San Francisco State University

NSF Awards · FY 2026 · 2026-07

This Engineering Research Initiation (ERI) project investigates how the fallopian tube provides the physical environment that supports fertilization and the earliest stages of embryo development. Although embryo culture has improved through advances in chemical conditions, much less is known about the shape and mechanical behavior of the healthy Fallopian tube, even though that environment guides transport, contact, and early development. As a result, widely used culture surfaces remain far simpler and far stiffer than living tissue. By establishing a rigorous foundation for this missing area of knowledge, the project will advance basic science while also informing use-inspired progress in reproductive health and biotechnology. The work aligns with National Science Foundation priorities by promoting the progress of science, advancing national health and welfare, and strengthening the science and engineering enterprise through open data, reusable models, and hands-on research training. In the long term, the results could support improved embryo culture, reduce repeated treatment cycles, and lessen the emotional and financial burden of infertility care. The project will also create research opportunities for undergraduate students and will share data and teaching materials that can be used by researchers, educators, and students across the nation. This ERI project has two integrated aims. First, it will process nine human Fallopian tube micro computed tomography datasets to create the first quantitative atlas and model-ready three-dimensional reconstructions of the inner passage of the Fallopian tube. These reconstructions will measure path tortuosity, cross sectional size and shape, minimum inscribed radius, and fold architecture across major anatomical regions. Second, it will use spherical probe atomic force microscopy on mouse oviduct tissue to measure time dependent and frequency dependent mechanical behavior at cellular depths, including elastic, viscoelastic, and poroelastic response. The work combines segmentation, mesh generation, centerline-based reslicing, quality control, and statistical analysis with indentation experiments designed to resolve properties that earlier shallow measurements could not capture. All datasets, analysis code, and geometric models will be released openly to support reuse in future computational modeling, biomechanics, and reproductive medicine studies. The expected contribution is a validated, scalable framework that links anatomy, tissue mechanics, and embryo culture design, thereby advancing mechanobiology, supporting future translational innovation, and building research capacity in an area of strong national importance. 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 · 2025-10

The widespread adoption of the Internet of Things (IoT) forms a critical foundation for enabling applications in healthcare, transportation, and industrial automation. However, the ultra-dense deployment of IoT devices and their need to transmit sensitive data raise significant challenges for efficient and secure communication. Conventional cryptographic methods are often too computationally intensive for resource-constrained IoT devices. This project explores a lightweight and non-cryptographic framework that secures wireless communication by leveraging the randomness of physical wireless channels, grounded in information-theoretic principles of Physical Layer Security (PLS). To address challenges in dense networks where channel correlation among users is high, the project integrates Intelligent Reflecting Surfaces (IRS), passive devices capable of reconfiguring wireless signal paths, into the system design to improve both security and energy efficiency. In addition to its technical contributions, the project supports national workforce development by providing interdisciplinary research training, enhancing cybersecurity education, and engaging students across multiple institutions. This project investigates a learning-based framework to enhance Physical Layer Security (PLS) and energy efficiency in ultra-dense IoT networks using Intelligent Reflecting Surfaces (IRS). By dynamically adjusting the IRS configuration based on relational information among legitimate users and potential eavesdroppers, the system aims to increase channel disparity and mitigate eavesdropping risk. The research introduces three core innovations: (1) an IRS control strategy guided by inter-device relational states to improve secure communication channels; (2) a friendly jamming mechanism enabled by traffic pattern analysis of inactive users to further suppress adversarial interception; and (3) a secure energy efficiency optimization framework that incorporates long-term fairness across users during resource allocation. The project combines algorithm design, theoretical analysis, and real-world wireless experiments to validate system performance. Its outcomes will provide critical insights into designing adaptive, secure, and scalable communication systems for next-generation IoT 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.

NIH Research Projects · FY 2026 · 2025-09

Project Summary / Abstract The proposed project will elucidate how subcellular compartmentalization of the RNase E endonuclease into bacterial ribonucleoprotein granules (BR-bodies) in Sinorhizobium meliloti contributes to successful host colonization. S. meliloti serves as a model for investigating infection by alpha-proteobacteria, which include human pathogens such as Brucella, Bartonella, and Rickettsia. Understanding the molecular and cellular mechanisms that underpin effective host colonization can provide critical insights for preventing and treating infectious diseases, particularly as bacterial resistance to antibiotics continues to emerge. S. meliloti establishes mutualistic symbiosis with compatible legumes, including the genetically tractable reference species Medicago truncatula, by inducing development of root nodules, colonizing them, and fixing nitrogen in exchange for nutrients from host plants. We found that removing the C-terminal intrinsically disordered region of RNase E in S. meliloti led to ineffective symbiosis, eliciting nodule development but producing etiolated plants that grew poorly compared to plants inoculated with wild-type bacteria. RNase E is an essential ribonuclease involved in RNA processing and decay, and its C-terminal domain, while dispensable for viability, was shown to be necessary and sufficient for the formation of liquid-liquid phase-separated biomolecular condensates, named BR-bodies, in alpha-proteobacteria. Sequestration of RNase E into such BR-bodies facilitates mRNA decay and modulates the cellular RNA pool. The goal of this project is to determine how phase separation of RNase E influences RNA processing in S. meliloti and enables effective symbiosis by accomplishing the following three specific aims. (1) We will assess the symbiotic defects of the RNase E C-terminal deletion mutant in detail by genetic analysis. (2) We will use microscopy to characterize the role of BR-bodies during host colonization. (3) We will examine how transcriptomes differ between wild- type and mutant S. meliloti during symbiosis, as well as compare gene expression profiles of host plants colonized by wild-type versus mutant bacteria. While RNase E has been linked to pathogenesis of various bacteria, including Brucella, relatively little is known about the specific microbe-host interactions involved. Results from the proposed investigation will help identify and provide better understanding of genetic and cellular factors that allow infecting bacteria to bypass host defenses. In addition to accomplishing the scientific objectives described above, this proposal will allow students, particularly those from underrepresented backgrounds, to gain research training and preparation for biomedical careers.

