Tuberculosis (TB) remains a major global health challenge, causing over a million deaths annually despite being a curable disease. A critical issue is treatment non-adherence, as many patients struggle to complete the required six-month regimen due to a lack of support and access to reliable medical guidance. Improving treatment adherence can significantly increase recovery rates and save lives. This project develops an AI-augmented chatbot powered by GPT-based models to assist Spanish-speaking TB patients. This is done by providing accurate medical guidance, fostering empathy, and enhancing communication between patients and healthcare providers. Integrated into a Human-System Interaction (HSI) interface, the system employs three AI models: a two-step pipeline that classifies messages as informational or emotional to tailor responses appropriately, a few-shot model that generates responses based on examples from prior patient interactions, and a Retrieval-Augmented Generation (RAG) + few-shot model that retrieves relevant medical information from guidelines while maintaining conversational fluency. These models leverage the same underlying technology as ChatGPT, optimizing responses for accuracy, linguistic fluency, and empathy. As part of the research team, I contributed to model development and implementation, ensuring alignment with medical guidelines and human-centered design principles. The chatbot is currently undergoing external evaluation by a multidisciplinary team, including healthcare professionals specializing in TB treatment and AI researchers. Evaluators interact with the chatbot using personas as TB patients, asking medical and support-related questions to assess response quality. They rate the system based on medical accuracy, linguistic fluency, empathy, and other key criteria relevant to patient-provider communication. Insights from this evaluation will guide future refinements, with the goal of improving AI-driven patient support systems in clinical settings.

Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) is a fatty acid β-oxidation disease associated with severe hypoglycemia and sudden death. MCADD is caused by biallelic pathogenic variants in the ACADM gene, which codes for a dehydrogenase specific to carnitines C6 through C12. MCADD is included in newborn screening (NBS) and characterized by elevated medium-chain acylcarnitine fats, annotated as C6, C8, and C10:1. Diagnostic testing is performed in plasma. Acylcarnitine results in dried blood spots have been described to differentiate carriers from affected individuals to reduce false positive NBS. Disease sensitivity and specificity, particularly to differentiate carriers from true positive cases, has not been well described in plasma. We posit that MCADD diagnosis will be more accurate if additional ratios beyond the primary disease markers, C6, C8, and C10:1 acylcarnitines, are considered. This study is a retrospective data review of NBS cases that were positive for possible MCADD and diagnostic testing was performed at Seattle Children’s Hospital. Cases are sorted into four groups: MCADD with homozygous disease variants, compound heterozygous MCADD, carriers of MCADD, or true negative. In collaboration with the biostats core service, linear regression models and receiver operator characteristic curves will compare acylcarnitine species and ratios by group. Preliminary results demonstrate that the primary markers associated with MCADD, C10/C2, C10/C6, C8/C2, C8/C10, and C8/Free carnitine, clearly discriminate affected individuals from control cases in plasma. Analysis is in process to compare the different genotypes of affected MCADD from carriers. Uncovering the diagnostic accuracy of plasma acylcarnitine profiles may influence future testing plans and improve the cost-effectiveness of healthcare services. DNA testing remains costly and slow. Additional biomarkers that provide a conclusive diagnosis of MCADD without requiring genetic testing may lead to more equitable patient care.

Dementia, a growing global health concern, affects the nervous system and leads to severe cognitive impairment, with Alzheimer’s disease (AD) being the most common form, currently impacting nearly 7 million Americans. As life expectancy increases, the prevalence of dementia increases in corresponding fashion, driving research efforts like those of the Darvas Lab, where we study AD and other related dementias using adeno-associated viruses (AAVs) to induce neuropathologic changes. The TDP43 protein is involved in neuropathologic changes such as those in Frontotemporal Dementia (FTD) and in Amyotrophic Lateral Sclerosis (ALS), a primary motor neuron disorder. TDP43, primarily localized in the nucleus, plays a crucial role in regulating gene expression and RNA metabolism. TDP43 pathology in neurons involves the presence of TDP43 in the cytoplasm and its accumulation in cytoplasmic inclusions. To better understand the role of TDP43 in neurodegeneration, we use a mouse model where TDP43 proteins are introduced via AAV, a genetically engineered viral vector commonly used in research. This approach allows control over the timing of neuropathologic changes. Our prior AAV constructs included the Synapsin I promoter, which led to a severe ALS-like motor phenotype due to its expression in spinal motor neurons. However, this model could not be used to study the more subtle effects of dementia due to the extreme nature of the physical pathology. Therefore, our goal is to produce a new model to overexpress TDP43 using an AAV that is exclusive to the cortical brain regions relevant to FTD by instead including the CamKIIα promoter, which exclusively drives expression in the forebrain. I assessed behavioral phenotypes in our mouse model by conducting a Y-maze to evaluate effects on short-term memory, and analyzing neurological scoring to evaluate neuromuscular dysfunction. The development of a more dementia-focused TDP43 model will allow us to more specifically investigate its neuropathology.

