Seed Grant Awards Description FY 2025

Rapid developments in the tech industry of apps and services run on a business model of extracting user personal data have continuously raised growing ethical concerns over the course of the last decade. One of the issues people face daily is the proliferation of user experience models that implement constraints which mask or disable existing options within a system so that the user is directed into an interaction model that monetarily benefits the service. In the field of Human Computer Interaction in particular, researchers and practitioners refer to such practices in user experience design through the notion of dark patterns, an umbrella term for deceptive design practice. The Dark Pattern Almanac is a multimodal publication in the form of an interactive glossary for situating extractive deceptive design and its effect on consenting mechanisms, allowing concepts from communities of practice to share space with those from academic research in an accessible medium. It also acts as a proposal for a participatory bottom-up mapping of (non) consent in user experience (UX) design informed by the lived expertise of end users, featuring existing alternative consenting frameworks.

The CU Denver Disinformation Working Group merges computational and communication-based methods to analyze the Communist Party of China’s (CPC) disinformation campaign attacking democracies worldwide. Based on threat assessments released by META, the CIA, and FBI, we know the CPC is flooding global democracies with disinformation, rumor bombs, conspiracy theories, and the other junk-communication scholars call “sharp power.” The research problem is clear: humanities-based readings of individual texts lack the representational authority to summarize the character of such disinformation campaigns, while computational analyses can map the size and scope of sharp power attacks yet ignore their content. We seek to bridge that research gap by creating an innovative interdisciplinary approach to detecting, categorizing, and understanding how disinformation works. The communication scholars will conduct rhetorical analyses of the content of representative samples of this disinformation and, by addressing its images, narratives, themes, and claims, will draw conclusions about how this disinformation creates chaos and anxiety. The computer scientists will perform computational analyses looking for patterns in system-level behavioral markers by tracking fake accounts, bot-generated likes, forged images, AI-generated shares, and so on, enabling us to map the size and range of the disinformation. To pursue this goal, this one-year pilot study seeks 1) to assemble the “take down data set” we will use to conduct our analyses; 2) to perform preliminary experiments seeking to cross-reference our communication and computational methods; and 3) to do the team-building and methods-testing work.

Since the 1970s, organizational theory scholars have focused on understanding employees’ experiences in their work environments. A vast body of organizational literature focuses on how climate is an important driver for performance at the micro and macro levels. However, within the field of public administration, little attention has been given to analyzing climate at the network level as a factor that leads to performance. Several questions need to be addressed to understand how the network’s structure and characteristics, like age, member composition, form of governance, centrality, and density, affect the development of network climate and effectiveness at the network level. This research proposal aims to apply organizational theory concepts to the collaborative network literature to answer two research questions: (1) What are the main drivers and mechanisms behind climate formation within a network? (2) How does climate at the network level impact organizational, network, and community effectiveness? To answer these research questions and contribute to understanding network climate, I will use a successful case of collaborative governance in the Denver metro area: the Denver Regional Council of Government (DRCOG). DRCOG is a purpose-oriented network that brings together local governments from 9 counties and 49 municipalities of the Denver Metro Region to collaborate on the design and implementation of transportation, growth and development, and aging policies. I will review archival data and collect primary data from surveys and semi-structured interviews with the members of DRCOG to understand the mechanisms behind the formation of the work climate at the network level and its impact on policy design and implementation. These findings will enable the formulation of a framework that explores the influence of network climate on performance.

