engagement and self-regulated learning. This technology addresses critical gaps in current digital learning environments by providing students with personalized support, timely reminders, and real-time feedback, fostering better academic performance and retention. By integrating with widely used digital learning management systems, this innovation has the potential to benefit millions of students across diverse educational settings, from K-12 to higher education. Additionally, it offers educators a powerful tool to monitor student progress and provide timely interventions, ultimately improving teaching efficiency. The potential of this project is significant, as educational institutions increasingly seek scalable, data-driven solutions to enhance learning outcomes. By leveraging advanced generative artificial intelligence technologies, this innovation can be adapted for various markets, including online education platforms, corporate training programs, and workforce development initiatives, making it a transformative tool for the future of education. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a generative, artificial intelligence (AI)-powered chatbot that integrates with digital learning management systems to deliver personalized, contextualized assistance to students. The underlying technology leverages large language models, retrieval-augmented generation, and natural language processing to answer student queries, generate customized reminders, and provide contextualized academic support. These techniques enable real-time information retrieval, intent recognition, and adaptive response generation, enhancing student engagement and instructor insights. The project builds upon research on self-regulated learning theory and gamification, incorporating evidence-based strategies to promote student self-regulation and engagement. Initial field experiments have demonstrated promising results, including increased student engagement, higher assignment completion rates, significantly improved academic performance, and positive testimonials from participating instructors. Through iterative testing and user feedback, this project aims to establish a robust, AI-driven solution for promoting learning engagement and self-regulated learning and expanding access to high-quality, chatbot-based, learning support. 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 · 2025-04

The turnover of organic carbon in the ocean plays an important role in regulating the ocean carbon cycle. The oceanic cycles of iron and carbon are tightly coupled. The supply of dissolved iron regulates ocean biology while organic carbon impacts the solubility and biological availability of iron in seawater. We strive to better understand the mechanisms and linkages between pools of iron and organic carbon in the oceans and to predict their sensitivity to future environmental and climatic changes. In this collaborative project, jointly funded with the U.K. Natural Environment Research Council, scientists from the U.S. and U.K. will combine field data from the Bermuda Atlantic Time-series Study (BATS) region and from the Eastern North Atlantic with targeted experimental studies and a state-of-the-art ocean biogeochemical model to better characterize organic carbon - iron linkages and their roles in past, present, and future changes in ocean biology and chemistry. The project will support the education and training of undergraduate, graduate, and postdoctoral researchers, and will connect rural K-12 and undergraduate students with the research through outreach activities. Field observations from the BATS and Cape Verde Ocean Observatory regions will be integrated with experimental studies targeting iron-organic carbon interactions across seasonal and spatial gradients. An ocean biogeochemical model will be used to constrain the processes that modulate interactions of iron with dissolved and particulate organic matter. Specifically, this project will examine the a ‘colloidal shunt’ mechanism, whereby a portion of the dissolved iron pool in the colloidal size range is not stabilized by complexation with organic ligands. This iron instead forms aggregates with organic carbon to form particulate matter that sinks out of the upper water column. The research will focus on the role of dissolved organic carbon and iron-binding organic ligands in mediating the colloidal shunt, the association of organic matter with thus-formed authigenic particulate iron phases, and the dissolution of these phases in the ocean interior as a function of oxygen. Potentially transformative implications of this research are that the colloidal shunt might vary in response to climate driven changes in ocean oxygenation, and that this process may provide a conduit for the vertical export of both particulate iron and organic carbon that augments the biological carbon pump in the subtropical and tropical oceans. 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 · 2025-04

This award supports the participation of graduate students and postdoctoral researchers in the "2025 Rivière-Fabes Symposium on Analysis and PDE" which is scheduled to take place April 25-27, 2025 at the University of Minnesota. The award gives early-career researchers and researchers without other sources of funding a chance to participate in the conference. In this way, the award supports the communication of state-of-the-art mathematical techniques and promotes the development of future generations of scientists working in important, cross-disciplinary fields. The symposium focuses on recent developments in mathematical analysis, this year especially in areas involving geometric measure theory, singularity formation in fluid equations, computer assisted proofs, microlocal analysis and inverse problems, wave turbulence, and statistical physics. More information can be found on the symposium web page https://cse.umn.edu/math/riviere-fabes. 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 · 2025-04