NSF Awards · FY 2025 · 2025-08

Over half of all American college students are low-income or come from families where neither parent has a bachelor's degrees (also known as 'first-generation students'). These low-income and first-generation students disproportionately enroll in broad-access institutions— colleges and universities that accept almost anyone who applies. These students graduate at rates that are half that of students who are not low-income or first-generation. They also end up with larger debt burdens and lower GPAs. Even though such students comprise the majority of American college students, engineering education researchers have paid little attention to them or the institutions where they enroll. This project aims to address that oversight by identifying ways that engineering faculty and staff can better support low-income and first-generation engineering students in broad-access institutions. This project will improve engineering education in broad-access institutions by studying how low-income and first-generation engineering students leverage their unique assets and achieve success in an educational system that has been slow to change to meet their needs. This project will directly impact the educational practices of engineering faculty and staff at broad-access institutions through participation in a community of practice, during which members will work to improve broad-access engineering programs around the United States. Findings from this project will help educators understand how to change their educational practices to better serve all students, particularly low-income and first-generation students. This work will help engineering programs at many different types of institutions develop asset-based strategies for supporting student success for all Americans. This project uses a three-phase research plan that explores how students leverage their assets (operationalized as funds of knowledge and community cultural wealth) to access the resources (social and cultural capital) needed for success within engineering. In Phase 1, it will use longitudinal interviews to understand the processes engineering students engage in to activate and convert their assets into forms of capital in order to succeed in engineering education and professional practice. In Phase 2, the project will explore how faculty and staff perceive the assets engineering students possess and how they believe students can best leverage those assets. In Phase 3, it will use these multiple data sources — engineering students, alumni, faculty, and staff — to create a case study of the experiences of low-income and first-generation students at one U.S. broad-access institution. The findings from this project will support efforts to make wide change within engineering departments serving low-income and first-generation students, particularly those that are broad-access. The research plan makes a significant theoretical contribution by combining funds of knowledge, community cultural wealth, and social/cultural capital to understand how students transmit, convert, activate, and contort their assets into engineering capital. The work's methodological contributions answer calls from leading scholars to improve our understanding of engineering students via one of the first uses of a longitudinal research design to study low-income and first-generation engineering students' and recent graduates' assets and capital; the inclusion of faculty and staff perspectives of student assets; and the selection of the research setting at a broad-access and minority-serving institution. 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 · 2025-07

The project involves application of emerging artificial intelligence (AI) technologies to engage in collaboration with a human. The collaborations involve adaptive goal setting, which is a new frontier in Human-AI Interaction. The project will develop a human-AI system to support individuals with mild cognitive impairments (MCI). At the core of the project are socially assistive robots designed to help patients set their goals in a collaborative way. This work aims to increase the efficacy of these interventions and ultimately improve people's emotional well-being, promote autonomy and self-efficacy, and better their quality of life. The main goal of this project is to develop a transformational goal-centered adaptation framework for autonomous behavior adaptation to support users with achieving real-world goals in longitudinal rehabilitation interventions. Our system will comprise three core properties. First, we will design a goal-setting framework using multimodal, naturalistic data for modeling each user's unique goal progress and motivation based on their diverse real-world behaviors and interactions with a robot. Second, we will develop human-centric approaches for automatically generating and recommending subgoals to support a person's overarching rehabilitation goals. Third, we will develop personalization methods to automatically adapt the behavior of a robot delivering a longitudinal behavioral health intervention to support a user's goal progress and motivation. Ultimately, these contributions will advance the field's understanding of how robots can conceptualize and adapt their behavior to people with cognitive impairments, grounded in current clinical practice. 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 · 2025-07

The electromagnetic spectrum contains all frequencies of light, from those humans can see to those they cannot. This spectrum is used for many types of wireless communication and must be shared when multiple uses occur in close proximity. The electromagnetic spectrum has become increasingly congested, driven by the needs for wireless communication and sensing to support various applications such as smart cities, autonomous vehicles, and Internet of Things. Different wireless systems, such as mobile networks, Wi-Fi, and radar-based sensing devices, must coexist in a limited spectrum band. Although the spectrum at high frequencies promises large bandwidth, it suffers from performance problems such as severe path loss and susceptibility to signal blockages. Thus, managing interference and signal reliability becomes increasingly critical. This project addresses these issues by developing a solution that uses intelligent reflecting surfaces (IRS) to improve spectrum sharing and performance of various wireless systems. IRS is an energy-efficient and programmable surface that can guide radio signals to bypass obstacles and reduce interference. By applying cutting-edge machine learning techniques and considering IRS physics-based constraints, the project aims to increase spectrum utilization and energy efficiency. The outcomes of this research can enhance user connectivity in crowded wireless environments, reduce signal disruptions, and drive application innovations. The project also integrates the wireless and machine-learning research findings into educational programs and provides opportunities to train undergraduate and graduate students through related research activities and hands-on system deployment. This project will develop a multi-IRS-assisted spectrum sharing and sensing framework to enable the coexistence of heterogeneous wireless systems. It explores the following interconnected innovations. (1) A graph neural network (GNN)-based scheme is designed to incorporate environmental information to estimate channel state information (CSI) efficiently and optimize the configurations of IRS reflection elements to direct signals and mitigate interference effectively. (2) A physics-regulated deep reinforcement learning (DRL)-based control scheme is developed to perform real-time fair resource allocation and beamforming under strict quality-of-service constraints among different wireless systems to optimize resource distribution and ensure reliable signal transmissions. (3) System validation is performed through extensive software simulations and testbed experiments. The developed techniques are expected to enhance coordination of multiple IRSs and improve spectrum efficiency and fairness for the coexistence of various wireless systems and applications in dynamic 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.

