Research Team
PI: Guadalupe Canahuate (Electrical and Computer Engineering, Engineering), Co-PIs: Thomas Casavant (Biomedical Engineering, Engineering), Mary Charlton (Epidemiology, CPH), John Buatti (Radiation Oncology, CCOM)

Executive Summary
Health disparities are defined by NIH as differences in the incidence, prevalence, mortality, and burden of diseases or health conditions between specific population groups in the US. These disparities are often associated with demographic, social or economic factors such as income, race, gender, and geography (e.g. rural vs. urban), among others. Iowa is not exempted from these disparities. The latest report released by the Iowa Cancer Registry shows that compared to all other racial/ethnic groups, the Black population in Iowa has the highest mortality rate in every single major cause of death, including cancer. At the same time, machine learning (ML) and artificial intelligence (AI) algorithms are increasingly used in clinical care to improve diagnosis, treatment selection, and prognosis of numerous diseases including cancer. Several recent studies have reported that AI systems can discriminate and create unequal outcomes in different population groups. Because AI/ML models learn from historically collected data, human and structural biases present in the data can be perpetuated and even exacerbated as the models are applied to clinical care. The goal of this initiative is to identify and quantify current biases in AI/ML healthcare models and to develop interventions to correct and reduce these biases. This jumpstart proposal seeks to: 1) assess the bias of existing AI models and compare different sociodemographic groups; 2) generate fair AI models under different metrics and compare performance with existing models; and 3) generate hypothesis-driven research projects to address health disparities targeting NIH/NSF grant programs while engaging the campus research community.

Research Team
PI: Charles Stanier (Chemical and Biochemical Engineering, Engineering), Co-PIs: Jerry Anthony (Urban and Regional Planning, Graduate College), Marc Linderman (Geography and Sustainability Sciences, CLAS), Wei Li (Finance, Business)

Executive Summary
Federal infrastructure and science policies are calling for “moonshot” projects to ensure carbonfree energy infrastructure to combat the anticipated large negative impacts of climate change. Iowa’s abundant wind, bioenergy and solar resources make it a strong player in the emerging green energy landscape. By 2040, Iowa can become a net exporter of energy. Achieving net export status will bring energy independence to Iowa and will attract industries supplying and demanding clean energy. However, to achieve its potential Iowa needs to accelerate research, development, and adoption of low-carbon energy production and storage methods. These technical elements must be coordinated with workforce development, innovation ecosystem, and public policy. The pace and scale of the transition will be significant, amounting to more than 10% of GDP per year combining contributions from transportation, electricity, fuels, industry, construction, agriculture, and building operation sectors. We propose a convergence research and community building project centered at the University of Iowa. Combining engineering, data science, public policy, environmental science, and business expertise, we will develop large proposals around the central question: how can R&D, education and outreach, markets, & socio-economic policy shift evolving barriers & attitudes towards adoption of carbon management practices & energy technologies? A number of partner organizations (business, local government, campus partners, agricultural partners) are identified in the proposal that are enthusiastic about guiding and participating in the project. Together, these efforts will position the University of Iowa for future grants, contracts, and leadership roles in the rapid decarbonization transition.

Research Team
PI: Milan Sonka (Electrical and Computer Engineering, Engineering), Co-PIs: Paul Dilley (Classics, CLAS), Daniel Maze (Art History, CLAS), Thaddeus Wadas (Radiology, CCOM)

Executive Summary
This Humanities-Science-Engineering project brings together UI faculty and staff researchers from across the campus to develop non-destructive digital imaging, machine learning, and artificial intelligence (AI) technologies to study cultural artifacts. The interdisciplinary team is uniquely qualified to achieve novel and ground-breaking results, with early-career faculty driving many aspects of the project. The project is innovative at multiple levels – a combination of imaging, machine learning, and AI will be used to study objects from the Iowa collections and to create a database of materials, texts, and other object properties from known samples. The proposed approach combines volumetric X-ray (Aim 1) and multi-spectral optical imaging (Aim 2) trained on a control dataset of materials of known composition (Aim 3) to determine unknown material properties, design, structure, and repair status of 3D artifacts, and the ink/pigment components of pre-modern texts, etc. We employ the novel use of 21st-century technology to establish early standards for future imaging research and to reveal data about cultural artifacts and their previously undiscoverable secrets. Aim-4 will study 13th–20th century African artifacts, 12th–15th century manuscripts, and 16th century rare books. Our community convergence plans focus on research and education connections with undergraduate and graduate students, on community engagement to digitally reach fellow Iowans, and on sharing our novel results worldwide. Sustainability will build upon the increased visibility and proficiency of the Iowa team. We will apply for a number of extramural grants including those supporting members of historically excluded populations in research of these populations’ cultural heritage.

