May 6, 2025
Honorees announced for 2025 undergraduate research recognition awards
The Population Health Initiative announced today the 21 University of Washington students who received Population Health Recognition Awards as part of their participation in the 2025 Undergraduate Research Symposium.
These awards, representing 18 separate projects, recognize each of the students for their innovative and well-presented research projects.
This award, which was created in partnership with the Office of Undergraduate Research in 2017, is an opportunity for students across all three campuses who are presenting at the annual Undergraduate Research Symposium on Friday, May 16, 2025 to be honored for their work.
A total of 177 applications were received for this award and reviewed by Population Health Initiative leadership. The 21 awardees, as well as brief descriptions of their projects, are:
Thea Zabala, Understanding the Chemical Structure of Spirulina to Optimize the Biomatter to Bioplastic Transition
The Great Pacific Garbage Patch, nano plastics found in human brains, and the 2.24 billion metric tons of carbon emitted per year are examples of the detrimental consequences of plastic pollution on human health and climate change. Not only do these negative impacts impede the right to health, but they do so in a way where plastic pollution disproportionately accumulates in coastal communities and has greater impacts on low-income countries. The need for plastic alternatives is clearly tied to population health. My research focuses on understanding how to manipulate the chemical and molecular structure of microalgae spirulina to create a sustainable, biodegradable plastic. By characterizing spirulina’s chemical bonds and its structural morphology as a function of different hot pressing conditions, I can tune the biomatter to bioplastic transition to form an optimized plastic alternative. I hope knowledge of this transition can be applied to other accessible organic materials for further research. Just as current plastics break down to nanoparticles and affect all aspects of health, so too do the implications of my research affect the pillars of population health. My work obviously results in a physical product that can mitigate the effects of plastic pollution on health and the environment. Yet its true implementation as a solution would allow policymakers to focus on identifying implementation gaps or ensuring compliance with sustainable development goals. Promoting social and economic equity in those areas disproportionately affected, integration of my work with policy advances a holistic approach to plastic justice.
Rin Prabhakaran, Salt and Water Regulation of Marine Mosquito and Midge Larvae
Population health is deeply connected to environmental changes, as shifting ecosystems influence the spread of infectious diseases and, in turn, impact human health. Mosquitoes are vectors of serious diseases such as malaria and dengue fever, which account for nearly 250 million cases and over 1 million deaths annually worldwide. Climate change and rising sea levels are changing the salinity of water bodies, particularly in coastal areas, affecting the survival of different aquatic organisms These changes have led to an increase in aquatic habitats where mosquito larvae hatch and develop, potentially expanding the spread of mosquito-borne diseases and could disproportionately impacting vulnerable communities. My research focuses on Aedes togoi, a salt-tolerant mosquito species that thrives in coastal environments. Unlike typical freshwater mosquitoes, Ae. togoi can survive in both freshwater and seawater, making it a unique species of interest as climate change continues to reshape coastal ecosystems. If rising sea levels and habitat changes expand the range of Aedes togoi, this could alter patterns of mosquito-borne disease transmission, creating new public health challenges. My research aims to understand how salt-tolerant mosquitoes like Ae. togoi, have evolved distinct anatomical and physiological mechanisms that enable them to survive in highly saline environments. By investigating Ae. togoi’s osmoregulatory mechanisms, my work has significant implications for predicting future species distributions and identifying physiological “weak points” that could serve as novel targets for population control. These findings could inspire projects aimed at reducing disease transmission with future environmental change.
Charles Mackey Henry and Ethan Bacci, Green Stormwater Infrastructure: A Case Study of Community Gardens and Flood Mitigation in Kent, Washington
In our ever-changing climate, developing resilient infrastructure to prepare communities for increasingly potent storm events is crucial in securing general health and wellbeing. Flooding has been an ongoing issue in Kent, Washington due to the hydrologic implications of impervious surface addition and antiquated stormwater infrastructure. Communities can use green stormwater infrastructure like community rain gardens and bioswales to slow down runoff and provide onsite storage and detention, providing effective stormwater control mechanisms to avoid damage to property and livelihoods. Our study investigates and models the quantitative hydrologic impacts of sustainable development such as community rain gardens and bioswales installed on previous impervious area in Kent, Washington. By modeling the site as it was before the rain garden, and inputting rainfall data from this season, we are showing how the construction of the rain garden has helped mitigate extreme flooding of the downstream portion of the watershed and improves the safety, livelihoods, and property of people in the downstream watershed.