This I-Corps project is based on the development of black soldier flies to produce omega-3 fatty acids. Omega-3 fatty acids are healthy fats found in certain foods such as fish and fish oil supplements. The goal of this technology is to produce a sustainable alternative to fish oils, reducing the overfishing associated with current practices. Unfortunately, the fat product produced naturally from farmed black soldier flies is suboptimal for use in animal feed and is usually disposed of as waste. This technology creates black soldier flies that can produce omega-3 fats that may be harvested and used in pet or livestock feed. This technology addresses these issues by transforming black soldier fly larvae, which are primarily used for protein production, into high-value omega-3 producers. Increasing omega-3 content in black soldier flies may create an economically attractive and environmentally sustainable alternative to fish oil. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of biomanufacturing omega-3 fatty acids in black soldier flies. Omega-3s such as alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are essential for human and animal health but are primarily sourced from fish oil. This technology uses genetic engineering to enhance black soldier flies to produce larvae with an altered fatty acid composition that is higher in the omega-3 precursor linoleic acid and omega-3 fatty acid alpha lipoic acid (ALA). This technology is based on an automated, genetic screening processes, rapid integration of beneficial transgenes, and the creation of stable, genetically modified insect lines. Currently, black soldier flies are farmed primarily for protein production. Farming genetically enhanced black soldier flies producing omega-3 lipids may improve the value of insect farming and solve the economic challenges of insect farming through a scalable biomanufacturing platform. Potential adopters, including nutraceutical companies and animal feed producers, may benefit from a reliable, scalable, and sustainable supply of omega-3 fatty acids, reducing environmental impacts and improving nutritional outcomes across the nutraceutical, agricultural, and pet food industries. 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 · 2025-03

NON-TECHNICAL DESCRIPTION New solid-state materials are essential to advance existing or create new technologies. Materials synthesis remains a crucial bottleneck to the materials discovery process. This project directly addresses this synthesis bottleneck in an emerging class of ternary chalcogenide-based semiconductors. Many materials in this family have been computationally predicted to have excellent properties for solar cells, energy-efficient electronics, and batteries – materials needed to directly and indirectly advance national health and security. However, experimental synthesis of these predicted materials has proven challenging, as only a handful of these materials have been made. This project involves computationally-led experiments and experimentally-informed computational work to understand and design new synthetic approaches to access these materials. The collaborative nature of this project provides a unique training experience for graduate students through their engagement in advanced computational and experimental research. TECHNICAL DESCRIPTION This project aims to discover new ternary chalcogenides for optoelectronic applications by leveraging alternative entropy sources that can enable materials synthesis. Many ternary chalcogenides have been predicted to be thermodynamically stable and exhibit compelling optical or electronic properties. Yet, only a small fraction of these predicted compounds have been experimentally synthesized. This project operates under the hypothesis that synthesis of these materials requires careful control of thermodynamic driving forces through entropic factors to prevent competitive compositional decomposition reactions or polymorphic transitions. Specifically, this project employs control over entropy associated with point defect formation, crystal vibrations, and gas evolution to stabilize and synthesize targeted chalcogenide materials relative to competing binary reaction products or polymorphs. The synthesis science discoveries have potential to apply broadly to other classes of materials. This collaborative project leverages first-principles thermodynamic calculations to lead experimental synthesis and characterization, as well as experimental work to inform computational efforts. Together, this project provides comprehensive training to student researchers in solid-state materials chemistry. 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 · 2025-03

Population movements have dramatically changed the composition of human groups. While some groups’ population and evolutionary histories have been studied, others are still in need of further examination. This doctoral dissertation research examines the composition and evolution of a past population and its living descendants by combining ancient as well as modern DNA analyses. Analyses of past individuals will trace maternal ancestry, whereas biparental ancestry will be examined in modern descendants. These findings enhance our understanding of human genetic variation and the ways in which historic events shape the genomes of contemporary groups. The study is designed in partnership with the descendants and provides training opportunities for students. This study collects and analyzes genetic data from ancient and modern contexts, to shed light on the evolutionary histories of a past population and its modern descendants. The researchers collect ancient mitochondrial DNA data from past individuals, as well as genome-wide single-nucleotide polymorphism (SNP) data from present-day peoples living in the same area. The project uses these data to investigate three main topics: maternal ancestry, through mtDNA, in past and present-day peoples, and biparental ancestry patterns (SNP data), as well as evidence of genetic adaptation in immune-related genes in present-day individuals. By integrating ancient and modern DNA, the project sheds light on how population movements influence patterns of genetic ancestry and signals of selection. 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 · 2025-03