NIH Research Projects · FY 2026 · 2025-07

PROJECT SUMMARY/ABSTRACT: Retinal sensitivity over the full range of environmental lighting conditions, from dark to bright, is mediated by rod and cone photoreceptors and is fundamental to vision. Importantly, when one type of photoreceptor dies, as in retinal diseases like macular degeneration or retinal dystrophy, the remaining photoreceptor type is unable to fill-in the gap in functionality that remains. This often leads to visual impairment or blindness. Disorders of the visual system that selectively damage photoreceptors affect millions of people worldwide. In the United States alone, age-related macular degeneration is the leading cause of blindness for people over 65 – an affected population that is projected to double in the next 25 years. Other rarer conditions, like retinitis pigmentosa and retinal dystrophies, affect ~1 in 4000 or 5000 people, respectively. Predictably, rescuing lost function in photoreceptors is a major goal in vision restoration efforts. However, the majority of mammalian retinas are “duplex” and have mixed rod-cone populations. Duplex retinas experience a “duality barrier” to restoring function after the selective loss of one type of photoreceptor. Retinas of other vertebrate organisms present us with exciting new opportunities to understand how we could possibly overcome the “duality barrier”. Here, we propose to investigate the pure-rod retina of Leucoraja erinacea (Little Skate), in which a single class of photoreceptor can subserve the full range of rod and cone vision. We have a limited understanding of what environmental and developmental factors govern this functional plasticity in the skate retina, but a detailed knowledge of how this is achieved could hold the key to expanding the functional repertoire of surviving rods or cones in diseased duplex retinas. Based on previous work and preliminary data, we hypothesize that this functional plasticity is driven by developmental programs under the influence of early sensory input, leading to the adaptations observed in the mature retinal circuit. We will test our hypothesis in the following specific aims: Aim 1: To determine what molecular and structural factors govern the establishment of cell circuitry in a functionally plastic single photoreceptor type retina during development. The objective of Aim 1 is to understand how early and late developmental stages shape the establishment of functional plasticity. Aim 2: To determine the role of sensory experience and light adaptation in the formation and function of rod circuitry on the anatomical, physiology, and molecular level. The objective of Aim 2 is to understand the effects of sensory deprivation on the development of a functionally plastic retinal circuit. The proposed research is innovative because it steps away from a traditional mixed rod-cone retina model system and instead studies the functional adaptation of rod circuitry in a naturally occurring pure-rod retina model system. It is significant because it will reveal fundamental principles of functional adaptation in a single photoreceptor type retina, which can lead to novel vision restoration efforts focused on expanding the functionality of surviving photoreceptors.

NSF Awards · FY 2025 · 2025-06

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Emerging Faculty Research Track project at San Francisco State University (SFSU) aims to enhance STEM education while addressing critical healthcare challenges faced by the aging population in the United States. This project aims to develop the fundamental knowledge necessary for an AI-driven, non-intrusive, real-time health monitoring system. The system will use floor vibration sensing technology to extract information about gait, enabling early detection of physical changes that might not otherwise be immediately noticed. By integrating advanced technologies, the system will deliver continuous, personalized monitoring while protecting the privacy of users. In addition to its technical contributions, the project's intellectual merit is rooted in its commitment to strengthening student engagement through both STEM education and research. By engaging students in cutting-edge research, this project creates an environment where students' skills and experiences are recognized as strengths within their research teams. The multidisciplinary nature of this project offers students the opportunity to collaborate, share ideas, and develop solutions to research challenges. The project will employ advanced machine learning techniques to address fundamental engineering challenges, supported by a robust mathematical foundation. Leveraging floor vibration sensing technologies will facilitate several key project outcomes: a robust, data-driven classification model to detect walking events; a deep learning-based model for gait parameter estimation; and general and personalized walker models for real-time monitoring. These advancements could lead to earlier detection of health declines, reduce hospital stays and readmissions, and improve the overall quality of life for aging populations. Complementing these research objectives, the project will impact STEM education by developing learning modules integrated into engineering and math courses at SFSU, providing students with hands-on experience in interdisciplinary problem-solving. Mentorship and professional development programs embedded in the project will provide key support for participating undergraduate researchers. Dissemination efforts will include academic publications, conference presentations, and outreach events to ensure broad impact. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to implement innovations that improve STEM teaching and learning at HSIs. 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 use of engineered organisms to sustainably produce valuable chemicals is a promising approach to reduce environmental impact and costs. However, natural metabolic processes of the organism often limit production of desired compounds. This project aims to understand and modify key enzymes that control cellular metabolism to enable more efficient production of high-value chemicals. Undergraduate students from diverse STEM backgrounds will be trained in cutting-edge techniques to study enzyme structures and behavior. By collaborating with researchers in India, the team will test these engineered enzymes in living organisms under various conditions. The project's outcomes will provide a toolkit of modified enzymes that can be used to enhance the production of valuable compounds, offering cheaper and greener synthesis methods for a wide range of industries. Furthermore, this project will offer insight into the basic underpinnings that control cellular metabolic state and thus have potential applications to fields beyond biomanufacturing, such as medicine, agriculture, and environmental science. The project also includes the training of undergraduates in cryo-EM data analysis through a dedicated computational course. The project aims to develop transhydrogenase systems to address redox imbalance bottlenecks in metabolic engineering. Focusing on the recently discovered autoregulated GltAB-GudB complex in Bacillus subtilis, the project will investigate its impact on stationary phase biosynthetic potential and physiology. This unusually large complex, nearly half the size of a ribosome, regulates glutamate metabolism through a sophisticated allosteric control system. Using time-resolved cryo-electron microscopy (cryo-EM), metabolite-protein interaction screening, and kinetic assays, the project aims to elucidate the structural mechanisms underlying autoregulation of the complex. By bridging the gap between in vivo and in vitro enzyme activity measurements, the project intends to develop a biophysical model of GltAB-GudB regulation to enable rational tuning of its regulatory features. This knowledge will be applied to engineer the GltAB-GudB system and explore alternative transhydrogenase systems to enhance the biosynthesis of compounds limited by redox imbalance, such as free fatty acids (biodiesel precursors) and shikimate (pharmaceutical precursors). Ultimately, the project plans to elucidate key elements of metabolic regulation and develop a modular redox balancing toolkit to boost anabolic biosynthetic pathways in metabolic engineering applications. 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