Yuanxi Li, The Extent and Nature of Cyberbullying Towards Transgender in Emerging Adulthood
This research aligns with population health by examining how cyberbullying affects the mental and emotional well-being of transgender and non-binary young adults. Population health focuses on the factors that shape the well-being of specific groups, and cyberbullying has become a growing public health concern, particularly for marginalized communities. Online harassment can have serious mental health consequences, including increased rates of depression, anxiety, and social isolation. Transgender and non-binary individuals already face high levels of psychological distress due to discrimination and stigma. Cyberbullying adds another layer of harm, often leading to lower academic and work performance, reduced well-being, and, in severe cases, increased risk of self-harm or suicidal ideation and understanding how cyberbullying impacts this group is essential for designing effective mental health interventions, improving community support, and shaping better digital safety policies. This study takes a mixed-methods approach to explore cyberbullying patterns in transgender and non-binary young adults. The research will provide statistical data on cyberbullying prevalence while also capturing personal narratives that highlight its emotional impact. These findings will help guide policy changes on social media platforms, promote stronger protections against online harassment, and inform population health strategies that address mental well-being. This research contributes to broader public health efforts by identifying key risk factors and advocating for safer digital spaces. The goal is to support the development of targeted interventions that improve mental health outcomes for transgender and non-binary individuals while fostering more inclusive and supportive online environments.
Amrit Sharma, Early Prediction of Neonatal Ventilatory Outcomes Using Machine Learning
Our research aligns with the theme of population health by leveraging machine learning to improve neonatal respiratory care at scale. By analyzing data from thousands of newborns across diverse clinical settings, our models provide early warnings of clinical deterioration, enabling more timely and targeted interventions. This predictive capability is particularly crucial in neonatal intensive care units (NICUs), where rapid changes in a patient’s condition require immediate action to prevent complications. A key aspect of population health is ensuring that healthcare resources are allocated efficiently, particularly in low-resource settings where access to specialized care is limited. Our model aids in optimizing clinical decision-making by identifying high-risk patients early, allowing providers to allocate ventilatory support more effectively and avoid unnecessary intubations. Reducing the reliance on invasive procedures not only minimizes risks associated with prolonged ventilation but also helps alleviate the burden on already strained healthcare systems. By integrating machine learning into neonatal care, our research contributes to more proactive and personalized treatment strategies, improving survival rates and long-term health outcomes for newborns. Furthermore, the scalability of our approach means that similar predictive models can be applied across different populations and healthcare environments, advancing the broader goals of population health. Ultimately, this work demonstrates the power of data-driven healthcare in fostering equitable access to quality medical care, reducing preventable complications, and improving outcomes for vulnerable neonatal patients worldwide.
Jae Paik, Understanding Mosquitoes' Plant Choices: Chemical Attractions Underlying Mosquitoes Phytophagy
With an estimated billion people impacted by malaria, yellow fever, and zika every year, the mosquito was declared the “World’s Deadliest Animal” by the CDC in 2024. Mosquitoes, as vectors, transmit pathogens from an infected host to unaffected individuals until the end of its life. Consequently, vector-borne diseases have expanded beyond tropical and subtropical areas into temperate ones, as noted by the World Health Organization. This translates to 3.2 billion individuals, or over a third of the world’s population, at risk. Notably, the WHO report notes the need for new vector controls, including insecticides and traps, following increased research. This research aims to close this gap by building a database of mosquito-attractive plant species, including its chemical profiles. In my research, I extract DNA from wild-caught Aedes aegypti and Aedes albopictus mosquitoes for gut content analysis. By running PCR barcoding for plant DNA markers within the mosquito gut, I identify the plant species most attractive to mosquitoes. Gas chromatography-mass spectrometry (GC-MS) is then used to separate and identify the volatile organic compounds (VOCs) emitted by each plant. Although some traps use plant-based lures, its effectiveness has shown to be inconsistent, likely due to limited understanding of mosquito-attractive plant volatiles. As insecticide resistance continues to rise, alternative control methods are increasingly necessary. By identifying the plants mosquitoes commonly feed on and analyzing its chemical profiles, this research will inform the development of more effective odor-based traps, helping reduce preventable human infections and deaths.
