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News and Events

Chair’s Message

pth-use-this-one We are moving toward our vision with a number of activities across our various programs. We have updated our strategic plan in response to the 10-year academic program review that we recently completed. For our research-oriented MS and PhD programs, we have recently added a specialization in Data Science. We are completing a curriculum revision for our on line applied clinical informatics MS which will be effective Fall 2020. The work of our fellows in the clinical informatics fellowship program has received plaudits from clinical administrators and faculty, and we are currently recruiting a new faculty member in our department to assist with this program (view position description). We are also recruiting a faculty member in medical education to start Summer 2020 (view position description). This is the beginning of a new cycle of admissions to our graduate programs, and we look forward to another productive year, and new growth in our department.

Cordially,

Peter Tarczy-Hornoch, MD
Chair and Professor, Department of Biomedical Informatics and Medical Education

Biomedical Informatics and Medical Education Newsletter

September 29, 2025 – October 3, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590
Presenter: Jim Phuong, MSPH, PhD
Thursday, October 9^th – 11-11:50 am
850 Republican Street, Building C, Orin Smith Auditorium (Not C123)
Zoom Information: https://washington.zoom.us/my/bime590
Speaker will present in-person

Title:
Secondary-use data and Real-world data Integration in National Research Consortia

Abstract:
Health systems are uniquely positioned to survey the health of their patient population, including the effects of natural hazards, disaster disruptions, and public health emergencies. As an integral part of the biomedical research landscape, Health systems data sharing supports data-driven research and iterative quality improvements to the data from each health system. Apart from clinical outcomes, health systems are gradually increasing their focus upon collecting and addressing gaps in understanding Social Determinants of Health (or Social Drivers of Health, SDoH) and their dynamic role in maintaining health and wellness. This includes integrating patient-level information as well as place-based information integrated from geocoding and secondary use of spatial-temporal datasets. In this talk, I will discuss the nexus of environmental health, disaster management and population health research, and biomedical informatics research. I will also discuss the directions from health system preparedness, the broader implications towards research data sharing and research consortia with a precision medicine focus, and the analytical capacities needed for research with multiple data types in cloud infrastructure.

Presenter Bio:
Jimmy Phuong obtained his Masters of Science in Public Health degree from University of North Carolina at Chapel Hill in 2014 and his Ph.D. degree in Biomedical Informatics and Medical Education from the University of Washington in 2020. Dr. Phuong’s research is at the intersection of secondary use of Electronic Health Records (EHRs), geospatial-temporal data integration, and informatics capacity development and maturity to enhance population health and precision medicine research. Since 2020, Dr. Phuong co-led the National Clinical Cohort Collaborative (N3C) Social Determinants of Health (SDoH) domain team, focusing efforts to enhance clinical research that integrates patient-level and community-level Social Determinants of Health information. He is the current Chair for the American Medical Informatics Association (AMIA) Informatics Maturity Working Group, site Principal Investigator for the NIH All of Us Research Program Center for Linkage and Acquisition of Data (CLAD) in which he leads Geocoding and Spatial-temporal data integration, and serves on the NIH-NCATS Clinical and Translational Science Award (CTSA) Real-World Data Workforce Development Task Force. I am also an active contributor to the CDC Region 10 Public Health Emergency Preparedness and Response (PHEPR) data ecosystem planning and its collaborative deliverables related to Public Health Data Modernization Initiatives. His interests include exploring cloud-based and research platform data modernization on issues like mass casualty emergencies, trauma outcomes research, and State-Tribal-Local-Territory (STLT) regional partnerships to prepare for and mitigate the impact of regional disasters and environmental health effects.

ANNOUNCEMENTS
Join us for the annual Science & Engineering Career Fair, hosted by the Science & Engineering Business Association (SEBA). This event brings together top employers and talented students for an afternoon of networking, recruiting, and career exploration. Employers will showcase job and internship opportunities across diverse industries, while students gain direct access to recruiters and career resources.
Link to student organization: here

📍 Location: Husky Union Building (HUB), North & South Ballrooms
📅 Date: October 15
🕚 Time: 11:30 AM – 3:30 PM
Whether you’re an employer seeking top talent or a student exploring future opportunities, the SEBA Career Fair is the place to connect, learn, and launch the next step in your career.