Next generation (NextG) network systems are envisioned to be complex, ubiquitous, and smart, which are likely to consist of millions of heterogeneous mobile devices to connect everything digital, enable machine-to-machine communications, and support a variety of critical machine learning (ML) paradigms, including the most popular federated learning (FL) over mobile devices. However, stakeholders in many intelligent mobile applications/services are resource constrained in terms of spectrum, energy, computing, etc., which poses many challenges to FL inspired applications/services. This project targets to develop a novel NextG network with high degrees of resiliency to address those challenges, in particular, when there may be massive bursty workloads, insufficient spectrum availability, limited computational and storage capability on edge, and privacy concerns of the training data on mobile devices. The anticipated project outcomes will enrich the knowledge of wireless systems and machine learning technologies and provide multidisciplinary training especially for underrepresented students. Additionally, the findings and innovations will be shared across the 23-campus California State University (CSU) system, where 90% of campuses are minority-serving institutions. Outreach activities including high school internships and summer undergraduate training programs can provide early exposure to research in science and engineering, fostering interest and encouraging more female and minority students to pursue careers in these fields. This project aims to address the resilient issues of FL over mobile devices via a novel holistic NextG network design across network architecture, local mobile devices, and accessing networks. (1) From the networking system's perspective, to support FL over large-scale heterogeneous mobile devices, serverless computing is exploited at the edge to resiliently and efficiently provide ML computing as a service. (2) From the local mobile devices' perspective, to resiliently protect local training data privacy against inference attacks in FL, an energy-efficient piggyback differential privacy (DP) design is proposed by jointly considering DP amplification from gradient quantization and sparsification, and free Gaussian noises from wireless channels. (3) From the accessing networks' perspective, to improve the spectrum accessing resiliency, network scalability, and spectrum efficiency, a multi-bit over-the-air computation (M-AirComp) based spectrum accessing design is proposed, which can enable efficient transmission of FL model updates even with limited spectrum availability, reducing the total energy consumption for mobile devices. 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

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Educational Instrumentation project at San Francisco State University (SFSU) will strengthen undergraduate learning in STEM education, particularly in Computer Science and Engineering (Civil, Computer and Mechanical). Specifically, this project will secure 10 VR workstations with the latest VR headsets and tracking devices, along with a large portable 3D wall display setup, which will allow students to to build expertise in learning and development of VR tools, systems, and technologies as well as reinforce engineering theory in various computer science (e.g., Human-Computer Interaction, Data Visualization, Computer Graphics System Design) and engineering (e.g., Mechatronics, Controls Systems Lab, Open Machine Learning, Senior Capstone) courses. An estimated 400-450 students and at least 5 faculty members will utilize the project-funded equipment each year. In addition to providing improved experiences in the above-mentioned CS and engineering courses, other faculty members at College of Science and Engineering at SFSU can also utilize the resources for their technical studies or curriculum innovation. This initiative aims to foster robust collaboration across different departments at SFSU, benefiting both faculty and students at various levels. The goals of this project are to enrich the learning and experiences of undergraduate students by providing critical equipment in computer science and engineering. The project aims to promote change by creating the necessary technological space for the current VR STEM curriculum to be tested, developed, and disseminated at a large scale. VRMaS will facilitate cross-departmental collaboration at SFSU’s College of Science and Engineering, as well as within its close network of 23 campuses in the California State University system. This new resource will increase opportunities for a diverse community of STEM students to engage with state-of-the-art virtual reality technology, create next generation applications, and acquire technical knowledge in science and engineering preparing them for entry into the workforce. The project will assess the impact of the project funded equipment using the incorporation of VR technology into computer science and engineering courses and evaluating its effect on student learning and success rate in these courses. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to engage in the development and implementation of innovations to improve STEM teaching and learning at HSIs. 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 · 2024-10

This project aims to serve the national interest by significantly advancing the understanding of how to provide guidance for neurodiverse teams of learners, in particular cultivating inclusion and engagement of neurodivergent learners in engineering. Engineering education literature on teamwork involving neurodiverse students is relatively sparse, in fact, most of the research on teamwork focuses on neurotypical majorities, with little attention to the strengths of neurodivergent minorities. Surveys of neurodivergent individuals reveal the social-emotional and sensory difficulties that reduce their participation in education and employment. It is known that interactional experiences like teamwork shape these students’ identity formation and provide opportunities to acquire executive functioning (EF) skills for planning, attaining goals, and regulating behaviors. This project will investigate engineering teamwork experience from a neurodivergent perspective and ascertain the effectiveness of an AI-driven intervention on students’ acquisition of EF skills as well as changes in their social-emotional and sensory challenges during teamwork. It is expected that the findings will plant the seeds for important cultural change by creating an education landscape that empowers and is empathetic toward neurodivergent students. The goal of the project is to develop a prototype of an AI-driven platform for guiding neurodiverse teamwork. The utility of the platform in cultivating inclusion and engagement of neurodivergent learners in engineering will be investigated for the following purposes: (1) providing evidence-based guidance to improve EF skills in neurodiverse students during teamwork and (2) assisting professors mentor neurodiverse students during teamwork and (3) increasing neurodiversity awareness among faculty and students. A Large Language Model will be developed and managed - in the interest of data security - on the institution’s local research server. Three research questions will be investigated related to (i) identification of challenges experienced by neuro-divergent students; (ii) potential of AI to mitigate social-emotional and sensory challenges and (iii) feasibility of AI platform to foster enhanced inclusion and engagement. A mixed method approach is planned involving both qualitative and quantitative data collection as well as the use of validated instruments for measurement of Executive Functions. The robust and well-conceived dissemination plan includes the publication of a free online handbook of evidence-based strategies for mentoring neurodiverse students and a workshop to empower faculty - as ambassadors for neurodiversity in the school of engineering. Lessons learned will inform future AI-powered interventions revealing the benefits and limitations of the use of AI to foster inclusion and engagement of neurodiverse students in engineering. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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 · 2024-10