This award will provide partial support for U.S.-based graduate students and postdocs to participate in the Young Geometric Group Theory XIII conference, to be held in Copenhagen, Denmark, from April 7-11 2025. The purpose of this international conference series is to expose early-career researchers to cutting-edge research, provide them with opportunities to share their work, and to facilitate new collaborations. The conference includes mini-courses by established experts, plenary talks by early-career researchers, lighting talks and a poster session for participants, and group discussions. The conference will give an opportunity for early-career geometric group theorists to publicize their research and strengthen their position in the field. The activities will also foster community and enable networking and interactions at all levels. Geometric group theory is a fairly young and very active field, and the selection of mini-course lectures and speakers at this conference will reflect a variety of subtopics within geometric group theory as well as a diversity of identity, background, and geographical location. There will be four mini-courses on the topics of free and free-by-cyclic groups by Radhika Gupta, Helly graphs and non-positive curvature by Thomas Haettel, L2-invariants of groups by Clara Loh, and finiteness properties of groups by Brita Nucinkis. These lectures will present a panoramic overview of some of the important developments in geometric group theory. The plenary presentations will aim to focus on other recent research and directions to broaden the scope of the workshop, and to encourage the participants to explore the boundaries of the subject. More information about the conference can be found on the conference website: https://sites.google.com/view/yggt2025 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 · 2025-03

This I-Corps project focuses on a permanent solution for people who have high blood pressure caused by stiff arteries. Stiff arteries affect up to 20 million people over the age of 60. The solution is a medical device that is implanted through minimally invasive procedures, serving the patients who are not responsive to medication. The treatment population can benefit from a higher quality of life and a lower risk of complications including stroke, heart failure, heart attack, kidney failure, and vision loss. In addition to increased patient health, this solution can result in a reduction of expensive surgeries associated with cardiovascular diseases and strokes. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This technology is based on the development of a physical approach to reduce systolic blood pressure. Within a pulse of blood from the heart, energy is usually distributed through the arteries due to their compliance. However, as people age, the arteries stiffen, leading to reduced buffering of this pulse wave and ultimately to isolated systolic hypertension. This disease is difficult to adapt to, since it stems from a physical change in the molecules that make up the walls of the blood vessels. The solution restores the native compliance of the blood vessels using an implantable device, which then brings the patient's blood pressure back to a healthy state. This solution differs from current treatments by directly treating stiff arteries, which are one of the most critical risk factors for the development of cardiovascular diseases. 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 · 2025-03

In nature, bacteria either swim freely to search for food or attach to surfaces, forming biofilms. Biofilms are groups of bacteria that stick together via secreted polymers and can be found on many surfaces—from rocks in streams to medical devices. While sometimes beneficial, biofilms often cause problems in industrial and medical settings because they are hard to remove and resist antibiotics. Understanding how bacteria interact with biofilms and switch between swimming/non-swimming states is crucial for controlling harmful biofilms. However, studying these interactions has been challenging due to the lack of tools that can observe both types of bacteria simultaneously. This project aims to develop HoloCon, a new imaging tool that combines three-dimensional holographic imaging and fluorescent microscopy, allowing scientists to see both free-swimming bacteria and biofilms in three dimensions and observe their interactions in real time at the single-cell level. HoloCon will visualize and quantify both bacterial populations in one setup, explaining how resident biofilms repel free-swimming cells attempting to colonize and invade them—a common scenario in natural environments like the ocean. HoloCon will be widely useful to researchers observing cell dynamics at high spatial and temporal resolutions, and to others imaging cell or particle trajectories in complex three-dimensional environments such as tissues. The Broader Impacts of the project include its intrinsic merit as the project could impact the work of microbiologists, cell biologists, and developmental biologists. Research tasks will be integrated with educational missions to train future scientists and engineers and inspire public interest through classes, research, and outreach activities in high schools. The major goal of the proposal includes both the development of a new tool for cell biology studies and the scientific discoveries enabled by the new tool. Specifically, in Aim 1, an innovative imaging tool named HoloCon will be developed, which represents the first system capable of simultaneously capturing 3D images of rapidly swimming bacteria and monitoring the dynamic evolution of biofilm architecture at single-cell level. HoloCon is composed of three integrated modules: a real-time 3D particle tracking module based on digital in-line holography (DIH) integrated with machine learning, a customized spinning disk confocal microscope module that receives information from DIH, and a fully integrated data analysis module ready for the research community to use. Aim 2 centers on addressing the key scientific questions of how resident biofilms repel free-swimming cells attempting to colonize and invade the biofilm. New information revealed by HoloCon with be combined with bacterial genetics, biochemistry, and surface engineering tools to paint a comprehensive picture about the interactions between the sessile and planktonic bacterial populations at sub-micron spatial resolution and <10 ms temporal resolution. The central hypothesis is that the interaction between a swimming cell and an established biofilm depends on the swimming behavior of the invading cell, the topography of the resident biofilm, and the biochemical interactions between cells and the extracellular matrix. Revealing the resistance mechanism to biofilm will add significantly to our understanding on the competition between bacterial populations in nature, and on how ecological functions are tightly coupled with the cell biology of individual bacterium. 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 · 2025-03