This proposed study will investigate the spatial patterns of social vulnerability in Peru during and following an extreme climate event. Peru like other equatorial countries is particularly susceptible to the recurring effects of climate variability and extremes associated with El Niño. El Niño affects global to local weather every few years, disrupting rainfall and temperature patterns, which in turn impacts local infrastructure and health vulnerability. While many studies advanced our understanding of El Niño-health effects, less is known about the social vulnerability which communities face during and following El Niños. Social vulnerability such as lack of access to clean water or adequate sanitation can increase a population’s exposure, sensitivity, and decrease capacity to respond to climate-health threats. In this project I will examine a spatial dataset collected during fieldwork in Peru, composed of indicators of demography, socioeconomics, and health in 2016, a year associated with an extreme El Niño event. The dataset made up of district-level (like U.S. counties) indicators across Peru presents a rich opportunity to understand the geography of social vulnerability, how it spatially varies, and which indicators are key for policy interventions. A major project outcome will be a preliminary assessment with maps of high and low social vulnerability areas and areas of overlapping social and health vulnerability. The project findings will strengthen the development of an external grant proposal that focuses on mitigating the health effects of climate change, while fostering critical relationships for international collaboration and stakeholder engagement.

Mathematical optimization is the process of modeling real-world phenomena using mathematical concepts, and solving the resulting formulation to obtain an optimal choice for the given problem. The framework has long been used by leading companies to maximize their revenue; a recent survey found that 85% of Fortune 500 companies utilize optimization. However, many important problems without profit as the primary objective can be tackled effectively with the same techniques. For example, an urban planner who wants to locate amenities to maximize accessibility, while respecting practical constraints and ensuring access remains equitable across the population.

We propose extending a formulation that currently locates polling stations to also optimally locate ballot drop boxes. The Bipartisan Policy Center defines ballot drop boxes as “secure locations where you can safely submit a completed mail ballot”. Due to their convenience and security, drop boxes are a valuable option for people who may struggle to vote in person on Election Day. This could be due to many factors such as reduced mobility, inadequate transportation, or inflexible work hours.

A fundamental principle of mathematical optimization is that analysis is never effective in a vacuum. As mathematicians, it is our job to provide quantitative results for domain experts to factor into complex decision-making processes. The proposed work supports this charge by developing methodology to identify geographical disparities in voter access. Most importantly, our models prescribe a means to remedy inequities in access that we find, aiding in the effort to improve voting access across the U.S.

This project seeks to develop an asset-based measure of neighborhood stability in the context of household displacement, one of the negative results of gentrification. The most vulnerable neighborhoods in Denver saw increasing rates of household displacement leading up to and through COVID (Newcomer, J. (in progress), which impacts if/how people develop attachments to and belonging in places (placemaking). This seed grant helps us answer a) What are child-informed variables of social infrastructure that influence place-making, and how do they vary across different neighborhood conditions?, and b) How might these variables contribute to measures of socio-cultural assets (SCA) based on children’s experiences with household displacement? These insights are critical because they move away from economic variables which often emphasize what is lacking in places, toward sociocultural assets that emphasize what is important in places, and why.

As a community participatory project, we will engage in research with children from two neighborhoods in Denver that represent contrasting levels of household movement (displacing/ receiving) and built form (urban/suburban). While studies tend to focus on places where people have been displaced (Easton, 2019), we address a research gap by focusing on neighborhoods that predominantly receive displaced households. By promoting SCA as a measurable and meaningful indicator of neighborhood stability, we can better advocate for children’s wellbeing above and beyond that of traditional economic metrics. Crafting a balance between academic contribution and practical application allows this work to inform policy and increases the likelihood of elevating marginalized voices in resource allocation, particularly regarding social infrastructure.

Auraria As We Remember It is part of a larger movement by universities, including Brown, Georgetown, and the University of Minnesota, to confront their own historical legacies of harm. Collectively reframing and re-telling the multiple histories of the Auraria campus and the surrounding underserved communities will support an emphasis on racial equality while creating new connections between the university’s current diverse student body and Auraria’s past residents. 

This research will allow us to address the missing history of residents of the Auraria neighborhood that have been subsumed in institutional and celebratory accounts. This archival research falls under two areas. First, we will research the untold history of students in a Chicano Studies course on campus in the 1980s who worked to conduct oral interviews of the Auraria neighborhood. Second, the team will compile and synthesize information from the local activist newspaper The Westside Recorder (held at the Denver Public Library) in order to construct a detailed narrative of community resistance that includes both activist leaders and the main organizations involved.