This project aims to serve the national interest by (1) improving programs preparing novice college mathematics instructors and (2) establishing leadership development for faculty who are the Providers of teaching-focused professional development (TPD) for those novices. Extensive educational research has identified evidence-based instructional practices that support undergraduates' persistence and learning in science, technology, engineering, and mathematics (STEM). For undergraduates to benefit from advancements in instructional practices, novice instructors (e.g., graduate students) need opportunities to develop expertise in those practices. For novice instructors to develop that expertise, Providers (i.e., those who facilitate TPD for instructors) themselves need opportunities to develop expertise in teaching about teaching. Providers face daunting challenges: no curricular packages (e.g., textbook, assessment items) exist for teaching graduate students how to teach mathematics. This effort builds upon previous work addressing these needs through workshops for Providers and creating a library of individual activities for TPD. Experienced Providers will assemble lessons from the library of activities, create assessments of learning about teaching, and teach new Providers about use of these packages. An innovation in the project is attention to a particular group of Providers, whose ambitions include scholarly work related to the development of novice instructors. These Provider-Scholars will be the next generation of leaders in this field. Greater Provider skill will improve instruction by novices and boost learning opportunities and outcomes for undergraduates. The goals of the project are (1) to develop curricular packages for learning about teaching college mathematics which will be piloted by Providers and (2) to build new research-based understanding of the knowledge, skills, dispositions, and communities Providers develop as they grow professionally into Provider-Scholars and Stewards (i.e., Provider-Scholars who also have leadership roles). Project research and evaluation will use a mixed-methods convergent design so complementary data are collected concurrently or, as appropriate, sequentially. This approach combines the strengths of quantitative data collection and analysis (e.g., large sample, repeated measures) with those of qualitative methods (e.g., participant voices, rich detail). In particular, the exploratory research questions are: (RQ1) What is the nature of Provider-Scholar knowledge, skills, and dispositions for engaging in scholarly work as Stewards? (RQ2) What is the nature of Steward, Provider-Scholar, and Provider engagement in the work and community growth? Project evaluation questions are: (EQ1) To what extent is project exploratory research implemented as planned? (EQ2) To what extent is the project succeeding in developing and piloting starter packages and Provider orientation with target communities? (EQ3) How can the project do better in supporting the professional community, including stewardship and leadership capacity development? The project intends to build professional community through collaborative working groups of experienced Provider-Scholars and education researchers. Mathematics graduate students (94% of whom have teaching related responsibilities while in graduate school) will benefit from the strengthening of TPD programs achieved by equipping new Providers with “starter packages” of resources informed by research findings about student-responsive teaching and learning. A robust community of Providers whose scholarly activity is about TPD will seed the next generation of leaders. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities. 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 · 2024-10

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI) Program, this Educational Instrumentation project at San Francisco State University (SFSU) will strengthen undergraduate learning in Civil, Mechanical, and Computer Engineering. Specifically, this project will secure a state-of-the-art Six Degrees of Freedom (6-DOF) Hexapod Motion Platform from Quanser Corporation, which will allow students to conduct hands-on experiments in courses such as Dynamics, Engineering Experimentation, Structural Analysis, Control Systems Laboratory, Systems Dynamics and Mechanical Vibrations, Digital Signal Processing, and Engineering Design Projects. An estimated 500 students and five faculty members will utilize the project-funded equipment each year. In addition to providing improved experiences in engineering courses, the new equipment will also be used in undergraduate research and independent projects. The goals of this project are to enrich the learning and experiences of undergraduate students by providing critical equipment in the aforementioned disciplines. The Hexapod Motion Platform will enable students to bridge theoretical knowledge with practical application, enhancing their understanding of real-world engineering challenges and developing essential technical skills. This project will assess the impact of the project-funded equipment using quantitative and qualitative evaluation methods, including tracking D, F, W rates, analyzing student performance on relevant assessments and conducting surveys to collect feedback. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to engage in the development and implementation of innovations to improve STEM teaching and learning at HSIs 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 · 2024-10

Providing computer science (CS) education to students prior to high school is critical for catalyzing their interest in CS and closing achievement and development gaps. However, the retention rate for underrepresented group participants in middle school CS teacher preparation programs is lower than that for their peers. The resulting lack of diversity in CS teachers contributes to students’ inequitable access to quality middle school CS education. In this four-year, Design and Development, Teaching Strand project, San Francisco State University, WestEd, and 10+ school districts in California will investigate effective design and implementation strategies of CS teacher preparation programs aimed to increase the number of middle school CS teachers from underrepresented groups. By investigating and designing an effective and equitable model for preparing middle school CS teachers, this project will increase the number of middle school CS teachers, particularly those from underrepresented groups. Society as a whole will benefit from a more diverse CS workforce. In this project, the project team will first work with participants in our CS teacher preparation program to identify factors responsible for the lower retention rate of underrepresented group participants and develop potential interventions to address these factors. The team will then integrate these interventions into three evidence-based components of a 1-year teacher preparation program: (1) a new teacher certification program to increase middle school teachers’ knowledge of CS content and culturally relevant pedagogy, (2) mentoring from experienced CS teachers from underrepresented groups, to provide CS content and pedagogical support for those teachers, and (3) professional learning communities to provide teachers in the program with a supportive community as they learn. The team will gather and analyze data throughout the program to determine which intervention components improve retention of underrepresented group teachers. This project will address the following research questions: (1) Which factors have contributed to lower retention rates for underrepresented group participants in CS teacher preparation programs? (2) What interventions can be implemented to address those factors and boost the retention rate of underrepresented group teachers in a middle school CS teacher preparation program? The project findings will contribute to the relatively scant evidence base on strategies to improve the retention rate of in-service teachers from underrepresented groups in CS teacher preparation programs, providing a foundation for creating more equitable CS learning environments for teachers and students. This project will reach 90 teachers during the grant period. The knowledge produced for retaining underrepresented group teachers in CS teacher preparation programs will be of wide interest, since school districts throughout the country are facing or will face CS teacher shortages. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