Maya Abhyankar, Redefining Antibiotic Resistance: The Role of Trade-Off-Breaking Mutations in Plasmid Evolution
Antibiotic resistance poses a significant threat to population health, with predictions estimating 10 million deaths annually by 2050 if current trends persist. This crisis is fueled by the spread of antimicrobial resistance (AMR) genes among bacteria, which undermines our ability to treat infections and protect public health. Vulnerable populations, such as immunocompromised individuals and those in low-resource settings, are disproportionately affected, further exacerbating health inequities. My research addresses this critical issue by investigating plasmids—mobile DNA elements responsible for transferring resistance genes between bacteria through horizontal gene transfer (HGT). Plasmids can also propagate these genes vertically during bacterial cell division (VGT). While enhancing HGT often imposes a cost to VGT, I study “trade-off-breaking mutations” that allow plasmids to excel at both, enabling rapid reproduction and efficient resistance gene spread. By creating a genotype-to-phenotype map, I link specific mutations to their effects on HGT and VGT rates. This approach provides critical insights into how these mutations contribute to the evolution of highly virulent, drug-resistant bacterial populations. Understanding these mechanisms is essential for predicting resistance dynamics and developing targeted strategies to curb the spread of AMR. This research aligns with the theme of population health by addressing a pressing public health challenge that transcends individual patients and impacts entire communities. By contributing to the development of interventions that slow the spread of resistance, my work aims to safeguard the effectiveness of antibiotics and protect global health equity.
Aida Chan, Investigating the 7DW8-5 Adjuvant and its Efficacy in a Malaria Vaccine
Malaria remains one of the world’s most enduring public health challenges, causing over 250 million infections and 500,000 deaths per year. It is well known that malaria is particularly endemic in Sub-Saharan Africa, which accounts for 95% of global malaria-related deaths, with 76% of deaths among children under the age of five. Currently two vaccines, RTS,S/AS01, and R21, are approved for administration to children under five years of age. Unfortunately, while these vaccines confer protection against malaria for adults, their efficacy is significantly curtailed in pediatric patients. In addition, the efficacy of these vaccines wanes over time, suggesting a lack of long-term protection against the pathogen. These two shortcomings, coupled with stalled progress in treating and controlling clinical malaria, have underscored the need for novel vaccines against malaria. My research investigates how the 7DW8-5 glycolipid adjuvant improves malaria-targeting lipid-nanoparticle vaccines. Through dose-optimization experiments, I seek to identify safe and effective vaccine formulations. My findings will not only advance our understanding of malaria vaccines but also contribute to the broader field of vaccinology. The COVID-19 pandemic highlighted the vulnerability of populations to infectious diseases, revealing the need for preventative instead of reactionary public health interventions. In the wake of growing distrust and skepticism towards vaccines nationwide, continued research to optimize vaccine efficacy, safety, and public confidence is crucial. By aiding the development of a more effective malaria vaccine, my work contributes to the worldwide endeavor to resolve one of the world’s most pressing public health crises.
Shawn Panh, Dissecting the Striatal Circuitry Underlying Drug-Seeking Following Self Administration of Methamphetamine and Fentanyl
Substance use disorder (SUD) is a national epidemic afflicting over 50 million people in the United States. Among those presenting with a SUD, polysubstance use is much more common than single substance use and is associated with increased risk of morbidity and mortality. Additionally, polysubstance users are less responsive to opioid use disorder (OUD) treatments, increasing the propensity for relapse and overdose risk. Notably, addiction disproportionately impacts individuals from marginalized communities, lower socio-economic backgrounds or those exposed to negative environmental influences, which can only be remedied through a deeper understanding of the underlying pathology. There are no FDA-approved treatments for polysubstance use, and current OUD treatments are limited in their ability to reduce relapse vulnerability. Thus, there is a need to further understand the neural mechanisms driving polysubstance use to develop effective therapeutics. This project provides critical insights into neural circuits regulating polysubstance use. Through a translational rodent model of human polysubstance use, we can investigate the behavioral and neuronal changes from polysubstance use, enabling the innovation of novel, effective and targeted therapies. The development of accessible interventions for polysubstance use will have a profound impact on public health by improving health outcomes, reducing the economic burden of patients and healthcare systems, and guiding policies to improve healthcare access and support for vulnerable populations. By learning more about the underlying mechanisms of polysubstance use, we can take significant steps toward enhancing population health and mitigating the impact of substance use disorders worldwide.