The medical profession continues to make key scientific and clinical advances toward understanding what gives rise to mental disorders and how we can care for those suffering. And, gratefully, the broader public is chipping away at the stigma surrounding mental illnesses suffered by 60% of college-aged students, 26% of all Americans and the more than 40 million people worldwide who suffer from bipolar disorder. But among those who suffer, more than half of adults do not receive treatment for their mental illness. And for those who do, the estimated gap between the onset of diagnosable symptoms and care is eleven years.

This transdisciplinary exploration of the interior mind of those suffering from bipolar disorder brings together artists, educators, mental health professionals, and communities with a shared vision of closing the 11-year care gap by deepen our understanding of those who suffer, destigmatize mental illness, and build empathy, so
that we might: combat suicide rates (most people who commit suicide have a diagnosable mental disorder), decrease the ravage experienced by families (impact dimensions include health, economic and social domains, and children’s education and nutrition), and allow those suffering to live more joyful, productive, and connective lives.

Understanding human behavior is essential for the seismic design and evacuation strategy planning of buildings and infrastructure systems. The current practice of behavioral research under natural disasters is simulating an earthquake scenario in a VR environment and capturing human reactions while they are visually immersed in VR. Unfortunately, the current earthquake simulations in VR cannot display material failures (e.g., cracks on concrete), element deformations (e.g., column bend), and structural displacement (e.g., floor drifts). Lacking these key visual cues for evacuation decision-making results in a limited understanding of human behavior in earthquakes and, therefore, a weak theoretical foundation for improving building seismic design criteria.

This project will bridge the barrier by visualizing detailed structural damage under earthquake simulated by the Finite Element Method (FEM). FEM is one of the most accurate numerical simulation methods for structural reactions under earthquakes. Dr. Han collaborates with Dr. Kuanshi Zhong, an earthquake engineering expert from the University of Cincinnati, on this project (and future proposals) to acquire data on structural damages. Then, the CU Denver research team is developing an innovative data visualization framework in VR that directly utilizes FEM simulation data to construct 3D meshes so that they accurately display structural deformations at every frame of the VR experience. Preliminary results have been published in the 2024 ASCE International Conference on Computing in Civil Engineering. To date, the key challenge is balancing the tradeoff between the massive simulation data (10 GB+) and a smooth VR experience (120+ frames per second). Dr. Han is testing solutions including different data formats and structures, various compressing and sampling methods, and innovative shaders. After completing the development of the proposed high-fidelity earthquake visualization in VR, the research team will recruit participants to experience earthquakes with different levels of magnitude in VR. We will collect user performance data and answer a variety of research questions, including but not limited to: (1) Does the visualization of building structural damages change users’ behavior in evacuation decision-making? (2) What characteristics should be included (and what is the appropriate distribution for each characteristic) when modeling human subjects for agent-based earthquake evacuation simulation? and (3) Does high-fidelity VR provide sufficient training for earthquake evacuation needs? These questions are well-aligned with the aim of many National Science Foundation (NSF) programs, such as Humans, Disasters, and the Built Environment (HDBE) and Research on Innovative Technologies for Enhanced Learning (RITEL), and our VR simulation is a unique and essential research tool to answer those questions.