Rock Magnetism is a research field within Earth and Planetary Sciences. It helps scientists study Earth's interior, its crust, past plate movements, critical mineral deposits, and processes on other planets. The 14th Institute for Rock Magnetism conference brings together prominent scientists to discuss state-of-the-art research and ideas on these topics. The themes of this meeting include using rock magnetism to find and understand critical mineral resources, the use of artificial intelligence to improve the interpretation of data and increase data analysis efficiency, and the magnetic properties of rocks from the Moon and Mars. Research on magnetism and magnetic materials is advancing in geophysics, geochemistry, nanoscience, and condensed-matter physics, especially where these fields overlap. Interdisciplinary discussions on recent developments in fundamental rock magnetism and its applications in geosciences will enhance our understanding of Earth's geological history, critical mineral resources, planetary processes, and the integration of artificial intelligence and machine learning to fully harness rock magnetic data. A three-day conference for 50 participants will be held in June 2025 at the University of Minnesota and will consist of two keynote lectures on topics at the intersection of geoscience disciplines, 16 extended presentations across four thematic sessions, a poster session, and a workshop on using newly developed rock magnetic data analysis software. The conference will bring together senior scientists, early career scientists, and students, with the aim of providing younger scientists the opportunity to build connections with established scientists to enhance their education and develop their careers. 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 · 2025-03

This research brings together ideas, techniques, and insights from two long-standing programs in mathematics: scissors congruence and algebraic K-theory. Scissors congruence originated in Hilbert's 3rd Problem, which asks when two polyhedra in three-dimensional space are "scissors congruent," meaning one can be obtained from the other by cutting it into smaller polyhedra and reassembling in a different way. This question, together with its solution by Dehn, initiated an extensive program of research. Over the past 120 years these ideas have grown and now connect to almost every branch of geometry. Ground-breaking recent work provides a fundamental link between this program and algebraic K-theory, which is itself a deep and rapidly developing area of research. Algebraic K-theory intertwines three major fields of mathematics: topology, algebraic geometry, and number theory. Developing the connection between scissors congruence and algebraic K-theory will significantly advance research in both. This work also provides the platform for striking new research avenues that will bring to bear the tools and techniques of modern algebraic K-theory research on a wide range of geometric questions. This project additionally includes a number of efforts to support students and new researchers in the field, expanding and broadening access to these innovative ideas. This broad new program of research develops the foundations of combinatorial, or "cut-and-paste," algebraic K-theory, applies these new tools to resolve outstanding geometric questions, and expands the scope of combinatorial K-theory to new applications. It brings modern techniques in algebraic K-theory to the emerging K-theoretic approach to cut-and-paste invariants, and applies this approach to a variety of problems in algebraic topology, differential topology, and algebraic geometry. Algebraic K-theory has seen a stunning revolution in the last thirty years due to the invention of trace methods, but these tools have not yet been developed for combinatorial K-theory, a deficiency that this project hopes to remedy. This requires developing the foundations of this new theory and exploiting connections to equivariant homotopy theory. New computational and analytic tools for combinatorial K-theory will lead to progress on a wide variety of geometric problems, including applications to manifolds and invertible TQFTs, varieties and motivic measures, and fixed point theory. Many questions in these fields have natural interpretations in terms of cut-and-paste invariants. 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 · 2025-01

Non-technical description: Hydrogels are squishy, sponge-like materials with significant potential in medicine and environmental science. Hydrogels are used for wound healing, drug delivery in the body, and even to clean up pollution. Made from long chains of molecules called polymers, hydrogels hold large amounts of water and change shape or function depending on their design. However, designing the most effective hydrogels for specific applications is a complex challenge. Traditional testing methods are slow and expensive, making it difficult for researchers to quickly and efficiently identify the best hydrogels. This prevents effective hydrogel materials from being developed for many critical applications. This proposal aims to leverage two innovative techniques, barcoding and pooled screening, to accelerate the testing and development of hydrogels. The principal investigator proposes to barcode individual hydrogel materials with unique identifiers, like product barcodes in a store. These barcodes are chemical markers that can be used to track and distinguish hydrogels. Instead of testing each hydrogel separately, barcoded hydrogels can be grouped, or pooled, together and exposed to the same test conditions, saving time and resources and lowering experimental variability. The barcodes make it possible to track the performance of each hydrogel individually. This proposed method will provide a way to test up to hundreds or thousands of hydrogel designs in parallel, enabling rapid evaluation and comparison of hydrogel performance. This approach aims to speed up the discovery of improved, functional hydrogels for medical and environmental applications. This project will also give middle school students the opportunity to learn about hydrogels through hands-on demos. The principal investigator also plans to introduce biomaterials into core college courses and create a new elective class to introduce students to exciting careers in the field of biomaterials. Technical description: Hydrogels are versatile biomaterials made of hydrated, cross-linked polymer networks used in tissue engineering, drug delivery, and environmental applications. However, their complex design and vast parameter space make it challenging to identify generalizable design principles through traditional, low-throughput methods, slowing and preventing the development of functional hydrogel materials. High-throughput techniques like barcoding and pooled screening can accelerate the discovery of structure-function relationships. While these types of approaches have not yet been applied to hydrogel-based biomaterials, there is significant potential to advance this field to the same extent. This CAREER proposal aims to leverage a molecular barcoding platform pioneered by the principal investigator for systematic evaluation of hydrogel parameters in a pooled, combinatorial manner. This approach will enable the assessment of material properties such as degradation and cargo release and help establish generalizable design rules for diverse hydrogel systems. By utilizing cost-effective, commercially available barcoding reagents and mass spectrometry-based detection methods, the proposed approach offers a standardized, high-throughput tool accessible to the hydrogel community. Additionally, it will streamline data harmonization and automate workflows. The research focuses on four main areas: (1) examining how polymer and linker designs affect hydrogel degradation, (2) studying the impact of biomolecule size and charge on release from hydrogel matrices, (3) developing and characterizing hydrogel sorbents, and (4) automating screening workflows. This proposal also aims to promote diversity in STEM and expose students to biomaterials-related careers, particularly in the local medical device industry through a multi-tiered educational program that includes the integration of biomaterials course modules into core undergraduate courses, development of an elective biomaterials course, and a STEM outreach program for middle school girls. 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 · 2025-01