Aleah Eve Rosner, Investigating Contact-Dependent and -Independent Effects of Microglia on Neurons in a 2D Co-Culture Model
Alzheimer’s disease (AD) is the 5th leading cause of death for American adults 65 and over. Nearly 7 million individuals live with AD nationwide, and an additional 11 million provide $350B worth of unpaid care at the expense of their own well-being. With no cure, current medications only treat severe stages after significant damage has occurred. My project, which investigates the relationship between neurons and microglia (innate immune cells in the brain), offers insight into potential sources of dysregulation that contribute to AD progression, and informs a direction for therapeutics that treat AD before progression to advanced stages. In the healthy brain, microglia release factors and cytokines, perform synaptic pruning, and execute phagocytosis to support neuronal health and promote a functional neural network. In AD, microglia adopt an activated morphology, releasing pro-inflammatory cytokines that accelerate disease progression. My project focuses on healthy neuron-microglia interactions. I investigate whether observed beneficial effects occur exclusively during physical contact between the two cell types, or if the supportive factors secreted by microglia alone are sufficient to drive this change. By determining the primary mechanism by which microglia benefit neurons, we may uncover points for dysregulation in this relationship that contribute to AD progression as described above. These results may also inform therapeutics that harness the mechanisms of this beneficial neuron-microglia relationship to promote the maintenance of a stable neural environment before AD progresses. This would significantly improve quality of life for folks living with Alzheimer’s and ease the burden placed on their caregivers.
Julien Goldstick, Investigation into rapTOR Regulation of Mitochondrial Dynamics in Response to Hypoxic Injury
Deprivation of oxygen, known as hypoxia, disrupts cellular homeostasis and if not restored, leads to cell death. Strokes and heart attacks caused by hypoxic cell death are the most prevalent form of debilitating diseases in the United States. The goal of the Crowder Lab is to use genetics to discover novel mechanisms leading to the development of effective therapies for hypoxic injury. Under the mentorship and guidance of primary investigator Dr. Crowder and head research scientist Dr. Sun, I am conducting my own independent research project to investigate how the rapTOR protects C. elegans from hypoxia-induced mitochondrial fragmentation. My preliminary findings suggest that cells can exhibit severe levels of hypoxia-induced mitochondrial fragmentation while still being hypoxia resistant. The research has direct implications for population health in life-or-death scenarios. Currently, physicians’ only option to treat ischemia, tissue damage from hypoxia, is to restore blood flow. However, during surgery immediate reperfusion may not always be feasible. My research shows it may be possible to stabilize cells under hypoxic conditions even with significant mitochondrial pathology, potentially informing development for new therapies anesthesiologists can use to improve patient outcomes. By uncovering genetic mechanisms that mitigate hypoxic injury, we have the potential to impact all populations by advancing treatments for hypoxia-related conditions. Ultimately, my research at the Crowder Lab’s aligns with population health by addressing one of the most pressing medical challenges, hypoxia, and striving to discover equitable, effective therapeutic solutions for treating hypoxia-mediated diseases for all communities.
Anna Fong, Do Youth-Focused Clinicians Learn Just as Well in Online Versus In-person Evidence-based Training?
Evaluating the effectiveness of online evidence-based treatment (EBT) training is an essential step in increasing quality mental health care access to the most vulnerable youth. Community mental health (CMH) centers mainly serve youth who are uninsured or Medicaid-covered, including youth of color and youth facing financial adversities (Substance Abuse and Mental Health Services Administration, 2022). While EBTs have been well studied and shown to be effective in treating mental health challenges, they remain underused in CMH settings, in part due to time, cost, and location barriers. Thus, the lack of access to EBT training among CMH clinicians directly impacts the ability of the most vulnerable youth to receive the highest quality care. My project aims to evaluate whether youth-focused CMH clinicians can learn just as well in online training versus in person. Regarding the population health pillars, the flexible arrangement and lowered financial cost of online provider training suggest that clinicians can access training even when logistical barriers might prevent them from participating in in-person training. This is especially useful in under-resourced settings, such as CMH settings, that may not have enough funding to sponsor in-person training (Meyer et al., 2020). Second, the findings from this study can help inform the best EBT training methods for CMH clinicians to help address mental health disparities among underserved youth. Ultimately, increasing effective training access is an initial step to increasing overall access to effective interventions for youth.