TDP43 is an RNA/DNA binding protein that forms pathological aggregates in most amyotrophic lateral sclerosis (ALS) and half of frontotemporal lobar degeneration (FTLD) cases. Knockout of TDP43 in animal models leads to neurodegeneration and motor deficits, but overexpression of wildtype TDP43 leads to the same events; therefore, TDP43 protein homeostasis is critical to prevent ALS/FTLD. To achieve this homeostasis, TDP43 autoregulates its own mRNA splicing, resulting in multiple TDP43 isoforms. Although some of these isoforms go through nonsense mediated decay, other isoforms result in unique proteins with differing C-termini. This leads to variable cellular localization. It is unknown if these alternative, protein-coding isoforms are predominantly associated with ALS/FTLD or if aging changes the frequency of these isoforms. To determine how TDP43 overexpression yields different isoforms and interacts with aging and ALS-like symptoms, the Darvas Lab created a novel approach to overexpress human TDP43 (hTDP43) via Adeno-Associated Virus (AAV) delivered through retro-orbital injection, leading to ALS-like motor deficits. We tested this AAV in young and old mice cohorts. Then, to determine if Tardbp alternative splicing is linked to ALS-like symptoms and aging, I designed and validated primers and protocols to measure the nine Tardbp mRNA isoforms in mice via quantitative real-time polymerase chain reaction (qRT-PCR). I have started to determine if hTDP43 overexpression leads to differential splicing compared to mice injected with a sham-control AAV in these old and young mice. Once this is done, we will clone the most interesting differentially spliced isoform in an AAV and inject that AAV and a full-length TDP43 AAV into mice to see if the spliceform causes increased toxicity, manifesting in worsening motor deficits and mortality.

Most cultures have some aspect of puppetry from history, ranging from single puppeteers to three expert manipulators using one doll to express human emotions, but Vietnamese water puppetry, or Múa rối nước, has been a staple of Viet Nam’s culture since it was introduced by the Chinese thousands of years ago. Performers standing waist deep in water (originally rice paddies) use bamboo sticks to manipulate vividly painted puppets to entertain the public and tell legends through this aquatic method. It is estimated to be over 1000 years old in Viet Nam alone. Given China was the largest occupier for centuries, Vietnam was once a protectorate under ancient China. Current assumptions are that Chinese occupiers brought teachings of the puppeteering craft and passed their knowledge onto northern villagers, and after the cultural influence had faded as occupation was replaced by Vietnamese nationalism, the culture of retelling history via water puppets transformed into a uniquely Vietnamese tradition. Each puppeteer would carve and control their own puppet, passing the knowledge to the next generation through self-training and shared community. Through my close readings of live and recorded Múa rối nước, and by examining others' writings about this practice's evolution throughout history as well as local reception, I will seek to answer why such a unique form of theatre has gone unnoticed and under-appreciated in our modern era of spectacle. And with tourism already being a primary draw to Viet Nam, how can those working on Múa rối nước harness its potential for global recognition?