The Imola (Intelligent Map recOgnition LAb) project develops advanced computational methods and scientific approaches to extract historical geographic information from scanned maps originally published by the US Geological Survey between 1884 and 2006. The project transforms historical road networks in these maps into a database that allows scientists to study the evolution of transportation networks and how humans interact with their environment over extended time periods and geographical regions prior to the era of satellite imagery. Extracting detailed geographic information from historical USGS topographic maps is a difficult task. The Imola project uses a new intelligent system called DaVinci to automate the extraction process and produce a large spatiotemporal database of historical road networks called US1884+. DaVinci reads maps like humans by automatically exploring geographic features in maps and in other datasets to generate more information related to historical road networks to then extract them. The DaVinci method eliminates the need for large, manually created training data and provides a way to measure uncertainty in the features extracted from the maps, which is important for conducting research with the data. The project provides a case study and creates tutorials to demonstrate how the US1884+ platform can be used in scientific research and how it advances knowledge of how humans interact with their environment. 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 · 2025-01

Digital Twins–virtual models of physical systems–have garnered growing attention in recent years, driven by rapid advances in sensing, communications, computing, machine learning and artificial intelligence, and hold the potential to vastly accelerate scientific discovery and revolutionize many industries. In particular, Digital Twins play a fundamental role in designing, managing and optimizing 5G wireless networks and will be essential in enabling next-generation 6G wireless networks. Despite recent advances in realistic channel modeling, there are still many fundamental challenges in developing fit-for-purpose Digital Twins for next generation wireless networks that can seamlessly integrate data for informed decision making, and can be dynamically updated as the physical environment varies and network operational objectives change. Motivated by these challenges, the team of investigators develops novel mathematical theories, and new data-driven, AI-guided models and algorithms that will lay the mathematical foundations for digital twinning of next generation wireless networks. The award also supports undergraduate and graduate students from underrepresented groups in research and educational activities as well as organization of K-12 outreach programs. This proposal aims to advance the mathematical foundations of next generation wireless network Digital Twins. The investigators will place the ray tracing problem–essential to such digital twins–in the more general framework of first order Hamilton-Jacobi equations, and will make theoretical and algorithmic advances in data-driven learning of Hamilton-Jacobi equations. The research team will prove optimal sample size complexity bounds for learning Hamilton-Jacobi equations and their solutions from data, and develop algorithms for achieving these bounds, in both the static and active learning settings. They will develop a temporal surface reconstruction algorithm that combines temporal LiDAR and video camera information by leveraging neural kernels and transport equations. In order to quantify the uncertainty in their results, the investigators will establish posterior contraction rates for learning Hamilton-Jacobi equations, and develop methods to construct and analyze Bayesian credible sets and perform scalable posterior sampling. Finally, the investigators will integrate their theoretical and algorithmic advances into a next generation wireless network Digital Twin platform that will be evaluated in both controlled and dynamic real-world environments. 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 · 2025-01

