News and Events
Chair’s Message
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 added a specialization in Data Science. We are completing a curriculum revision for our on line applied clinical informatics MS. The work of our fellows in the clinical informatics fellowship program has received plaudits from clinical administrators and faculty. We are at 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
New Global Rankings for UW
In the summer of 2026, the University of Washington was recognized by U.S. News & World Report as one of the best universities in the world.
The University of Washington Welcomes New Chief Data Officer for UW Medicine
The University of Washington is delighted to announce that Yuan Luo, PhD, FACMI, FAIMBE, FAMIA, FIAHSI, will be joining the University of Washington as a Professor in the Department of Biomedical Informatics and Medical Education (BIME). In addition to being a core BIME faculty member, he will serve as Chief Data Officer for UW Medicine and Associate Vice President for Data, Analytics and AI Integration for UW Medicine, with a focus on clinical transformation reporting to Alexander Chiu, MD, Executive Vice Dean and Senior Vice President for Medical Affairs.
“I am honored and excited to join the University of Washington, BIME and UW Medicine at a time when data, analytics, and AI are becoming central to the future of health care, research, education, and operational transformation,” says Dr. Luo. “UW has extraordinary strengths across medicine, biomedical informatics, computer science, population health, and translational research. I look forward to working with colleagues across the enterprise to build practical, responsible, and high-impact data and AI capabilities that advance UW Medicine’s mission.”
Dr. Luo is currently a Professor in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine, Chief AI Officer for the Northwestern University Clinical and Translational Sciences Institute and the Institute for AI in Medicine, and Founding Director of the Center for Collaborative AI in Healthcare. He is a nationally recognized leader in healthcare AI, biomedical informatics, and clinical and translational data science. He has served as Co-Chair of the Standards Working Group on the PCORI Methodology Committee, a member of the National Quality Forum’s AI in Quality Measures Technical Expert Panel, and a member of the Board of Directors of the American Medical Informatics Association.
During his time at Northwestern, Dr. Luo has led major NIH-funded research programs, cross-institutional collaborations, as well as data and AI governance and strategy efforts. His work has advanced collaborative infrastructure and programs including the CRITICAL consortium, the SOAR platform, the Healthcare AI Forum, and the AI4H Clinics. He has also mentored faculty, trainees, and research teams while contributing to national leadership in biomedical informatics and healthcare AI.
Dr. Tarczy-Hornoch, Chair of BIME and outgoing Chief Data Officer for UW Medicine says, “We are delighted to have Dr. Luo join UW bringing deep expertise in biomedical informatics, data science and AI. He will further extend the breadth and depth of the expertise of the current faculty in BIME in biomedical informatics, computing, data science and AI. This is particularly critical today with a key objective of the UW Strategic Framework being UW and UW Medicine lead in the responsible development and use of big data, AI and other emerging technologies to advance next-generation healthcare. Dr. Luo in his CDO and AVP roles will join a collaboration of faculty and leaders focused on this objective across UW, UW Medicine, BIME, the Institute for Medical Data Science, the Institute for Translational Health Sciences, and UW Medicine Information Technology Services.”
“Dr. Luo’s appointment comes at an important moment for UW Medicine as we accelerate the responsible use of data, analytics, and AI to improve care delivery, support discovery, and strengthen our operations,” says Eric Neil, Chief Information Officer for UW Medicine. “His leadership will advance us on our journey to turn data into meaningful improvements for patients, clinicians, researchers, and the communities we serve.”
Alexander Chiu, MD, Executive Vice Dean and Senior Vice President for Medical Affairs adds, “Dr. Luo’s appointment as Associate Vice President for Data, Analytics and AI Integration represents a pivotal step forward for UW Medicine. His deep expertise in data science, clinical informatics, and AI strategy will drive us to modernize how we structure, govern, and activate our data—creating a more unified, accessible, and high-impact enterprise data foundation that strengthens our readiness for AI. This work will accelerate our ability to deploy AI at scale, unlocking capabilities that enable clinical transformation, and support operational excellence across UW Medicine’s broader business functions.”
Dr. Luo’s position begins effective July 16, 2026.
Biomedical Informatics and Medical Education Newsletter
August 3, 2026 – August 7, 2026
UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in fall quarter – 10/1/2026!
_________________________________________
September 2026 UW Medical AI & Data Science Journal Club
Monday, September 21, 2026: 1:00pm Pacific Time
Presenter Faiz Moazzam will discuss the paper: Development and validation of a deep learning model to predict visual and anatomical prognosis of anti-VEGF therapy for neovascular age-related macular degeneration (KongMing Study): a prospective, nationwide, multicentre study
Join us in person: F107, 750 Republican St, Seattle 98109
-or-
via Zoom: https://washington.zoom.us/j/92158637394?pwd=pi87aK9LVz5Jx7KTPgVq0SX7d2xNIL.1
Meeting ID: 921 5863 7394
Passcode: 424586
Bio: Faiz Moazzam is an incoming second-year student. He joined the Computational Ophthalmology Lab in October 2025 and presented his work earlier this year at ARVO 2026. Faiz is currently finalizing his first manuscript and recently participated in a summer fellowship in biomedical machine learning. Faiz is excited to explore the connections between ophthalmology and retinal biomarkers for Alzheimer’s/dementia, and especially how it connects to machine learning. He is looking for new opportunities to learn and grow as a student and engineer and is excited to connect and collaborate. https://www.linkedin.com/in/faiz-moazzam/
_________________________________________
The UW Medical AI & Data Science Journal Club is led by Acting Assistant Professor, Yue Wu, PhD, , UW Medicine Computational Ophthalmology Lab. Our journal club is open to all who are interested, providing an opportunity to exchange ideas, ask questions, and critique scientific methods related to artificial intelligence and big data that support our collective goal of creating better health.