When communicating with infants, parents world-wide speak in “baby-talk” or infant-directed speech (IDS) intonation, which is characterized by exaggerated pitch modulation and slower and simplified enunciation of words. Although “baby-talk” does not sound serious, much research has documented that it more effectively captures infant attention, modulates infant mood, and facilitates rudimentary language acquisition, than does adult-directed speech (ADS). Our contribution to this field has been studying effects of postpartum depression (PPD) on IDS production and infants’ responsiveness to it. Our recent focus has been on infants’ reactions to the people who speak IDS. Normally, following one-minute of watching a video of an unfamiliar, non-depressed adult female speaking in IDS, infants of non-depressed mothers will look longer at a silent, still image of that woman’s face over a novel woman’s face — a face preference. However, when an infant’s own mother is experiencing PPD, infants look longer at the novel woman’s face over the face of the IDS speaker. Why does this matter? The extent to which infants show a preference for the face of the IDS speaker correlates significantly with how well they perform on the cognitive and receptive communication subscales of a standardized assessment of infant development. We believe that infants drawn to adults who speak “baby-talk” are better able to form an effective “social-learning partnership,” through which their learning about the world is guided.

One way a social-learning partnership guides infants is helping them become familiar with their parents’ native language, in turn facilitating their transition from prelinguistic “language generalist” in the first 6 months of life to budding “language specialists” in the second 6 months of life, culminating in the infant understanding of word-object associations and eventually their first word. For example, young infants demonstrate an ability discriminate between subtly different vowels that are meaningful in non-native languages but that do not appear in their native language. In the second 6 months of life, however, infants seem to lose this ability as they commit to their native language. This process is known as “perceptual narrowing.”

We propose to study preferences for the faces of native- vs. non-native-language IDS speakers in infants of mothers with and without PPD. Preliminary results support perceptual narrowing, with a trend toward stronger native-speaker face preferences and weaker non-native speaker face preferences as infants age, with one exception. Younger infants of PPD mothers exhibit a strong preference for the face of a non-native IDS speaker over a novel woman’s face, and a strong preference for a novel woman’s face over the face of a native IDS speaker – an apparent instance of neophilia, possibly linked to non-optimal caregiver-infant interactions. Preference for the face of native speakers re-emerges after 6 months in infants of PPD mothers. We request funds to support a doctoral student in replicating and extending this curious effect and examining whether the transient perturbation in IDS speaker face preference is linked to any delays in cognitive-linguistic development. We are also interested in studying what happens with infants growing up in bilingual families.

The post-COVID financial downturn has intensified urban vacancies in mid-sized and major U.S. cities, affecting not only neglected public spaces but also disused buildings, from homes to offices. A recent study funded by the American Rescue Plan Act (ARPA) reported a 30-year high office vacancy rate of 18.2%, with Denver reaching as high as 20%. While adaptive reuse—repurposing or retrofitting existing structures—offers environmental and sustainable benefits, it has also put pressure on existing methods of architectural design. First, the conventional hierarchical relationship of “Program First, Then Material” has been inverted. Building remnants now evoke a past without clear programmatic intent, as seen in the post-COVID blending of work and living spaces. Consequently, architectural design, once celebrated as a conceptual process detached from material considerations, is no longer sufficient.04 Second, despite the urgent need to reduce carbon footprints by reclaiming abandoned structures, architectural design still relies heavily on new specifiable, readily available materials that perpetuate carbon emissions. My proposal, Working Remnants: Material Reuse in North America, directly addresses these challenges by asking: Can architectural design thrive by working with what remains? If so, how should the design process adapt to inherit existing forms of embodied energy, despite the rigidity of current construction practices across North America? I see vacancies—marked by neglect and decay—not as endpoints, but as generative phases in a building’s lifecycle, distinct from its original use. Shifting the focus from vacant, program-less spaces to ones rich in material specificity reframes the conversation around architectural norms and opens up fresh possibilities for design. By moving away from standard, off-the-shelf materials and exploring the origins of reclaimed materials, this proposal advocates for a change in perspective: urban disuse is not an obstacle, but a resource that can propel cities into the future. In turn, it also challenges us to reimagine collective spaces through a lens of degrowth, stepping away from the relentless pursuit of capital development and efficiency that has historically shaped our built environment. Using Denver and Toronto as case studies to address broader North American issues, this research will explore experimental methods of re-considering building vacancies and remnants for their design potential. It will culminate in an exhibition featuring large-scale physical models, mockups, orthographic drawings, and computational surveys, all of which examine existing buildings in both cities that retain structural integrity and reuse potential. This exhibition proposal has been peer-reviewed and accepted by DesignTO, an internationally recognized design platform, and will take place at Collision Gallery in downtown Toronto in January 2026.