The broader impact of this I-Corps project is the development of a pain assessment and intervention recommender technology. This technology is designed for the person who lives with post-amputation pain, a growing population worldwide due to trauma or vascular disease (e.g., diabetes, peripheral vascular disease). People experience a range of pain following amputation, including residual limb pain (i.e., pain felt in the remaining limb) and phantom limb pain (i.e., pain felt in the part of the limb that no longer remains). Phantom limb pain affects up to 86% of individuals with amputation and results in added health care expenses in the first year following amputation. In addition to being prevalent, amputation-related pain is associated with poorer health outcomes, interference with life activities, anxiety, and depression. While many treatments exist, success rates with treatments vary, and it is not clear how to optimize treatment prescription. Long-term, the application of the pain assessment and intervention recommender technology can include other chronic pain populations such as chronic low back pain or fibromyalgia, thereby expanding the commercial potential of this project. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a pain assessment and intervention recommender technology. Current standards for assessing pain involve patient reports during a clinic appointment. However, these reports can be affected by recall bias and the clinic environment. This technology enables the patient to have a real-time assessment that occurs in their home environment. The assessment can be performed virtually, which has the potential to improve care for all patients regardless of their proximity to services. The results are processed through a recommender platform that uses machine learning algorithms to generate a personalized recommendation for intervention. The goal of the recommended intervention is to increase the patient's ability to participate in desired roles and activities through effective pain treatment. The pain assessment and intervention recommender has the potential to guide more effective treatment recommendations, reduce clinical follow-up visits, and improve accessibility for patients in rural areas. 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 · 2025-01

Today’s world is increasingly driven by advanced electronic integrated circuits, or chips, which power artificial intelligence (AI), infrastructure, mobile communications, scientific computation, and consumer electronics. The computations in a chip are facilitated by supply voltages that are distributed to the computational elements through power distribution networks (PDNs). These PDNs consist of structures that carry large currents through lossy filamentous wires, which may be inadequate for ensuring robust voltage levels at the computational elements. These effects can potentially lead to incorrect computations and unacceptable errors. Moreover, high currents can cause accelerated aging in the PDN due to phenomena such as electromigration (EM) that can result in chip failure. Developing optimization strategies that ensure supply voltage integrity and PDN reliability is therefore critical. The task is further complicated with the challenges associated with emerging methods for building advanced integrated circuits, including new wire and transistor structures, and elevated on-chip currents and temperatures that degrade performance and reliability. Therefore, the development of PDN design techniques is vital for enabling the next generation of chips that drive computation from the datacenter to the edge. This project aims to address the challenges of optimizing voltage drop and EM in PDNs, while ensuring minimal utilization of the limited available on-chip wiring resources. For the problem of voltage drop, the work will address today’s widely used front-side interconnects as well as newer backside interconnect technologies. Degradations in supply voltages can also cause circuit delays to deteriorate: the interplay of PDN optimization on circuit timing in digital circuits will be addressed in this project through new approaches that break down the barrier between PDN design and timing optimization, performing integrated optimizations that benefit both PDN resource usage and logic circuit metrics. To address EM, this research will advance the use of physics-based approaches that predict chip lifetimes by directly modeling EM-induced stress in interconnects. New methods will be developed based on a stress-electrical duality that maps accurate physics-based stress analysis to methods for analyzing resistor-capacitor (RC) networks and transmission lines. An educational component of the project aims to attract fresh talent to advance the mission of workforce development in the field of electronic design automation. Specific efforts will target students at the K-12, undergraduate, and graduate levels, and intend to attract women and other underrepresented minority groups. Outreach activities will be centered around artificial intelligence and semiconductor technologies, and will be supplemented by curriculum development efforts. 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 · 2024-12

Learning a structural model of dynamic decision-making helps us better understand and predict how agents, whether human or machine, make decisions over time in changing environments. Instead of just copying actions, this approach allows us to capture both the agent’s goals (preferences) and how it understands the world (environment dynamics). This provides a much deeper insight into behavior, enabling predictions about how the agent would act in new or unseen situations. Such models are valuable because they can help improve decision-making systems, allowing them to adapt and make reliable choices in complex real-world scenarios, such as personalized AI assistants, autonomous systems, or decision support tools. There is an urgent need for models and algorithms that can create such structural frameworks. The outcomes of this project will have broad applications, including areas like control systems, natural language processing, and autonomous driving. Moreover, these efforts offer valuable opportunities to enhance the optimization and reinforcement learning curriculum, engaging students from diverse backgrounds in cross-disciplinary research and K12 outreach initiatives. This project develops machine learning models of an agent’s dynamic decisions subject to structural constraints on observed behavior. Specifically, the agent’s observed behavior (data) is modeled as being consistent with the inter-temporal optimization of a reward function (preferences) given a representation of how the environment evolves pursuant to control actions (dynamics). Unlike behavioral cloning models, a structural model of observed control behavior is a solid basis to perform counterfactual analysis and/or transfer learning. However, developing structural models of control is computationally challenging and the statistical properties of structural estimators are not easy to characterize. This project aims to advance the state-of-the-art on methodologies for learning structural models of control, by considering a diverse set of data (including demonstration and preferences), and by considering both online and offline settings. Finally, extensive experiments will be conducted to evaluate and apply the proposed methodologies in aligning large language models (LLMs), and in autonomous driving. 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 · 2024-12