Research Team
PI: Ravitej Uppu (Physics and Astronomy, CLAS), Co-PIs: Aditi Bhattacherjee (Chemistry, CLAS), Joe Gomes (Chemical and Biochemical Engineering, Engineering), Xueyu Zhu (Mathematics, CLAS), Thomas Folland (Physics and Astronomy, CLAS)

Executive Summary
Quantum simulation (QSim) can enable efficient discovery of drugs, biocompatible fertilizers, and high-temperature superconductors, all key priorities as identified by the United Nations. Such simulations are not possible even with the largest supercomputers due to the limits of conventional computation, but quantum computers would be capable of solving these problems. Growing excitement around QSim has led to significant recent investment from Federal government’s initiatives, such as NSF Big Ideas, National Quantum Initiative, and multibillion-dollar investments from industry. This proposal aims to solve the convergent problem of constructing a practical QSim leveraging unique expertise at UI by creating a team of physicists, chemists, engineers, and mathematicians to concurrently tackle the fundamental as well as technical challenges. Currently, QSim has only been realized using superconductors that require specialized technology available only at large user facilities. The cost and scalability of superconducting QSim is one of the strongest limitations to its wider application. We aim to implement a practical and scalable QSim by i) developing semiconductor qubits operating at higher temperatures and lower costs than associated with competing technology and ii) building on UI strengths in nanofabrication (Iowa CREATES) and quantum algorithms. This research will jumpstart the creation of the first elements of QSim by bringing together a transdisciplinary team across two colleges, College of Liberal Arts and Sciences and College of Engineering, with the long-term goal (<5 years) of placing UI on the map as a leader in quantum science research and development.

Research Team
PI: Lucie Alice Laurian (School of Planning and Public Affairs, Graduate College), Co-PIs: Iulian Vamanu (School of Library and Information Science, Graduate College), Jennifer Glanville (Sociology and Criminology, CLAS), Phuong Nguyen (School of Planning and Public Affairs, Graduate College), Haifeng Qian (School of Planning and Public Affairs, Graduate College), Kang Zhao (Business Analytics, Business)

Executive Summary
The core research component will assess how public libraries mitigate community vulnerabilities and build resilience to climate, social, and economic risks. Libraries provide welcoming spaces and essential services during crises: shelter from extreme heat/cold waves for the poor and homeless, internet access, job search and training during economic recessions, and reliable information during crises, such as the COVID-19 pandemic. Using spatial, quantitative, qualitative, and social media data mining methods, the project will yield a public-facing report of the findings, produce scholarly publications, and serve as a pilot study for several major external grant proposals.
This project will also utilize team-building methods to develop a launching platform for a sustainable UI-wide interdisciplinary research group focused on Community Resilience. The Core Team includes scholars from the School of Library and Information Science, the School of Planning and Public Affairs, the Department of Sociology and Criminology, and the Tippie College of Business. We will further engage scholars from the Schools of Social Work, Public Health, Education, Journalism and Mass Communication, Geography and Sustainability Sciences, and more. Community-building ideation
gatherings will intentionally build on insights from Team Science, Place Studies, Liberating Structures, and Information Behaviors theories. The gatherings will be designed to appeal to academics’ intellectual curiosity, bring scholars to unusual places to spark idea collisions, and foster research group consciousness. The project will involve undergraduate and graduate students in meaningful research, and engage partners beyond the UI campus (e.g., library Directors, philanthropists).

Research Team
PI: Eric Nuxoll (Chemical and Biochemical Engineering, Engineering), Co-PIs: Jacob Elkins (Orthopedics & Rehabilitation, CCOM), David Stolz (Internal Medicine, CCOM), Dominique Limoli (Microbiology & Immunology, CCOM)