Data is the fuel driving AI innovation. Much of the most valuable data is, however, siloed in research centers, hospitals, banks, etc. The onerous processes researchers must go through to access each silo cause a substantial underutilization of AI in many of the most important domains, including healthcare and genomics. AI researchers cannot train models for personalized medicine if they cannot get their hands on enough relevant patient data. One way to provide broader access for research while also retaining the privacy of the original data is with synthetic data generation (SDG), which uses machine learning to generate a set of synthetic data similar enough to the real data to retain its value for research while also anonymizing it. While in some cases a single data custodian (such as a hospital) alone may have enough data to train a generative model, usually, datasets from multiple custodians need to be combined to reach a cumulative size that enables meaningful AI research. The latter is, for example, often the case for rare diseases, with each clinical site having data for only a small number of patients, which is insufficient to train high-quality synthetic data generators. The goal of my research is to generate synthetic genomics data of patients with Neurofibromatosis type 1, a rare genetic condition that causes changes in skin pigment and tumors on nerve tissue. Thanks to our Privacy-Preserving Machine Learning Lab’s inclusion in the National Artificial Intelligence Research Resource (NAIRR) Pilot and our collaboration with Sage Bionetworks, I have access to the TACC Frontera supercomputer at the University of Texas and multiple sets of NF1 patient data. Results of my work on the NAIRR include an empirical evaluation of cross-silo federated SDG algorithms in terms of quality of the generated NF1 data, computational cost, and level of privacy protection.

The Bed Trick, a recent play by Keiko Green, premiered at Seattle Shakespeare Company in Spring of 2024. It is a meta adaptation of William Shakespeare’s All’s Well That Ends Well and is named for a narrative trope, the bed trick, that features prominently in Shakespeare’s play. In her play, Green deconstructs and reworks the titular narrative device and engages metatextually with All’s Well That Ends Well to examine the themes of consent, honesty, loyalty, and friendship. Green uses a variety of adaptive strategies to examine the ethical holes in All’s Well That Ends Well. Rather than directly adapting her source, she uses it as a jumping off point for her own story, and warps the structure of the trope of the bed trick to engage with current socio-political conversations around consent, rape, sex, and the boundaries thereof. I attended a performance of The Bed Trick toward the end of its first run, and it fascinated me so much that, four months later, I made it the focus of a research project for an adaptation studies class. In addition to utilizing my first-hand knowledge of play, I also accessed the primary text through the New Play Exchange, as it is a new play unavailable in libraries or bookstores. In my presentation, after briefly summarizing All’s Well That Ends Well and outlining the basic structure of the bed trick, I will walk through my original research of Green’s play, examining her various mutations of the bed trick, the ways that she engages metatextually with All’s Well That Ends Well, and the adaptive strategies she uses. The Bed Trick is a fascinating example of meta-adaptation and a highly contemporary and socially engaged piece. It is well-worth an exploration to analyze its purpose and structure, and adds greatly to discussion of theatrical adaptation.

As of 2025, the United States has the highest incarceration rate in the world, with its incarcerated population making up 25% of the incarcerated individuals worldwide. Mass incarceration inflicts the most harm on the most vulnerable populations, disproportionately affecting racial and ethnic minorities and creating insurmountable barriers to reintegrating into society. Prison education programs provide opportunities for growth that help prevent recidivism and support rehabilitation efforts, and with the reinstatement of Pell Grants for incarcerated individuals in 2023, there has never been a better time to expand educational opportunities than now. However, little research has been done on prison education programs, with even less research focusing on enhancing and expanding them to address the specific needs of incarcerated individuals, particularly in digital literacy. In a rapidly evolving digital world, it becomes imperative to ensure that incarcerated people, many of whom have had limited experiences with technology due to extended sentences, have the skills to confidently return to a digital society. This project explores how integrating computer science curricula into correctional facilities can increase rehabilitation, reduce recidivism outcomes for incarcerated individuals, and further support other pre-existing educational programs in prisons. To answer this question, we examined legal documents, performed literature reviews, analyzed previous studies on the incarcerated population, and conducted a comprehensive analysis of outcomes from prior prison education programs. Our findings reveal that computer science education for incarcerated people increases self-efficacy rates, post-employment opportunities, and facilitates a smoother transition back into society. Additionally, integrating computer science through enhanced digital infrastructure can address challenges with current educational programs, such as accessibility, course expansion, and classroom segregation. Collectively, this project represents one of the first studies to explore the possibilities for computer education and prisons, offering valuable insights into the potential to improve rehabilitation, reduce recidivism, and address the digital divide.