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Emerging Topics in Quality Improvement Webinar Series

Always free and open to the public, these webinars highlight trending issues and practical methodologies in quality improvement. Webinars take place on the second Tuesday every other month from 12-1pm PT. Registration is required to attend.

Join us for the next webinar on
Tuesday, October 14, 2025 from 12-1pm

Pathway Assistant: A Use Case in AI for Quality and Safety

Yu-Hsiang “Clara” Lin, MD
Chief Medical Information Officer and VP, Digital Health & Informatics
Seattle Children’s
Clinical Associate Professor
Department of Pediatrics, UW Medicine

Darren S. Migita, MD
Medical Director of Clinical Effectiveness, Center for Quality and Patient Safety, Seattle Children’s Hospital
Clinical Professor
Department of Hospital Medicine, UW Medicine

Register Now for this 10/14/25 Webinar

PAPERS, PUBLICATIONS & PRESENTATIONS

Ojas A. Ramwalawill be giving a talk on Explainable AI for Biomedical Image Processing at PyData Seattle, to be held November 7-9, 2025, at Bellevue College. Additional information can be found here: https://cfp.pydata.org/seattle2025/speaker/BVZDEJ/
Sihang Zeng, Yujuan Fu, Sitong Zhou, Zixuan Yu, Lucas Jing Liu, Jun Wen, Matthew Thompson, Ruth Etzioni, Meliha Yetisgen. Traj-CoA: Patient Trajectory Modeling via Chain-of-Agents for Lung Cancer Risk Prediction. NeurIPS 2025 GenAI4Health Workshop.
Tianmai M Zhang*, Zhaoyi Sun*, Sihang Zeng*, Chenxi Li*, Neil F Abernethy, Barbara D Lam, Fei Xia, Meliha Yetisgen. UW-BioNLP at ChemoTimelines 2025: thinking, fine-tuning, and dictionary-enhanced LLM systems for chemotherapy timeline extraction. Clinical NLP Workshop
Tianmai M Zhang, Neil F Abernethy. Reviewing scientific papers for critical problems with reasoning LLMs: baseline approaches and automatic evaluation. arXiv:2505.23824. AI for Science Workshop at NeurIPS

September 22, 2025 – September 26, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590
Presenter: Gang Luo, PhD
Thursday, October 2^nd – 11-11:50 am
850 Republican Street, Building C, Orin Smith Auditorium (Not C123)
Zoom Information: https://washington.zoom.us/my/bime590
Speaker will present In-Person

Title: Identifying Patients Who are Likely to Receive Most of Their Care from a Specific Healthcare System

Abstract:
Background: In the United States, health care is fragmented in numerous distinct healthcare systems including private, public, and federal organizations like private physician groups and academic medical centers. Many patients have their complete medical data scattered across several healthcare systems, with no particular system having complete data on any of them. Several major data analysis tasks like predictive modeling using historical data are considered impractical on incomplete data.
Objective: Our goal is to find a way to enable these analysis tasks for a healthcare system with incomplete data on many of its patients.
Methods: This study presents, to the best of our knowledge, the first method to use a geographic constraint to identify a reasonably large subset of patients who tend to receive most of their care from a given healthcare system. A data analysis task needing relatively complete data can be conducted on this subset of patients. We demonstrated our method using data from University of Washington Medicine (UWM) and PreManage data covering use of all hospitals in Washington state. We compared ten candidate constraints to optimize the solution.
Results: For the UWM, the best constraint is that the patient has a UWM primary care physician and lives within five miles of at least one UWM hospital. About 16.01% of UWM patients satisfied this constraint. Around 69.38% of their inpatient stays and emergency department visits occurred within the UWM in the following six months, more than double the corresponding percentage for all UWM patients.
Conclusions: Our method can identify a reasonably large subset of patients who tend to receive most of their care from the UWM. This enables several major analysis tasks on incomplete medical data that were previously deemed infeasible.