Executive Summary
Infection Control on Medical Implants is a $5 billion problem affecting more than 100,000 U.S. patients per year with substantial morbidity and mortality but without any significant advances in decades. This project will integrate a team of researchers spanning expertise from chemical engineering to orthopedic surgery to advance an innovative new strategy: In Situ Thermal Sterilization. Rather than surgically remove the infected implant and surrounding tissue, the proposed project investigates heating the implant surface in place to kill the biofilm, then send the patient home. Extensive in vitro experimentation from a strictly engineering approach is clearly insufficient for turning this strategy into a clinical reality, where the complications of multispecies biofilms in complex animal hosts and potential tissue damage must be addressed. This project will investigate how the presence of multiple species affects a biofilm’s thermal susceptibility, and conversely, how thermal shock affects the biofilm’s culture heterogeneity. It will compare the thermal susceptibility of biofilms grown in vivo to biofilms from various in vitro models and compare the efficacy of thermal shock when applied in vivo vs. in vitro (while simultaneously evaluating the accompanying tissue damage), as well as provide a feasibility demonstration of growing and eliminating an implant infection in vivo. Finally, it will characterize the population density and architecture of biofilms on clinically explanted artificial joints and evaluate the tissue damage of thermal shock on ex vivo human bone. These results will facilitate targeted external grants at each interface and jumpstart a new area of excellence at Iowa.

Research Team
PI: Corey Markfort (Civil and Environmental Engineering, Engineering), Co-PIs: Xun Zhou (Business Analytics, Business), Greg LeFevre (Civil and Environmental Engineering, Engineering), Peter Thorne (Occupational and Environmental Health, CPH), Elise Pizzi (Political Science, CLAS), Susan Meerdink (Geographical and Sustainability Sciences, CLAS)

Executive Summary
Iowa’s lakes are critical drinking water sources, and their economic and social value for recreation (swimming, fishing) is increasingly abundant. Nevertheless, lakes across the Midwest—including Iowa—are experiencing frequent harmful algal blooms events (HABs) that imperil health while necessitating beach closures. HABs impede Iowa’s sustainable development goals and water safety—particularly in small communities lacking advanced water treatment. Current understanding of HABs is limited by complex, interacting biogeochemical and physical processes that lead to highly dynamic HAB formation in space and time, resulting in challenges predicting and mitigating risk to lake users. Status quo techniques fail to promptly report HABs and associated health advisories on appropriate spatiotemporal scales, essential for developing exposure risk tools and devising stakeholder-driven solutions. There is a critical need to define and understand Iowa’s HAB challenge through a multifaceted, interdisciplinary approach that our team is uniquely positioned to address. A team of experts from public health and communication, policy, environmental sensing, physical and biochemical, and environmental engineering, have come together to develop solutions to the HAB challenge in Iowa. Only through this approach can economic opportunities be maximized for rural tourist-based communities while protecting drinking water sources, and recreation for millions of Iowans.

Research Team
PI: Michelle Voss (Psychological and Brain Sciences, CLAS), Co-PIs: Lucas Carr (Health and Human Physiology, CLAS), Kara Whitaker (Health and Human Physiology/Epidemiology, CLAS/CPH), Chooza Moon (Nursing, Nursing), Nathaniel Jenkins (Health and Human Physiology, CLAS)

Executive Summary
The demands of modern society, career pressures, and technological advances have reduced physical activity (PA) and sleep across age groups, but especially during midlife (40-65yrs), which is now recognized as a pivotal life stage for slowing age-related cognitive decline and delaying the onset of irreversible age-related neurodegenerative diseases such as Alzheimer’s disease. Better understanding of the dynamic interplay between PA and sleep during midlife has the potential for developing novel interventions to prevent age-related cognitive impairment. A paradigm shift is needed towards the 24-hour activity cycle, which describes all the movement behaviors that comprise a day including moderate-to-vigorous PA (MVPA), light PA (LPA), sedentary behavior (SB), and sleep. A major barrier is that expertise in the measurement, intervention, and adaptations to PA, SB, and sleep are siloed in separate fields with distinct devices, theories, analyses, and aging outcomes. Here we converge around the development of a novel integrative framework for a Move-ome, which we define as the 24-hour movement and energy expenditure profiles across a whole day, to be integrated into the broader preventative framework of the Exposome. As a first step, we test the efficacy of a 10-week, student-delivered intervention on 24-hour activity cycles and changes in cognitive and cardiometabolic risk factors among middle-aged adults at risk for accelerated cognitive decline. Success will lead to a more comprehensive lifestyle behavior intervention for cognitive health available to our community, cross-disciplinary training at all levels, and a registry for long-term follow-up to characterize modifiable health behaviors that promote lifelong cognitive health.