Ocean eddies contribute significantly to the transfer of heat and energy throughout the world’s oceans, playing a key role in regulating climate. Eddies are observed predominantly through Earth-orbiting satellites that collect data on sea surface height (SSH), a metric that can be used to estimate eddies on a global scale. Historically, satellites could only capture point-wise measurements, resulting in low-resolution SSH maps, which led to underestimations of small-scale eddy strength. Launched in 2022, NASA’s Surface Water and Ocean Topography (SWOT) satellite now provides groundbreaking 2D SSH imagery with higher resolution relative to existing SSH products. However, there are only two years of SWOT data available, unlike other satellites with decades-long records. Here, we considered how the recent SWOT data could be deployed to improve the spatial resolution of SSH products from the preceding 30 years. To achieve this, we trained an image-to-image U-Net neural network to predict the high-resolution SSH from an existing low-resolution product (NeurOST). We used SWOT high-resolution data as a ground truth to train this neural network and minimize the mean squared error of the SSH output with respect to the SWOT data. By evaluating the accuracy of the SSH output maps against an independent withheld satellite, we demonstrated that our method improves the spatial resolution of the SSH product compared to the NeurOST dataset. We next plan to test the accuracy of our method when applied to years before SWOT was launched. Overall, our research highlighted how leveraging deep learning and SWOT can enhance the spatial resolution of a decades-long eddy observation time series, enabling more accurate studies of eddies and their climate impact.

Visual perspective-taking (PT) is a fundamental spatial cognition task, requiring an individual to adopt another’s viewpoint. Previous experiments have shown that response times increase as the angular difference between viewer and reference perspectives grows. Preliminary fMRI results suggest that neural activity in specific brain regions follows a similar pattern, their activity increases as a factor of angular difference, reflecting the cognitive demands of mental perspective transformation. However, little is known about how eye-gaze behavior varies in this task. In this study, we analyze eye-tracking data collected during fMRI scans with an Eyelink 1000 to examine the relationship between gaze patterns and perspective alignment. Specifically, we investigate whether eye-gaze behavior differs between aligned and unaligned trials and whether angular difference influences gaze dynamics. Gaze coordinates (xpos, ypos) will be analyzed trial-by-trial to determine how visual attention is modulated during perspective-taking. Understanding these gaze patterns may provide insights into the strategies used in spatial perspective shifts and their neural underpinnings.

Previous research indicates that males typically outperform females in spatial perspective-taking tasks where an individual is prompted to assess a scene by adopting a perspective other than their own. However, a recent study, with only female participants, found an increase in female perspective-taking performance when the task asked subjects to take the perspective of a social agent. Many have theorized that this performance increase is exclusive to females, who are believed to hold superior social skills. This implies a distinction between purely spatial perspective-taking and social perspective-taking, the latter of which females are theorized to perform better at. More recent studies have countered this notion, suggesting that directional information provided by a social agent could explain the increased performance in females. Assessing the relationship between spatial and social perspective and sex-based differences in performance can provide insight into social perspective-taking in human cognition. To clarify the influence of social agents on perspective-taking performance in both males and females, we administered two spatial perspective-taking tasks, with either a social or non-social agent. We aim to clarify theorized sex-based differences in performance by comparing accuracies and reaction times in social and non-social conditions. We hypothesize that male and female performance in perspective-taking tasks will be equally affected by the presence of a social agent.