Anika Consul, Hyperglycemia Associated with Diabetes as a Driver of Monocyte Lipid Uptake
People with Type 2 diabetes have an increased risk of developing CVD. Hyperglycemia is a hallmark of diabetes, but diabetes can also result in increased levels of triglyceride-rich lipoproteins such as very-low-density lipoprotein (VLDL), a condition known as diabetic dyslipidemia. Diabetic dyslipidemia is believed to contribute to the augmented CVD seen in diabetes. In the bloodstream, an immune cell population known as monocytes accumulates in the artery wall in atherosclerosis, which is the underlying process resulting in CVD. Monocytes and macrophages can engulf lipids and foam cells. Lipid-laden cells are a hallmark of atherosclerosis. My project investigates how glucose-mediated increase in CD36 expression increases the lipid uptake of monocytes. Understanding this relationship is vital for addressing the prevalence of type 2 diabetes which corresponds to the Population Health pillar of human health. In T2D, insulin resistance is a major issue. Monocytes and other immune cells play a large role in inflammation, contributing to insulin resistance since the increased lipid uptake by CD36 can lead to lipid accumulation, which may trigger an inflammatory response. Insights gained from this research will help develop targeted interventions to mitigate diabetes cardiovascular disease progression driven by lipid-loaded macrophage accumulation. T2D has long been a prevalent population health issue. Thus, if we can modulate CD36 expression, it might be possible to restore efficient fatty acid utilization, reducing excess free fatty acids that contribute to insulin resistance in T2D. This information can better help inform public health interventions and contribute to the holistic approach of population health.
Hyunji Park, BAF Complex Inhibitor in B-Cell Acute Lymphoblastic Leukemia
B-cell acute lymphoblastic leukemia (B-ALL) is the most common pediatric cancer and the second leading cause of cancer death among children. Standard therapies, including drugs such as dexamethasone and vincristine, achieve remission in approximately 90% of cases, but 10% of patients exhibit resistance. Patients endure severe short- and long-term toxicities, contributing to disparities in cancer care. Thus, improving treatment strategies that maintain efficacy while reducing harm is essential. My research evaluates the efficacy of FHD-286, a BRG1/BRM ATPase inhibitor, in combination with dexamethasone and vincristine, hypothesizing that the combination may overcome treatment resistance and reduce toxicity in B-ALL. By testing these combinations across genetically diverse B-ALL cell lines, I aim to identify safer, more effective drug regimens that enhance cancer cell death while minimizing harm to healthy tissues. Our findings suggest that FHD-286 demonstrates significant effectiveness in KMT2A-rearranged B-ALL, a high-risk subtype prone to relapse, while also showing potent effects in non-KMT2A-rearranged B-ALL. If this approach enhances treatment efficacy, it could reduce the need for prolonged chemotherapy, lowering hospitalization rates and making effective therapy more accessible across diverse populations. By optimizing treatment strategies, my research supports a shift toward more sustainable, patient-centered oncology care. Demonstrating the effectiveness of FHD-286 in overcoming resistance could expand treatment options and reduce reliance on highly toxic regimens, ultimately improving survival rates, quality of life, and long-term health outcomes for diverse patient populations.
Laila Almansour, Unpacking Gender Disparities: The Role of Sense of Mattering for Women in Computer Science
My research, Unpacking Gender Disparities: The Role of Sense of Mattering for Women in Computer Science, examines the psychological and social factors that contribute to gender disparities in STEM. Specifically, I investigate whether a woman’s sense of mattering—the perception that her contributions are valued—affects participation, interest, and anticipated performance in male-dominated fields like computer science. Through an experimental study involving 200 participants, I manipulate peer recognition levels in a simulated group task to assess whether increased recognition enhances engagement and motivation, particularly for women. This research aligns with the Population Health Recognition Award by addressing systemic barriers to gender equity in education and workforce participation—critical determinants of public health. When women experience diminished recognition in academic and professional settings, they may disengage from high-opportunity fields, contributing to long-term disparities in economic stability, occupational health, and mental well-being. By identifying how social cues influence participation, my study provides insights for interventions that can foster inclusive learning and work environments. My research also has broader implications beyond STEM, offering strategies to promote equity in various disciplines and workplaces. Understanding the role of sense of mattering can inform educational and organizational policies that improve psychological well-being, retention, and professional success for underrepresented groups. By fostering environments where women feel valued and empowered, this work advances population health by reducing social and economic disparities, ultimately contributing to a more equitable and thriving society.