Presenter Bio: Gang Luo obtained his Ph.D. degree in Computer Science minor in Mathematics at the University of Wisconsin-Madison in 2004. Between 2004 and 2012, he was a Research Staff Member at the IBM T.J. Watson research center. Between 2012 and 2016, he was a faculty member in the Department of Biomedical Informatics at the University of Utah. Gang is currently a Professor in the Department of Biomedical Informatics and Medical Education of the School of Medicine at the University of Washington. His research interests include health/clinical informatics (software system design/development and data analytics), machine learning, database systems, information retrieval, natural language processing, big data, and data mining with a focus on health applications. He invented the first method to automatically provide rule-based explanations for any machine learning model’s predictions with no accuracy loss, the first method to efficiently automate machine learning model selection, the questionnaire-guided intelligent medical search engine iMed, intelligent personal health record, and SQL, machine learning, and compiler progress indicators.

September 15, 2025 – September 19, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590
Presenter: Peter Tarczy-Hornoch, MD, FACMI
Thursday, September 25^th – 11-11:50 am
850 Republican Street, Building C, Room 123 A/B
Zoom Information: https://washington.zoom.us/my/bime590
Speaker will present In-Person

Title: 2025 BIME Vision, History, Strategic Plan and Praxis

Abstract: The presentation will provide an overview of the Department of Biomedical Informatics and Medical Education through the lens of the current strategic plan. The overview will include vision, history and evolution looking at the synergy between research, education and practice (praxis) as well as the synergy between practice, applied research and foundational research. Within each area (research, praxis, education) current activities and future plans will be reviewed.

Presenter Bio: Peter Tarczy-Hornoch has over 40 years of experience in computer science, over 35 years in biomedical informatics and over 20 years in clinical medicine (pediatrics and neonatology). He has been at the University of Washington since 1992, serving as Head of the Division of Biomedical and Health Informatics since 2001 and serving as Chair of the Department of Biomedical Informatics and Medical Education since 2011. He has served in a variety of operational leadership roles in UW Medicine IT Services since 1992 in the analytics, research, and clinical computing domains, currently (since January 2022) serving as UW Medicine Chief Data Officer. He has played a leadership role in the creation and evolution of the BIME educational programs (undergraduate (joint with iSchool), MS/PhD, postdoctoral, applied clinical informatics MS (CIPCT) joint with Nursing, Clinical Informatics Fellowship joint with Family Medicine). He has led a number of key initiatives in informatics practice (praxis) including the areas of telemedicine, digital library, electronic medical records, data warehousing, analytics, clinical research informatics). His unifying theme of research over the last two decades has been data integration of electronic biomedical data (clinical, genomic and other including data) both for a) knowledge discovery and b) in order to integrate this knowledge with clinical data at the point of care for decision support. His current research focuses on a) secondary use of electronic medical record (EMR) for translational research including outcomes research, learning healthcare systems, patient accrual and biospecimen acquisition based on complex phenotypic eligibility criteria, b) the use of EMR systems for cross institutional comparative effectiveness research, and c) integration of genomic data into the EMR for clinical decision support.

PAPERS, PUBLICATIONS & PRESENTATIONS

A Novel Communication Rating Scale to Mitigate the Effect of Implicit Bias, Jennifer Tjia MD, MSCE; Chengwu Yang, MD, MS, PhD; Julie Flahive, MS; Kelly Harrison, MD; Geraldine Puerto, MPH; Vennesa Duodu, MPH; Lisa A. Cooper, MD, MPH; Olga Valdman, MD; Janice Sabin, PhD, MSW,

JAMA Netw Open. 2025; 8(9):e2532319.10.1001/jamanetworkopen.2025.32319

September 8, 2025 – September 12, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025!