Understanding and predicting changes in primary productivity depend on both upper ocean warming and nutrient supply from the ocean interior. Fronts, where distinct water masses converge, are hotspots for these vertical exchanges, transporting nutrients upward and supporting diverse ecosystems. These fronts create sharp gradients in temperature and salinity, generating strong vertical velocities that upwell nutrients and biomass. However, the exact dynamics of frontogenesis (the formation of fronts) remain poorly understood. Additionally, these processes occur at scales too fine to be resolved in global climate models and are only marginally captured by high-resolution ocean simulations. This underscores the need for observational studies to characterize frontogenesis and test existing theoretical frameworks. In this study, we diagnose frontal dynamics using Petterson’s frontogenesis function, which quantifies the roles of divergence and strain. Using NcCut, a GUI developed by our group, we compiled a unique dataset capturing the full life cycle of numerous ocean fronts in front-following coordinates from a state-of-the-art ocean simulation. Our results indicate that for mesoscale (~100 km) fronts, strain dominates over divergence, aligning with classical theories. In contrast, submesoscale (~10 km) fronts exhibit shorter life cycles and no clear dominant driver of frontogenesis within the Petterson framework. We also identified key limitations in conventional diagnostics and improved our analysis by masking the front from its surrounding environment before diagnosing its drivers. This enhancement provides a more accurate representation of frontogenesis dynamics. In the future, we plan to apply our method to satellite observations to study real-world ocean fronts, validate ocean models, and improve predictions of primary productivity changes. Our findings highlight the importance of refining frontogenesis diagnostics to better capture the small-scale dynamics critical to ocean biogeochemistry and climate predictions.

Following an extensive history of industrial activity in Commencement Bay, Washington, the health of marine ecosystems continues to be affected by persisting pollutants. Commencement Bay has been identified as a Superfund Site, in which the Environmental Protection Agency (EPA) is tasked with cleaning up locations contaminated with hazardous materials. In an effort to gauge just how effective these recovery efforts have been, this study, part of the Puget Sound Foraminifera Project at the Burke Museum, investigates how the density and diversity of benthic foraminiferal assemblages have changed over time. Foraminifera, a diverse and widespread order of shelled marine protists, can be utilized as a reliable measure of marine ecosystem health due to their innate sensitivity to environmental changes. Samples collected by the Washington Department of Ecology (WDOE) from 2014 and 2022 allow for a comparison of diversity indices that are indicative of the success in the bay’s recovery. To quantify this success, calculations of the Shannon Index and the Simpson Index were completed for each sample, supporting our determination of the Foraminiferal Benthic Index (FBI) of the region. The FBI was defined using measures of abundance, diversity, and percentages of tolerant species present in each sample to quantify the extent of adversity. With 2022 density and diversity averages that are statistically similar to those of 2014, we can conclude that clean up efforts have not yet made sufficient measurable improvements in the Foraminiferal Benthic Index over the previous eight years.

Protein Kinase Inhibitors (PKIs) are a family of heat stable, high-affinity inhibitors of the catalytic subunit of Protein Kinase A (PKAc). In the presence of Mg-ATP, the three isoforms—PKIα, PKIβ, and PKIγ—bind to PKAc with very low dissociation constants: 0.758nm, 1.875nm, and 0.4142nm respectively. In vitro studies have shown that PKIs can translocate PKAc from the nucleus to the cytoplasm, suggesting a role for PKIs in terminating nuclear cAMP-driven PKA activity. Previous research, including studies from our lab, has found that dysregulated PKAc mutants play a significant role in Cushing’s syndrome, a rare and potentially fatal metabolic disorder caused by excessive cortisol production. Building on these findings, we hypothesized that increasing PKI expression could counteract the hyperactivity of PKAc mutants and reduce cortisol production. To test this, we expressed each PKI isoform in adrenal cell lines and assessed their steroidogenic capacity using biochemical assays such as western blots, RNA-seq, qPCR, and ELISA-based cortisol assays. We observed that PKIα and PKIγ led to a general suppression of steroidogenic associated proteins such as StAR, Cyp11a1 and SF1. This altered proteome was accompanied by significantly suppressed cortisol synthesis only in the PKIα and PKIγ expressing cells. The difference between PKIα/γ and PKIβ was surprising given that all PKI isoforms are postulated to potently inhibit PKAc. Thus, we questioned whether PKIα/γ effects are mediated through PKAc. To answer this, we have cloned mutant PKI isoforms that do not bind PKAc, and confirmed the mutant PKIs do not inhibit PKAc through kinase assays. Our next step is to express the mutant PKI isoforms in adrenal cells and assess their effect on steroidogenic capacity of the cells. Our findings suggest that PKIα and PKIγ play key roles in cortisol regulation and may have broader implications for gene regulation in adrenal cells.