Research Team
PI: Daniel Fine (Dance and Theatre Arts, CLAS), Co-PIs: Joseph Kearney (Computer Science, CLAS), Tyler Bell (Electrical and Computer Engineering, Engineering), Bryon Winn (Theatre Arts, CLAS)

Executive Summary
By the end of March 2020, nearly all live, co-located performances were shut down due to the Pandemic. Undaunted, technologists and artists responded by streaming performances to entertain and inspire audiences who were isolated at home. However, the limitations of live video streaming soon became apparent: Streaming 2D video flattens interactions by imprisoning performers and audiences inside the rectangle of a screen. As imagined in Star Trek’s Holodeck, stages of the future will allow humans to escape the confines of video boxes and meaningfully connect with each other within shared virtual worlds from the comfort of their own remote locations. To create the stages of tomorrow, there is a need for a convergence of virtual reality (VR) technology and live performance. In pursuit of this vision, we propose NEXT Stages: Novel Environments for Extended Theatre. The goal of this research is to develop new methods to create immersive, embodied theatrical experiences. In these experiences, a diverse and remote audience becomes part of the performance, interacting with 3D video streams of live actors embodied in shared virtual worlds. This project leverages four years of research at the intersection of virtual reality and theatre conducted by an interdisciplinary team of faculty, students, and industry researchers from engineering, computing, and multiple artistic disciplines. Our past research includes the creation of Elevator #7, a VR-based theater production, which was performed at UI and at the Advanced Computing Center for Arts and Design at The Ohio State University and was disseminated at some of the world’s leading conferences and tradeshows.

Research Team
PI: Amy Colbert (Management and Entrepreneurship, Business), Co-PIs: Ion Vasi (Sociology and Criminology, CLAS), Michele Williams (Management and Entrepreneurship, Business), Cassie Barnhardt (Educational Policy and Leadership Studies, Education)

Executive Summary
Organizations are increasingly searching for strategies to promote diversity, equity, and inclusion (DEI), with billions of dollars being spent on DEI initiatives each year. However, progress toward diversity goals is slow, and the societal context in which organizations operate is changing rapidly in ways that impact DEI goals. We propose research to identify emerging DEI practices in business and higher education and to examine the factors that have shaped adoption patterns. We will also examine how DEI practices and their adoption patterns impact DEI-related outcomes (e.g., representation in leadership roles) and stakeholder attributions about organizations. To fully understand emerging DEI practices and their effects requires a convergence approach that draws from sociology, organization theory, organizational psychology, management, accounting, higher education, and business analytics. The research that we propose to conduct over the next year will provide pilot data to strengthen external funding proposals. We will also build community with other University of Iowa scholars studying DEI in organizations and other social justice issues (e.g., environmental justice, health equity, algorithmic bias), as well as with external organizational partners. Ultimately, we believe that the University of Iowa can become known as a leader in DEI and social justice research, a destination for students interested in addressing social justice issues, and a resource for organizations attempting to leverage diverse perspectives and address systems of social injustice.

Research Team
PI: Sarah Vigmostad (Biomedical Engineering, Engineering), Co-PIs: James Buchholz (Mechanical Engineering, Engineering), Xiaoyang Hua (Otolaryngology, CCOM), Brian Dlouhy (Neurosurgery, CCOM), Eric Hoffman (Radiology, CCOM), Ching-Long Lin (Mechanical Engineering, Engineering), Sajan Lingala (Biomedical Engineering, Engineering)

Executive Summary
The upper airway is a primary portal between our physiology and the environment. Sensing and signaling pathways impact brain activity and alert us to changing environmental conditions, while anatomic features within the upper airway serve to filter, humidify, and warm inhaled air to maintain proper lung function. The upper airway is linked to a myriad of diseases and plays a central role in determining an individual’s susceptibility to airborne pollutants (including allergens, viruses, bacteria, and particulate matter). Yet little is understood about how upper airway variations are driven by environmental factors or patterns of activity, or the ways in which structural differences within the upper airways impact sensing, biofeedback, primary respiratory disorders, or environmental sensitivities. The unfolding impacts of climate change and pandemics like SARS CoV-2 compel firmer understanding of this complex aspect of our physiology, and through this Jumpstarting Tomorrow project, we will deliver the clinical imaging and modeling tools necessary to undertake this research. The objective of this proposal is to develop clinical imaging protocols that integrate with a comprehensive thermal-fluid model of the upper airway which will serve to explore and define the interface between environmental factors (e.g. temperature, humidity, and airborne pollutants and particulates), upper airway structures (including airway geometry and the effects of surgical intervention or disease), and sensory functions, to form a basis for understanding the myriad of disparate medical symptoms and evolutionary forces in which this region of the physiology plays a crucial role.