The Scientist Spotlights Partnership Program: Engaging High School Students in Exploring Biomedical Science Careers by Connecting with Counter-Stereotypical Scientists Project Summary/Abstract Extending the work of the successful NIH SEPA-funded Scientist Spotlights Initiative, San Francisco State University – in partnership with Foothill College and University of Georgia – aims to expand collaborations with high school teachers to be nationwide, connect high school students with near peer undergraduate student mentors from diverse backgrounds, and investigate the impact of engaging high school students as authors of Scientist Spotlights in the new Scientist Spotlights Partnership Program. Few high school students have access to biomedical scientists; even fewer have insights into their personal backgrounds and professional journeys. Research on science identity, stereotypes, and career interests suggests that lack of access to diverse representations of scientists is a key barrier for high school students envisioning themselves in biomedical research careers, especially for students from populations marginalized in science. Yet, bringing scientists directly into classrooms is not possible for many teachers, would not provide access to biomedical role models at scale, and may inadvertently reinforce stereotypes about who can pursue biomedical science. To increase representation of diverse biomedical science role models in high school science curriculum, we previously developed hundreds of Scientist Spotlights – metacognitive curriculum supplements that align with high school NGSS content standards, highlight the stories and research of counter-stereotypical biomedical scientists, and are reflective assignments completed by high school students. Faculty and undergraduate students authored Scientist Spotlights were freely available on the Scientist Spotlights Initiative website for teachers to use. Research results from prior efforts demonstrated increases in high school students’ science identity and relatability to scientists after experiencing only three Scientist Spotlights, and we unexpectedly observed even more dramatic positive impacts for undergraduate students who authored Scientist Spotlights. To leverage these results, we now propose to engage high school students themselves in exploring biomedical research careers by potentially interviewing scientists and authoring Scientist Spotlights. To accomplish this, we will partner high school teachers with undergraduate near peer mentors to guide the authoring process as well as to collaborate in assessing impact on high school students. Over 5 years, we aim to collaborate with ~40 teachers, ~80 near peer mentors, and ~1280 high school students who will have agency to identify, interview, and author Scientist Spotlights, which will be disseminated on the Scientist Spotlights Initiative website. Finally, we will conduct research to compare the impact of authoring versus just experiencing Scientist Spotlights assignments on high school students’ science identity, relatability to scientists, and career interests.

NSF Awards · FY 2024 · 2024-09

In this project, funded by the MPS-LEAPS (Launching Early-Career Academic Pathways) Program and managed by the Broadening Participation Program in the Division of Chemistry (CHE-BP), Professor Michael Enright and his students at San Francisco State University will perform studies focused on the design and development of efficient nanoscale catalysts capable of driving new photoredox processes. Most existing photocatalytic processes are limited by high catalyst loading, reliance upon precious metals, or poor efficiency resulting from radiative recombination on the nanosecond timescale. Professor Enright and his students will use CuAlS2/ZnS nanoparticles as model systems to understand the role of nanoparticle structure on photocatalytic performance. The proposed experiments will quantify competitive rates of exciton separation, hole quenching, and back electron transfer across heterostructure nanomaterials to understand specific materials and structural attributes that lead to improved photocatalysis. Their studies could lead to the development of improved nanoscale catalysts to drive new photoredox processes, and could contribute to the development of new nanomaterial-driven photocatalytic reactions. This project is designed to provide research experiences for a diverse cohort of student investigators and to promote the inclusion of students from minority groups underrepresented in STEM and first-generation college students. This work seeks to make significant contributions to the development of nanoscale photocatalysts. In addition to developing heavy-metal-free heterostructures using CuAlS2/ZnS, this investigation will give insights into the impacts of nanocrystal morphology on the catalytic viability of type II heterostructures. The proposed investigation seeks to become one of the first non-oxide-based examples of sustained photocatalysis with nanocrystals using an applied bias. Furthermore, future development of new, previously inaccessible photoredox reactions for nanocrystals and even multielectron/multiproton reactions with molecular co-catalysts could become possible because of this work. Significant components of this work will be investigated in Course-based Undergraduate Research Experiences, where students will learn the same skills as a traditional laboratory but also learn the advanced laboratory techniques and how to use instrumentation using the proposed nanoparticles and photocatalysis instead of pre-stocked laboratory samples. 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