ANNOUNCEMENTS
Please join us in congratulating Dr. Raghav Madan who successfully passed his PhD Defense!
Title: NPP: tissue-anchored, GIS-inspired spatial modeling of tau neuropathology

Abstract: I developed NeuroPathPredict (NPP), a pipeline that fuses quantitative histopathology (Alzheimer’s disease) with neuroimaging to generate voxel-based tau distribution maps in unsampled regions . Slide-level AT8 measures are mapped to MNI 2009b via ex vivo MRI (QNPtoVox); voxels are enriched with an atlas “brain-GIS” of tracts, functional networks, vascular territories, cortical geometry, and distance transforms (I-BIS). I fit universal kriging with external drift, selecting a tractable set of primary covariates via Elastic Net, estimating variograms, and validating with spatial block cross-validation. Applied to Adult Changes in Thought (ACT) study data, NPP yields anatomically interpretable effects, competitive prediction versus non-spatial models, and reproducible, donor-comparable pathology distribution fields suited for cross-modal evaluation. Looking ahead, NPP can serve as a reference layer for cross-modal validation and hypothesis testing, and be extended to other proteinopathies and cohorts for scalable, tissue-anchored brain mapping.

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Please join us in congratulating Faisal Yaseen who successfully passed his General Exam!
Title: Treatment response prediction in advanced non-small cell lung cancer: Biomarkers, multiscale, multimodal, and uncertainty quantification

Abstract: With metastatic disease, treatment response can be highly variable, leading to challenging clinical decision making. . Traditional assessment methods, such as computed tomography (CT) lesion size, often fail to capture the spatial heterogeneity of tumor response. Fluorodeoxyglucose (FDG) PET/CT imaging offers the ability to detect early metabolic changes across patient, lesion, and voxel levels. To improve early treatment response prediction and clinical utility, we propose three synergetic yet independent aims: (1) identify FDG PET imaging and blood-based biomarkers to discriminate patient-level treatment response and survival outcomes, (2) develop a multiscale regression framework to predict voxel-level tumor response with uncertainty quantification using conformal prediction, and (3) integrate imaging, blood biomarkers, and clinical data into an multimodal AI framework for early response. Collectively, this project will deliver a clinically relevant decision support prototype to guide personalized therapy in mNSCLC.

PAPERS, PUBLICATIONS & PRESENTATIONS

Feng Chen, Dror Ben-Zeev, Gillian Sparks, Arya Kadakia, Trevor Cohen. Detecting PTSD in Clinical Interviews: A Comparative Analysis of NLP Methods and Large Language Models. Paper accepted by Pacific Symposium on Biocomputing 2026.

September 1, 2025 – September 5, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025!

PAPERS, PUBLICATIONS & PRESENTATIONS

Mastrianni, A., Twede, H., Sarcevic, A., Wander, J., Austin-Tse, C., Saponas, S., Rehm, H., Conard, A.M. and Hall, A.K., 2025. AI-Enhanced Sensemaking: Exploring the Design of a Generative AI-Based Assistant to Support Genetic Professionals. ACM Transactions on Interactive Intelligent Systems.

UPCOMING EXAMS

Final Dissertation Defense
Title: NPP: tissue-anchored, GIS-inspired spatial modeling of tau neuropathology
Student: Raghav Madan
Date/Time: Wednesday, September 10^th, 2025, 12pm PT
In-person location: SLU, BLDG C, C122
Zoom: https://washington.zoom.us/my/jhgennari?pwd=TUx0clkwKzdnS1ZQV1dXRnZqMWMzZz09

General Exam
Title: Treatment response prediction in advanced non-small cell lung cancer: Biomarkers, multiscale, multimodal, and uncertainty quantification
Student: Faisal Yaseen
Date/Time: Thursday September 11^th, 2025, 9am-11am PT
In-person location: HSEB 421
Zoom: https://washington.zoom.us/my/jhgennari?pwd=TUx0clkwKzdnS1ZQV1dXRnZqMWMzZz09

August 25, 2025 – August 29, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025!