The project will evaluate the effectiveness of an intervention designed to build prosocial SECs of principals: Soul of Leadership (SoL) with 45 principals as a pilot study representing a diverse cross-section of rural, suburban, and urban schools of 38 geographically and socio-economically diverse school districts. The program has been previously piloted, establishing preliminary evidence for feasibility and acceptability. However, further research is needed to test the intervention to support funding applications to conduct a controlled trial.

Use of personal electric mobility devices (e-mobility devices) like e-bikes and e-scooters have proliferated many folds recently. With promises of greater flexibility on travel, low transportation costs and low carbon footprint, these modes are equally attractive to users and city officials and as such, many cities are offering incentives to promote these modes. However, the safety aspects of road sharing between vehicles, pedestrians, bicyclists and these newer modes is becoming an increasing concern with Netherlands and Germany for the first time in many years reporting increase in bicyclist injuries. The interaction between these personal mobility devices, pedestrians, traditional bicyclists and vehicles is also an area less understood and studied.

Using downtown Denver as case study, the proposed project focuses on two aspects of understanding the interactions between these newer modes, vehicles, and pedestrians and bicyclists – multisource data collection and scenario development for future testing of human factors in these interactions via simulation studies. The project will leverage the data collected via LiDAR equipment, video data and survey data to identify potential and actual conflict scenarios between the modes. These scenarios will then be recreated in the VR environment to further test the actions and reactions of users via simulation experiments in the future. To our knowledge, there has been no such research in place yet – this research has the potential to make the transition into the connected automated future of transportation safe and equitable for all modes. The survey will provide additional background information on people’s motivation behind using the personal e-mobility devices, their road sharing behavior and attitude towards safe shared mobility, enabling us to develop generalizable personas for them in future using latent trait/class analysis.

The project tasks will primarily focus on passive (LiDAR/video) and stated (survey) data collection, analysis and VR scenario development. Undergraduate students will be involved in all three aspects of the project and graduate students will be engaged in the project through supervision of undergraduate students and in working directly with the PI and the Co-PIs for survey instrument development. The project will aim to provide a diverse set of undergraduate students experience with developing 3D simulation of scenarios as an engaging and creative way to work with data and transportation safety.

Most connected and autonomous transportation future related research account for only traditional modes of transportation with a few research accounting for bicyclists and pedestrians. However, with the increased focus and awareness on climate change and sustainable future, e-mobility devices are more than likely to become a mainstream mode of transportation. Given the speed, route and user variability among these modes, it is important to understand how they interact with the other modes and the challenges they bring with them.

A growing number of children remain in hospitals for weeks, months, or even years, not because they need hospital-level care, but because they lack alternatives. This population of children, known as “extended stay patients,” is increasing at the same time there is a national decline in pediatric hospital units. This study aims to collect qualitative data from in-depth interviews from two groups: parents and caregivers of children who have prolonged hospitalization and pediatric healthcare workers responsible for their care. First, data will explore how parents and caregivers navigate their children’s long-term care, in hospitals or as they work to transition their kids home. Second, data will elucidate how healthcare providers and systems manage the growing number of hospitalized children, particularly as the infrastructure and supports for pediatric healthcare continue to decline. Research findings will provide insight into how social systems and institutions are constrained by policies and state priorities, which shape individual experience in sometimes deleterious ways. This work builds on the investigator’s prior research on families’ experiences in the child welfare system and of healthcare decision-making around vaccines to untangle this new public health challenge. In addition to making this unrecognized growing challenge visible, this research is designed to make theoretical and empirical contributions to sociological and public health debates about the use of technologies in medical care, state responsibilities to provide social support to families, and the role of hospitals in communities.