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution. 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 serve the national interest by engaging undergraduate students as active change agents in curriculum reform of entry-level and upper-division college chemistry courses. Chemistry suffers from high attrition rates, and studies on science identity, science belonging, stereotype threat, and possible selves suggests a lack of diverse representations of scientists could disproportionately impede historically underrepresented students from persisting and succeeding in STEM. This project plans to give students the ability to reform undergraduate chemistry curricula to be culturally responsive and inclusive by authoring "Scientist Spotlights." Scientist Spotlights are reflective assignments in which students explore the personal history and professional contributions of counter-stereotypical scientists whose work is connected to the science concepts under study. Expanding these evidence-based, inclusive curricula in chemistry and enlisting students as partners to reform chemistry curriculum is important to improve STEM student engagement and success. This project also plans to disseminate the Scientist Spotlights on counter-stereotypical chemists–authored by and for students on an open-access database so other instructors can in integrate culturally inclusive materials in their chemistry courses as well. This project aims to (1) adapt and implement the Scientist Spotlights intervention to engage students in authoring and experiencing culturally responsive curricula in all chemistry courses and (2) assess the impact of the Scientist Spotlights intervention on student affective and academic outcomes in chemistry courses. Diverse students at University of San Francisco will author unique Scientist Spotlights, containing personal interviews, that would allow chemistry instructors to integrate inclusive activities explicitly into their courses in alignment with their chemistry content. Pre- and post-surveys will be collected to evaluate qualitative themes and quantify the shifts in students' stereotypes of scientists and scientist relatability before and after authoring Scientist Spotlights versus experiencing Scientist Spotlights. Student grades and pass rates will also be assessed during the Scientist Spotlights intervention to measure shifts in academic performance. Results emerging from these data will advance understanding of the significance in engaging STEM students as active agents to reform the messaging in undergraduate chemistry curricula as well as the effectiveness of adapting and implementing the Scientist Spotlights intervention to a new discipline, institution, and diverse student population. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY With the increase in antibiotic resistance bacterial infections there is an urgent need for novel antimicrobial agents that target alternative cellular pathways. One attractive strategy for the development of new antibiotics is to target DNA biosynthesis by inhibiting thymine biosynthesis. It has been shown that several severe human pathogens, such as Mycobacterium tuberculosis (M. tb) and Clostridioides difficile (C. diff) (and several other severe human pathogens), produce the DNA base thymine using an alternative enzymatic pathway that relies on a unique flavin- dependent thymidylate synthase (FDTS) that is coded for by the thyX gene. In eukaryotes and humans, the thyA or TYMS gene respectively code for “classical TSase” enzymes, which are well-characterized and the target of several chemotherapeutic drugs. Both the FDTS and classical TSase enzymes catalyze the same net reaction of uridylate (dUMP), which forms the product thymidylate, dTMP; however, the chemical mechanism, catalytic intermediates, and protein/active stie structure have been shown to be very different. Since these two proteins have distinct structures and mechanism of catalysis, it should be feasible to inhibit FDTS selectively over human TSase thereby interrupting DNA production in the pathogen but not in humans, providing antibiotics with low toxicity. In the proposed research plan our main goals are i) to study the molecular mechanism of MtbFDTS and CdiffFDTS catalysis and understand the nature of enzyme inhibition using biochemical, biophysical, and structural techniques to develop a consensus mechanism for this putative antibiotic drug target, ii) Develop biochemical methodologies to understand the nature of ligand binding to the MtbFDTS enzyme and relate this to assays that evaluate inhibition, such that these methods can be used for testing the efficacy and potency of newly synthesized molecules at inhibiting FDTS selectively over classical TSase., iii) to synthesize new compounds that we hypothesize to display selective inhibition of FDTS over human TSase, and to create a structure-function relationship for rational design of antibiotic compounds that may be effective against several human pathogens. By completing these experimental goals, we expect to discover unique mechanistic features of the MtbFDTS and CdiffFDTS enzymes, solve novel enzyme structures, and uncover physical parameters for selective inhibition of thymidylate production within pathogenic bacteria, without interrupting human TSase enzymes. This approach will help to define a structure-function relationship for selective enzyme inhibition. This will ultimately increase the overall chances of future antibiotic drug discovery through the rational design of compounds using fragment-based docking models using the crystal structures that we’ll solve for the MtbFDTS and CdiffFDTS enzymes, and through future high-throughput inhibitor screening using the assays we develop. Our studies are expected to discover underlying principles that will allow us to design and test new molecules that will not interfere with human DNA biosynthetic enzymes, which will potentially give rise to antibiotic drugs with low human toxicity.

NIH Research Projects · FY 2026 · 2024-07

Adolescents in families with financial challenges are nearly twice as likely to smoke cigarettes or vape and are more likely to use substances, such as alcohol, cannabis, and illicit drugs than adolescents in households without such challenges. This study will add to our understanding of adolescent substance use by examining adolescents’ experiences based on financial challenges, such as being laughed at or teased. Studies with adults have shown that experiences based on financial challenges are positively associated with substance use. Yet, this line of inquiry has not been extended to adolescents, and this age is when the onset of substance use occurs making it particularly important to examine. To our knowledge, there is only one study that exists with adolescents, and it shows that adolescents with mothers who had experiences based on financial challenges were more likely to use tobacco products than their counterparts. Recognizing a gap in the field, the PI created a new conceptual model to guide researchers who are examining experiences based on financial challenges among adolescents. Then, the PI conducted preliminary research to support the model. Specifically, the PI’s research has shown that adolescents who had experiences based on financial challenges were more likely to use tobacco than their counterparts. However, we do not yet know if this association will remain with other substances, including alcohol, cannabis, and opioids, which are known to be harmful for adolescents. Thus, to contribute to this critically important topic, the proposed research will advance our knowledge with three specific aims: To (1) examine adolescents’ experiences based on financial challenges, (2) determine how experiences based on financial challenges are associated with substance use, including alcohol, cannabis, and opioids, and (3) investigate how associations between experiences based on financial challenges and substance use differ among adolescents. Providing new knowledge is critical for informing programs that reduce and prevent substance use by targeting experiences based on financial challenges. A mixed-methods study that includes interviews and surveys. Consistent with the R16 aims, students will be extensively involved. The PI’s track record with mentoring includes 100 students and 33 publications with student co-authors. Strategies to train students are planned.