PAPERS, PUBLICATIONS & PRESENTATIONS

Placental network differences among obstetric syndromes identified with an integrated multiomics approach. Piekos SN, Barak O, Baumgartner A, Chu T, Parks WT, Hadlock J, Hood L, Price ND, Sadovsky Y. Commun Biol8, 1239 (2025). https://www.nature.com/articles/s42003-025-08631-6
Xu W, Pakhomov S, Heagerty P, Horvitz E, Bradley ER, Woolley J, Campbell A, Cohen A, Ben-Zeev D, Cohen T. Perplexity and proximity: Large language model perplexity complements semantic distance metrics for the detection of incoherent speech. Journal of Biomedical Informatics. 2025 Aug 21:104899. https://www.sciencedirect.com/science/article/pii/S1532046425001285
Wang, L. C., Pike, K. C., Conway, M., & Chen, A. T.(accepted). Identifying stigma phenotypes in social media narratives of substance use: An observational study. Journal of Medical Internet Research.
Chen, A. T.,Wang, L. C., Pike, K. C., Conway, M., & Glass, J. E. (accepted). Comparing the use experiences, contextual factors, and recovery strategies associated with different substances: An analysis of social media narratives. Substance Use & Misuse. DOI: 10.1080/10826084.2025.2540938
Liu, J., Bessler, S., Zhang, Y., Komi, M. M., & Chen, A. T.(2025). Changes of information needs and emotions during COVID-19: A longitudinal view. Library & Information Science Research, 47(3), 101367.
Chen, A. T.*, Dunn, L. H.*, Fan, W.,& Agrawal, N. (2025). Audience responses to online public shaming during COVID-19: A mixed-methods study. Journal of Medical Internet Research, 27. DOI: 10.2196/67923.

UPCOMING EXAMS
Title: NPP: tissue-anchored, GIS-inspired spatial modeling of tau neuropathology
Student: Raghav Madan
Date/Time: Wednesday, September 10^th, 2025, 12pm PT
In-person location: SLU, BLDG C, C122
Zoom: https://washington.zoom.us/my/jhgennari?pwd=TUx0clkwKzdnS1ZQV1dXRnZqMWMzZz09

August 18, 2025 – August 22, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025!

ANNOUNCEMENTS
Please join us in congratulating Serena Jinchen Xie who successfully passed her PhD Defense!
Title: Cultural Adaptation and Evaluation of AI Mental Health Support Conversational Agents

Abstract: Mental health disparities disproportionately affect underserved caregiver populations, in part due to limited availability of culturally responsive interventions. While large language model (LLM)-driven conversational agents offer promise for scalable mental health support, their outputs often suffer from cultural misalignment, limiting engagement among diverse populations. This dissertation develops and evaluates a generalizable, low-resource workflow for dynamic cultural adaptation of LLM-based mental health agents. Grounded in formative qualitative work with Chinese American and Latino American family caregivers and community stakeholders, I developed a cultural context database capturing salient caregiving challenges. Two adaptation strategies were implemented: (1) prompt-based “cultural prompting” and (2) a retrieval-augmented generation (RAG) workflow that dynamically integrates relevant cultural context during real-time interactions. Controlled evaluations showed the RAG-based approach outperformed both prompt-based and non-adapted agents on cultural responsiveness, perceived empathy, and therapeutic alliance. A randomized pilot study with Chinese American caregivers demonstrated improvements in short-term emotional well-being. This work advances scalable, culturally responsive AI agents for equitable mental health support and offers a generalizable workflow for adaptation across diverse populations and care contexts.

August 4, 2025 – August 8, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025!

UPCOMING EXAMS
Title: Cultural Adaptation and Evaluation of LLM-Driven Mental Health Conversational Agents
Student: Serena Xie
Date/Time: Monday, August 18^th, 2025, 11am PT
In-person location: Health Science Building (HST) T473
Zoom: https://washington.zoom.us/my/cohenta

July 28, 2025 – August 1, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025!

ANNOUNCEMENTS
Internship – Real World Evidence (RWE) Team
Location: Remote or Hybrid (based on applicant location)
Duration: 3–6 months
Compensation: Paid Internship
Start Date: Flexible (Summer/Fall 2025 preferred)

Position Summary:

The Natera RWE team is seeking a highly motivated and analytical intern to contribute to real-world data initiatives involving large-scale clinical and genomic datasets. The ideal candidate will have hands-on experience with clinical coding systems (ICD-10, CPT, NDC), a keen interest in advanced analytics using AI/LLMs, and exposure to digital pathology and multimodal biomedical data.

This internship provides a unique opportunity to work at the intersection of clinical informatics, genomics, and machine learning, supporting projects that drive impactful healthcare insights.