The 2025 IEEE North American School for Information Theory (NASIT 2025) will be held at the University of Minnesota in Minneapolis, from June 16th to June 20th, 2025. This grant provides support for the expenses of school participants from the United States such as graduate students and postdoctoral fellows. Attendees will benefit by learning from senior colleagues, presenting their own research in poster sessions, and expanding their network with the research community. This award will cover accommodation and travel for students. The IEEE North American School (NAS) for Information Theory is an annual event of the IEEE Information Theory Society; 2025 will be the 17th year the school will have held the event. The NAS provides a supportive environment where foundations for learning and long-term future scientific collaborations are established. NAS delivers interactive education for graduate students in mathematics, engineering, and computer sciences. It presents students the opportunity to meet and learn from senior researchers in academia and industry who present long-format tutorials. Student and postdoctoral participants present their research results in poster sessions. 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 · 2024-12

The broader impact/commercial potential of this I-Corps project is the development of a pediatric manual mobile standing wheelchair, a novel wheelchair that allows children with a neuromuscular condition to transition between standing and sitting and move manually throughout their day whether at home or school without need for additional equipment or caregiver assistance. School systems that are required through federal mandates and Individual Education Plans to support children in wheelchairs and their medical need for daily standing would benefit from a pediatric manual mobile standing wheelchair. Families with children with neuromuscular conditions will similarly benefit. This novel wheelchair reduces the number of pieces of specialized equipment needed in the school or at home, reducing both cost and space demands as well as reducing the number of staff members/caregivers and time needed to assist the children in transitioning between and using each piece of equipment. Finally, a pediatric manual mobile standing wheelchair may have significant health benefits for children with neuromuscular conditions including the health benefits from frequent standing (bone density, muscle and tendon length, respiratory and cardiovascular health, and more) and the psychosocial benefit of increased independence and participation. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a pediatric manual mobile in stranding wheelchair. The Pediatric Manual Mobile Standing Wheelchair is a novel mobility device that allows children with disabilities to navigate their environment in either a seated or standing position. The ability to stand or sit in a single device reduces the need for multiple pieces of equipment and decreases caregiver demands by eliminating the requirement to complete several daily transfers between devices. Offering the ability to manually move in both the seated and standing position is theorized to increase compliance with therapeutic standing programs and thereby augment the positive health outcomes associated with regular standing. In addition, the ability to move in either a standing or seated position facilitates greater participation and independence in activities of daily living. The technology was developed via a collaboration between the University of Minnesota and the Minneapolis Veterans Affairs Medical Center. 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 · 2024-12

The design of materials and structures has become increasingly dominated by the adoption of optimization methods, which allow maximizing certain measures of mechanical performance, such as stiffness and energy absorption. Optimization is crucial in engineering applications involving components that are expected to execute complex mechanical operations, such as aerospace systems, biomedical devices and soft robotics. Together with the fabrication flexibility in additive manufacturing, optimization boosts the opportunities for design by tapping into a nearly unbounded design space. This award supports research with the goal to design structures that can be programmed to display variable levels of material softness and rigidity, allowing them to manage, intelligently, the loads applied by the outside environment. The advances enabled by this study will affect many technological applications of industrial and societal interest, such as the design of tires space vehicles or operating in hazardous environments, protective equipment that can sustain impacts from projectiles, and soft robotic devices with sensing capabilities. The knowledge will enrich understanding of important concepts in mechanics and optimization, with educational impact on how these topics are taught in the classroom. Topological metamaterials are systems whose functionalities are controlled and protected by the topology of their phonon bands. They display unconventional elasticity regimes characterized by robustness against defects, damage and randomness. This project is especially concerned with so-called topological polarization, a property of certain lattice materials that manifests as a dichotomy between edges, whereby one edge displays an excess of softness, promoting extreme localization of deformation, while the opposite edge behaves rigidly. This property enables the design of materials with soft boundaries that can handle asperities and sharp loads, without compromising the global stiffness of the entire structure. The project will investigate polarization through the lens of optimization with a double objective: acquiring a deeper understanding of the mechanistic relations between the geometric features of the materials and the emergent polarization, and designing families of metamaterials with maximized and programmable polarization, beyond the canonical kagome paradigm. 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 · 2024-12