Homelessness, a pressing and enduring public issue, has recently garnered increased attention (Mosley & Park, 2022). The public’s intervention in homelessness can be traced back to the enactment of the McKinney-Vento Homeless Assistance Act in 1987. Despite policies at all governmental levels, the Point-in-time count (U.S. Department of Housing and Urban Development, 2023) reported that 653,104 individuals were experiencing homelessness in 2023. This project is dedicated to understanding the governance modes and patterns that emerge from the implementation of the Continuum of Care (CoC) program using a network approach. The CoC program aims to incentivize and strengthen collaboration for homelessness services at the local level. While empirical research has focused on questions related to the effect of cross-sector collaboration on performance, few studies have ventured into how general guidelines of federal programs like the CoC translate into governance dynamics at the local level.

To fill this gap, this project poses two questions: (1) What governance patterns emerge from implementing a federal program that imposes a network approach to service delivery related to homelessness? And (2) How effective is this network template in integrating the existing collaborative dynamics by analyzing which actors are not part of this network?

The study is conducted in two comprehensive stages, each with distinct data collection strategies and research aims. The first stage involves collecting the governance charters of the 383 CoCs in the country and qualitatively coding governance elements and collaborative rules. The second stage is focused on conducting a thorough media search in the regions covered by a representative sample of CoCs to identify which organizations deliver services to homeless populations but are not part of the CoC network of their region. In-depth interviews with both members and non-members of the CoCs will be conducted to address the question of the effectiveness of this top-down network approach, ensuring a comprehensive and rigorous research process.

The project started the first stage by collecting governance charters and implementing a pilot stage of qualitative coding. After six rounds of coding, the coding protocol was refined to improve the identification of rules and governance characteristics. The funding requested in this Seed Grant program will contribute to completing the coding of all the governance charters available and, more importantly, the initial steps of the second stage. The four CoCs in Colorado will be used as a pilot phase on the media search for isolated organizations and interviews with members and non-members of CoCs. This pilot phase is critical to refine the media search protocol, isolate identification, and interview protocol. The initial findings of the two stages are the seed content and direction needed to apply to the NSF Human Networks and Data Science (HNDS) Infrastructure Grant (HNDS-I), whose focus is on developing data infrastructure or network databases that can support social and behavioral research.

This study seeks to establish the effect of suspensory and climbing activity in humans on plasticity (shape changes in response to environmental stimulus) in upper limb skeletal and muscular anatomy. Understanding this relationship has important implications for interpreting the human fossil record where many specimens show features associated with forelimb suspensory locomotion (FSL) in other apes. Additionally, variability in upper limb anatomy has been linked to injury susceptibility in modern humans. Comparative research on primate upper limb anatomy has been equivocal in relating bone and muscle variation directly to locomotor behavior, and therefore has been unable to facilitate a clearer interpretation of the skeletal features typically believed to relate to FSL in the human fossil record. Unexplored is the malleability of upper limb skeletal and muscle properties in direct response to activity patterns in modern humans. The proposed study would fill this gap in knowledge by assessing differences in upper limb skeletal and muscle variables between collegiate gymnasts and soccer players. While both cohorts engage in high level athletic activities, only gymnasts experience extreme biomechanical forces on the upper limbs and therefore should show shape changes in association with FSL if the upper limb undergoes remodeling in response to this behavior. To investigate these potential differences, computer tomography (CT) and magnetic resonance imaging (MRI) of the upper limb and torso will be used to virtually reconstruct and measure key variables of the shoulder, arm, forearm, and hand and compare them between the cohorts and with previously published data of extinct human ancestors represented by fossils. This proposal requests funding for pilot imaging data from eight participants so that the imaging and analysis protocols can be validated prior to submitting an NSF grant for a larger sample size.