Madeline Marie Baird, Application of Metabolic Assays to Characterize Thermal Tolerance in Pacific Oyster (Magallana gigas) Early Life Stages
Human health is deeply interconnected with environmental health. Aquaculture plays a vital role in sustaining global nutrition by providing a reliable source of seafood rich in essential omega-3 fatty acids. Additionally, it supports livelihoods and creates jobs, contributing to economic stability in coastal communities. Oyster farms, for example, are a major source of seafood production, especially in the US Pacific Northwest, but they are highly vulnerable to disturbances including heat waves and disease outbreaks, which can threaten both industry sustainability and food security. Protecting farmed stocks from significant losses is crucial to maintaining a stable supply of healthy seafood. My research on the thermal and immune stress responses of Pacific Oysters is particularly relevant to public health and sustainable aquaculture. By understanding how oysters respond to increasing marine heatwaves and disease exposure, farms can develop more resilient stocks that are better equipped to withstand environmental stressors. This work provides knowledge necessary to implement resilience strategies in aquaculture operations in order to ensure the continued persistence of shellfish and availability of high-quality, nutritious seafood.
Rohan Pandey and Ray Chen, Model comparison and parameter identification for CAR T-cell cancer therapy
CAR T-cell therapy has transformed cancer treatment, offering remarkable success for blood cancers like B-cell acute lymphoblastic leukemia (B-ALL). However, variable patient responses—from sustained remission to relapse—create disparities in outcomes that directly challenge population health goals of equity and optimized care at scale. Our research addresses this by bridging computational modeling and clinical data to decode heterogeneity in treatment responses. Using systems of ordinary differential equations and nonlinear mixed-effects modeling, we analyze variability across 10 B-ALL patients to identify population-level patterns and patient-specific factors driving outcomes. By systematically comparing mechanistic hypotheses against real-world data, we determine which biological variables (e.g. CAR T-cell expansion kinetics, tumor antigen density) most strongly predict relapse or remission across diverse subgroups. This work advances population health in two key ways: First, our models provide a framework to stratify patients by predicted response, enabling clinicians to tailor therapies before treatment—reducing trial-and-error approaches that disproportionately harm high-risk populations. Second, by quantifying how individual variations (e.g., immune cell dynamics) cascade to population-level outcomes, we inform strategies to optimize dosing protocols and timing for broader demographic groups, not just idealized “average” patients. Translating these insights into clinical decision-support tools could standardize care quality while preserving personalization—a critical balance in population health. By linking mechanistic biology to scalable predictive analytics, our work aims to reduce disparities in CAR T-cell therapy access and efficacy, ensuring advances in immunotherapy benefit the widest possible patient populations.
Mahek Nizar and Mahriban Yalkapova, AI-Augmented Chatbot for Tuberculosis Treatment Support
Tuberculosis (TB) remains a significant global health challenge, especially among underserved populations who face barriers in accessing timely and accurate medical support. Effective communication between patients and healthcare providers is crucial for improving treatment adherence, but many individuals struggle with understanding and engaging in the care process. This research seeks to address these challenges by developing an AI-augmented chatbot designed to provide guideline-based responses to Spanish-speaking TB patients. By integrating a Human-System Interaction (HSI) interface, the chatbot ensures accessibility and user-friendliness while optimizing communication. Using three advanced models—a two-step pipeline, a few-shot model, and a combined Retrieval-Augmented Generation (RAG) with few-shot model—the system delivers responses with high levels of empathy, linguistic fluency, and medical accuracy. This chatbot contributes to human health by offering reliable and timely support, which can improve patient adherence and reduce the burden of TB. Additionally, by increasing access to medical care and supporting adherence, the system enhances environmental resilience by helping prevent the spread of TB within communities. The model also promotes social and economic equity by bridging healthcare gaps for underserved populations, providing them with the tools they need for better health outcomes. Currently undergoing external evaluation by healthcare professionals, the system will be further refined based on feedback. Ultimately, this research aims to implement AI-driven solutions in TB care, contributing to health equity and global efforts to combat tuberculosis. This undergraduate research is supported by a UW PHI Tier 1 Pilot Research Grant on “Building and evaluating AI-augmented treatment support for individuals with tuberculosis.”
Please visit our funding page to learn more about these awards.