Visuospatial attention is a complex, dynamic process critical to our conscious perception of the world. The N2pc event-related potential (ERP) is a time-locked EEG waveform implicated in the modulation of visuospatial attention and observed in Posner task paradigms. The N2pc ERP functionally represents attention mechanisms, with hypotheses suggesting it could represent target enhancement or distractor suppression. Further, perceptual differences have been found in autism spectrum disorder (ASD) populations, suggesting that these differences could be discriminated in N2pc properties. Visuospatial cueing differences are observed in autistic individuals, yet the neural mechanisms underlying these differences remain unclear. This study investigates possible differences in the N2pc component reflecting distinct patterns of attentional modulation in autism. We conducted 32-electrode EEG recordings of neurotypical and autistic adults engaged in a Posner paradigm visual detection task, detecting grayscale circles embedded in a checkerboard stimulus. Using MatLab and EEGLAB, we expect to localize N2pc ERPs in parietal regions in epochs post-cue and post-stimulus presentation. We hypothesize that we will see different amplitude and latency N2pc ERPs in autistic individuals compared to neurotypical controls, reflecting differences in attention modulation. Results may provide insight into how attentional mechanisms differ in autistic individuals, allowing for a greater understanding of neurotypical and neurodivergent approaches to visuospatial attention.

Visual Perspective-taking (VPT) is the ability to recognize another’s viewpoint, and can play a role in communication and empathy. Previous research supports that VPT in Autism Spectrum Disorder (ASD) populations is altered compared to neurotypicals (NT), but the traits within both populations that contribute to VPT differences remain unknown. This study investigates how VPT differs in ASD compared to NT adults using both animate and inanimate target objects. We also explore how these differences might be associated with ASD traits, measured by the Social Responsiveness Scale-2 (SRS-2). Participants complete computerized tasks that evaluate how stimuli appear from a different perspective. Psychophysical tests determine participants' ability to identify the position of an object from the perspective of an animate object (an avatar in the image) and an inanimate object (a chair), measuring accuracy and reaction time. We expect to replicate past findings of increased reaction time with greater angular disparity between the participants’ viewpoint and the viewpoint of the target object, for both ASD and NT subjects. We hypothesize this interaction between reaction time and angular perspective for both populations may interact with the type of reference object (animate vs. inanimate) and SRS-2 scores. We believe that NT participants will demonstrate greater accuracy and faster reaction times than ASD participants in both animate and inanimate conditions, with the difference being evident in the animate condition for ASD participants, possibly due to challenges in processing social cues reflected by higher scores on the SRS-2. This research can increase the understanding of the psychological disparities in individuals with ASD compared to NT contributing to diagnostic tools and targeted interventions for improving social cognition in ASD populations and potentially other neurodivergent populations with VPT differences.

The aorta is the largest blood vessel in the body and is responsible for transporting blood to our organs and extremities. A type A aortic dissection (TAAD) is a tear in the inner and middle layers of the ascending aorta. Given the significant and traumatic nature of such an event, the mortality rate is a major concern as some literature cites up to a 2% increase in mortality rate per hour of an individual suffering from TAAD. Genetic aortopathy, which is an umbrella of genetic diseases, significantly increases the risk of catastrophic aortic events such as TAAD. Patients with genetic aortopathy have been found to have an increased risk of aortic dissections which has already proven to be deadly. However, there is very little research that has been done to show the effect of genetic aortopathy on the short-term outcomes of patients who have undergone surgical repair of TAAD. Our goal is to identify whether differences in outcomes between patients with and without genetic aortopathy truly exist. The dataset we are using is localized to treatment at the UW Medical Center, and contains genetic testing on TAAD patients – something very few centers have previously done. To date, we have completed the database entry of the patients relevant to the study and are beginning the statistical analysis phase which is executed with R programming. The results of this study concern both patients and physicians interested in postoperative outcomes. But, to the patient, this is perhaps the most pressing question moving forward. What is the risk of needing a repeat surgery? What effect does this have on my life expectancy? These are all common yet largely unanswered questions which we provide clarity on.