The broader impact/commercial potential of this I-Corps project is based on the development of a platform that enables the discovery of highly specific drugs targeting a unique site on G-protein-coupled receptors (GPCRs). GPCRs are a large family of cell surface receptors that play a crucial role in transmitting signals from the outside to the inside of cells. These receptors are among the most important drug targets in modern medicine, with many medications, including beta-blockers, antihistamines, and psychiatric drugs, interacting with specific GPCRs. Nearly one-third of all FDA-approved drugs target GPCRs, representing approximately 30% ($890 billion) of the global pharmaceutical market share. GPCRs are desirable drug targets for two main reasons: their druggable sites are easily accessible, and they directly regulate a wide range of physiological and disease processes. However, conventional GPCR-targeted drugs face limitations in terms of safety and efficacy, restricting the patient populations they can effectively treat. This project proposes a novel drug discovery platform targeting this new GCPR druggable site that could overcome these limitations, enabling the identification of new drug candidates and the development of more effective, safer, and innovative therapies more rapidly. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of the proposed technology. It is based on the prior development of a platform technology that enables drug discovery related activities specific to a new molecular mechanism of action targeting G-protein-coupled receptors (GPCRs) as a new druggable site. Compared to other druggable sites on GPCRs, this site is highly specific in terms of its composition among the 800+ different receptor isoforms. The technology that was developed in the process of characterizing this new site is a platform that enables identification of compounds that target this site. A key component of this platform is a patented high-throughput screening assay that detects nuanced differences in GPCR drug effectiveness that are not detectable using other high-throughput screening formats. 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 · 2024-11

Since 1907, the University of Minnesota’s Itasca Biological Station & Laboratories (IBSL) has offered educational programming and research in the general area of environmental biology. Legions of scientific leaders have trained and conducted research at Itasca. The 50-acre campus is on the eastern shore of the official headwaters of the Mississippi River (Lake Itasca), it sits at the nexus of the three largest Biomes in North America, and it is located inside the second oldest State Park in the United States, Itasca State Park. The scientists visiting IBSL have laid foundations in biology and ecology, and they have applied their research to protect and inform management for a large number of regional natural areas, including 14,000 hectares of old-growth forest in the State Park. These scientists are also increasingly realizing the potential for partnering with Itasca State Park to engage the public across a rural-urban divide and for building relationships with indigenous communities of northwestern Minnesota. The Station hosts >7000 annual users, maintains 64 buildings, manages 45 hectares of land, and employs 8-10 local seasonal staff each year. This is a large portfolio for a field station, but the general trend over several decades has been a drift away from IBSL-led programming, with associated pros and cons. With nearly 100% turnover in the staffing at IBSL in recent years, including two new Directors, and with extensive turnover in administration on the main Twin Cities campus, the timing is very good for planning the road ahead for this field station. A specific planning effort for IBSL will convene an advisory team of 15-25 stakeholders and a professional facilitator over two full days of guided discussion at the IBSL campus. Stakeholders will include the Dean of the College of Biological Sciences (CBS), along with key administrators from CBS, from the Minnesota Department of Natural Resources (including State Park staff), from local/indigenous communities, and from several relevant field stations as external reviewers. A facilitator will help the group focus on research capacity building along with the teaching and engagement portfolios, with an additional sustainability topic area that includes buildings and grounds. This effort will achieve two outcomes. 1) The first core outcome will be a dynamic strategic plan that can act as a guiding document and a sharable vision. This plan will include a near-term plan of action, a long-range outlook, and a specific 5-year core planning document. 2) A second core outcome will be a vocal stakeholder base that can inform and amplify the vision at IBSL. An aspect of planning will focus on supporting and fostering this base network after the planning effort is finished. Change in the face of traditions can be challenging, and this stakeholder group will strategically create bridges to the main campus, to local communities, and to the State. 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 · 2024-11

The conference "D-modules, local systems and applications" will be held in Centre de Recherches Mathematiques (CRM) in Canada, September 16-20, 2024. This award provides partial travel support for early-career researchers from the United States to attend the conference. The exploration of D-modules, the algebra of linear partial differential equations, and their solutions have been at the forefront of numerous groundbreaking advancements in pure mathematics. These include their pivotal role in the resurgence of singularity theory and topology, and their centrality in geometric representation theory. The conference will unite experts from the fields of geometric representation theory, arithmetic geometry and birational geometry, promoting interdisciplinary collaboration and the exchange of the latest developments in these deeply intertwined areas of mathematics. The conference will cover a broad range of topics, include a diverse list of speakers and participants, and highlight the work of early career mathematicians. The central theme of the meeting is to explore how incorporating Hodge structures and additional weight considerations, as exemplified in p-adic geometry, broadens the application scope of the theory of D-modules into new areas. Hodge theory is crucial for applications in geometric representation theory, arithmetic geometry and birational geometry. This well-timed gathering of experts from these areas will impact the community as a whole, stimulating new ideas and fostering lasting connections among researchers in these rapidly evolving fields. More information is available on the conference webpage: https://www.crmath.ca/en/activities/#/type/activity/id/3968. 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.