For Full Details and How to Apply contact rigreen@natera.com

PAPERS, PUBLICATIONS & PRESENTATIONS

S. Zeng, L. Liu, J. Wen, M. Yetisgen, R. Etzioni, and G. Luo. TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction. Proc. 2025 Machine Learning for Healthcare Conference, Rochester, MN, Aug. 2025.

July 21, 2025 – July 25, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025

ANNOUNCEMENTS
Please join us in congratulating Kevin Chen who successfully passed his PhD General Exam!
Title: Precision Prognostication in Post-Cardiac Arrest Brain Injury using Deep Learning

Abstract: Neurological injury is a primary determinant of mortality and long-term disability in cardiac arrest survivors, yet current prognostic tools fail to capture the dynamic complexity of recovery. This proposal aims to develop a data-driven framework that combines deep learning with structural neuroscience to decode hypoxic-ischemic brain injury. At its core, the proposal has three transformative aims: the novel application of autoencoder neural networks to uncover latent injury patterns from neuroimaging that may elude conventional radiological assessment, the identification of clinically distinct patient subgroups through unsupervised clustering of these injury patterns potentially revealing recovery trajectories, and the integration of multimodal data identifying neural hubs that can govern the recovery of consciousness. By moving beyond traditional one-dimensional prognostication, this approach characterizes the spatial heterogeneity of brain injury and also generates clinically actionable insights through patient stratification. The framework’s ability to pinpoint vulnerable brain regions enables targeted monitoring and early intervention that may lead to improved neurological outcomes.

PAPERS, PUBLICATIONS & PRESENTATIONS

Wesley Surento had an abstracted accepted by conference workshop ISMRM Workshop on Breast MRI: Technological Advances & Clinical Applications (https://www.ismrm.org/workshops/2025/BreastMRI/). It will be on September 13-15, 2025 in Vegas.
Zhaoyi Sun, Wen-Wai Yim, Özlem Uzuner, Fei Xia, Meliha Yetisgen, A scoping review of natural language processing in addressing medically inaccurate information: Errors, misinformation, and hallucination, Journal of Biomedical Informatics, 2025, 104866, https://doi.org/10.1016/j.jbi.2025.104866.

July 14, 2025 – July 18, 2025

UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in autumn quarter – 9/25/2025!

ANNOUNCEMENTS
Recent BIME graduate Yue Guo was selected as a finalist for the Edward H. Shortliffe doctoral dissertation award: https://amia.org/about-amia/amia-awards/signature-awards/edward-h-shortliffe-doctoral-dissertation-award

PAPERS, PUBLICATIONS & PRESENTATIONS

Fecho K, Glusman G, Baranzini SE, Bizon C, Brush M, Byrd W, Chung L, Crouse A, Deutsch E, Dumontier M, Foksinska A, Hadlock J, He K, Huang S, Hubal R, Hyde GM, Israni S, Kenmogne K, Koslicki D, Marcette JD, Mathe EA, Mesbah A, Moxon SAT, Mungall CJ, Osborne J, Pasfield C, Qin G, Ramsey SA, Reese J, Roach JC, Rose R, Soman K, Su AI, Ta C, Vaidya G, Weber R, Wei Q, Williams M, Wu C, Xu C, Yakaboski C; Biomedical Data Translator Consortium. Announcing the Biomedical Data Translator: Initial Public Release. Clin Transl Sci. 2025.

UPCOMING EXAMS
Title: Precision Prognostication in Post-Cardiac Arrest Brain Injury using Deep Learning
Student: Kevin Chen
Date/Time: Monday, July 21, 2025, 9am – 11am PT
In-person location: 850 Republican Street, Building C, SLU C123A
Zoom: https://washington.zoom.us/j/91423524935

News and Events

Chair’s Message

Biomedical Informatics and Medical Education Newsletter

September 29, 2025 – October 3, 2025

September 22, 2025 – September 26, 2025

September 15, 2025 – September 19, 2025

September 8, 2025 – September 12, 2025

September 1, 2025 – September 5, 2025

August 25, 2025 – August 29, 2025

August 18, 2025 – August 22, 2025

August 4, 2025 – August 8, 2025

July 28, 2025 – August 1, 2025

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