NIH Research Projects · FY 2024 · 2023-09

Abstract The overall goal of our research is to reduce HIV-related health inequities among Latinx immigrant populations. We propose to determine the effectiveness of Hermanos de Luna y Sol (HLS), a community-based, group intervention delivered in Spanish, designed to reduce HIV sexual risk among Latinx immigrants who identify as gay/bisexual men or men who have sex with men (GBMSM). The study is designed as a quasi-experimental, community control, with Oakland, CA as the intervention group and Chicago, IL as the control. Assessments will be conducted at -3 and 0 mos., and follow-ups at 3, 6, and 12 mos. Participants (N=360; n=180 per city) will be recruited using Time-location sampling (a venue-based sampling designed to reduce sample bias). HLS, the intervention at the heart of this study, offers several novel features: it focuses on immigrant, Spanish- speaking populations; it addresses racism and homophobia as factors shaping HIV risk; and uses a community-based approach centered on community involvement (e.g., civic participation, volunteering) as a means to foster sexual health and community building. The study will help identify effective interventions to prevent HIV among Latinx immigrant GBMSM, a marginalized population for which HIV preventive interventions are severely lacking. This study capitalizes on an existing intervention designed for Spanish speaking populations; is the first of its kind to rigorously test the intervention’s effectiveness among Latinx immigrant GBMSM using a community control design. The study applies the best possible scientific approach to obtain estimates of intervention effectiveness. If successful, the intervention would be relatively easy to disseminate via community organizations and the Centers for Disease Control and Prevention. Ultimately, the study will help move forward efforts to reduce racial/ethnic health inequities, one of the nation’s major public health priorities. This proposal is directly relevant to the RFA on Transformative Research to Address Health Disparities and Advance Health Equity at Minority serving Institutions. The project is led by SFSU – a Hispanic Serving Institution-- in collaboration with two Latinx community-based organizations: La Familia and Chicago Queer Latinx Collaborative. We are a multidisciplinary research team with the depth and breadth of experience on HIV prevention with Latinx and GBMSM communities to successfully conduct the study. All senior personnel are of Latin American descent, fully bilingual (Spanish and English), and three of them are women. The proposed study is strongly aligned with NIH UNITED Initiative of fostering racial equity and inclusion in biomedical research and is responsive to priority areas of multiple NIH institutes and centers, such NIMHD, NIMH, and the Office of AIDS Research.

NIH Research Projects · FY 2025 · 2023-09

The overall goal of this research is to reduce HIV-and related health variations among US male populations from Hispanic backgrounds. The quasi-experimental study will determine the effectiveness of a group intervention designed to reduce risk behaviors among Hispanic male sub-populations with the highest HIV risk. This quasi-experimental, longitudinal design has both an intervention and a control arm. Assessments will be conducted at -2 and 0 months, and follow-ups at 3, 6, and 12 months. Participants (N=360; n=180 per arm) will be recruited using time-location sampling (e.g., a venue-based strategy). The intervention at the heart of this study offers several novel features: it focuses on Hispanic men, socio-cultural risk factors shaping HIV susceptibility, and uses an approach centered on local involvement, such as civic participation and volunteering, as a means to foster health behaviors and group social support. The study will help identify effective interventions to prevent HIV among Hispanic male subpopulations at highest risk, but who remain understudied, and for whom HIV preventive interventions are severely lacking. This study capitalizes on an existing intervention and is the first of its kind to rigorously test, using a control arm, the intervention’s effectiveness among Hispanic men who do not exclusively identify as heterosexual or engage primarily in heterosexual relationships. The study applies the best possible scientific approach to obtain estimates of intervention effectiveness. If successful, the intervention can inform future interventions in the target population including its dissemination via local organizations and the Centers for Disease Control and Prevention. Ultimately, the study will help advance efforts to improve health across sociodemographic groups and thus, across the whole U.S. population. The project is led by San Francisco State University in collaboration with other academic partners and local organizations, the latter situated in each of the study sites. The research team is multidisciplinary with the depth and breadth of expertise in prevention science, along with extensive experience working with the targeted study population all of which required to successfully implement the project.

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY/ ABSTRACT Establishing precise synaptic connections is critical for normal brain function. Synaptic dysfunction can lead to neuronal hyperexcitability, contributing to disorders including epilepsy. Microglia are the dominant immune cells in the brain and play multiple roles in synaptic development, modulating neuronal excitability, and engulfing excess excitatory synapses. However, the mechanisms by which microglia impact synapses have largely been investigated with fixed tissue histology or in limited regions of the adult brain using rodent models. In fact, microglial engulfment of whole synapses has not been directly observed in the developing brain. In this proposal, I will use a zebrafish model system to study microglial-synapse interactions in the intact developing brain. My recently published work identified a population of synapse-associated microglia (SAMs) enriched in the zebrafish hindbrain and defined its transcriptional profile by single-cell and regional bulk sequencing. In this proposal, I will examine this microglial subset using a combination of live imaging and candidate gene deletion in both physiology and in the context of hyperexcitability. Aim 1 will determine if microglia engulf synapses during development and the impact of immune activation or after deletion of a core lysosomal protease known as cathepsin b (ctsba) - a top candidate from my transcriptomic work. Aim 2 will further assess these phenotypes in the context of chemically induced hyperexcitability and use startle behavior recordings to assess the impact on neural circuit function. Finally, in Aim 3 (R00 phase), I will define the molecular mechanisms regulating lysosome activity during microglia phagocytosis and transcriptionally profile microglia following neuronal hyperexcitability. Together these studies will open a distinct direction using a new model to identify molecular pathways that regulate microglia-synaptic interactions with the potential to investigate non-neuronal therapeutic interventions that impact development and disease states such as epilepsy.

NIH Research Projects · FY 2026 · 2023-05

While generally the genes in a single organism are thought of as having aligned interests – maximizing the fitness of the organism – under some circumstances, different genes in an individual may benefit from different tradeoffs between an organism’s characteristics. Under such “intragenomic conflict,” different genes may evolve to influence the organism in different ways, and to antagonize the actions of other genes. While the importance of this fact is well-understood among molecular evolutionary biologists, biomedical researchers have largely failed to appreciate these implications. In the proposed work, we will explore the long-underappreciated role of the X chromosome in intragenomic conflict, and elucidate the impacts of this conflict on human biology. The X chromosome is expected to experience particularly high levels of intragenomic conflict both because of its atypical inheritance pattern (being primarily inherited from females) and because of its hemizygous experience (allowing a single allele to have outsize influence). The long term goals of this research programme are to understand how intragenomic conflict influences human health and to devise conflict- focused strategies for interventions. The short-term goals of this proposal are to identify the regulatory, transcriptomic and cellular impacts of conflict-drive X chromosomal biology. We will pursue these goals through (i) studying the impact of genomic conflict on X chromosomal microRNA regulatory networks; (ii) identifying genes that are differentially expressed on X chromosomes depending on which parent they are inherited from; and (iii) using single-cell RNA-seq data to identify the cell-type and transcriptomic impacts of differential expression of maternally- and paternally-inherited X chromosomes in human tissues.