We generally meet on 2nd Mondays, 1-2pm Pacific Time in person and via zoom (exception: 3rd Monday in September 2026).
At each meeting, the presenter provides an overview of a paper they selected, providing their thoughts and interpretation, and then the presentation is followed by questions and discussion among participants.
We are seeking additional presenters for 2026-2027. If you are interested in presenting, or would like to be added to our mailing list, please contact Emily Heindsmann.
ANNOUNCEMENTS
Please see below for a couple of job postings from Washington State Department of Health. These recruitments are open to Washington residents and those residing on the ID/WA and OR/WA borders.
1
Public Health Data Scientist Informatics Specialist (DSIS 1) DOH8960
Workforce Pathways Program (WFP) Executive Office for Government and Community Affairs, Office of the State Health Officer (OSHO)
Center for Public Health Informatics, Washington State, Department of HEALTH
Closing: August 12, 2026 (11:59pm Pacific)
2
Data Scientist, Public Health Data Linkage (DSIS 3) DOH8949
Data Scientist, Public Health Data Linkage (DSIS 3) The Opportunity As a Data Scientist you will work within the Linkage and Integrated Data Analysis (LIDA) Unit within the Center for Health Statistics (CHS)
Closing: August 9, 2026 11:59 PM Pacific
Washington State Department of Health At a Glance
_________________________________________
On June 3rd, the Institute for Medical Data Science (IMDS) held its 3rd annual IMDS Symposium at UW’s Center for Urban Horticulture. The keynote speaker was Jeff Leek, Vice President and CDO at Fred Hutch Cancer Center. Also, Andrew Connolly, Director of the eScience Institute, gave a presentation on UW’s deployment of data science and AI across campus. Additionally, there were presentations by previous IMDS Pilot Award recipients, as well as by key selected researchers from among the more than twenty poster presentations. To wrap up the day, IMDS Director and UW CRIO Shawn Murphy presented future directions for IMDS, including its focus on development of AI-based digital twins for patient representation.
The event was well-attended and sparked lively discussion, both following talks and presentations, as well as among attendees enjoying breaks and refreshments under the shaded early summer sunlight in the Center’s lovely, botanic courtyards. You can access recordings of the talks via the IMDS 2026 Symposium page. Keep an eye out in early 2027 for information regarding the next installment of the IMDS Symposium.
UPCOMING EXAMS
Final Exam
Title: Quantitative MR Imaging Markers for Breast Cancer Risk Prediction
Student: Wesley Surento
Date/Time: Tuesday, August 11, 10-12pm PT
In-Person Location: Fred Hutch Yale Building
823 Yale Ave N, Seattle, WA 98109, Room J6-102 (6th floor)
Zoom: : https://washington.zoom.us/my/jhgennari?pwd=TUx0clkwKzdnS1ZQV1dXRnZqMWMzZz09
Abstract: Breast cancer risk assessment can help early prediction and intervention planning, lower mortality, and improve care outcomes. Many current tools utilize risk factors such as age, menopausal status, personal biopsy history, and family history of breast cancer. Although these characteristics do a reasonable job at capturing risk, they omit all information from imaging studies such as mammograms or MRIs. Even when negative for disease, analysis of these images could provide a number of markers that might also capture risk. There remains much unexplored potential in leveraging imaging markers as part of risk assessment models for prevention and early prediction.
In this work, we aim to develop and assess a new risk prediction model that incorporates MRI-derived features along with clinical risk factors.
In the first step, I collected relevant risk factors for predicting cancer within 5 years from the MRI for a cohort of high-risk patients. I built a REDcap data repository to store their clinical risk factors obtained from electronic health records, such as select demographic information, menopausal status, BRCA mutation, and family history of breast cancer.
In the second step, I identified predictive quantitative breast MRI markers. I extracted quantitative markers of background parenchymal enhancement using an image processing pipeline which I helped develop, and proceeded to assess their ability to predict 5-year cancer risk.
In the third step, I performed multimodal combination of imaging markers and clinical risk factors to predict 5-year cancer. We also explored the performance of these combinations for several cohort subsets. Our findings showed that multimodal combination of imaging markers can improve the predictive performance of a conventional risk assessment tool.
COMMUNITY BUILDING
Biomedical Trainee Empowered Wellness Circle (Virtual)
Empowered Wellness Circle, a time for biomedical trainees to focus on health and wellbeing with each other and a local counselor. All biomedical postdocs, grad students, and postbacs in Fred Hutch, University of Washington, and Seattle Children’s labs/groups are welcome – and no sign-up necessary. The group meets every fourth Wednesday of the month.
Next meeting August 26 @ 3:00 pm – 4:30 pm
Event Link: Biomedical Trainee Empowered Wellness Circle
_________________________________________
Graduate Student Research Institute
September 14-18, 2026, Virtual
Join the UW Libraries this summer for the eighth annual Graduate Student Research Institute (GSRI)! The Graduate Student Research Institute (GSRI) is a free and asynchronous multi-day online workshop offered by the UW Libraries with the goal of motivating new and returning UW graduate students to explore tools and strategies to research smarter, not harder.
GSRI can help you to:
Learn skills and strategies for effective academic research
Become familiar with core tools and resources for research productivity
Connect with relevant support units across the UW campuses
Build community with other UW students and campus support staff
Students receive five days of online guidance and support from a team of Libraries volunteers as they work through key content and activities from the openly available Graduate Student Research Institute site. There are no required meeting times and learning can take place anytime within the span of the workshop session.
Additional benefits for registered students include access to:
Daily tips and resources for research, using the Libraries, and being a graduate student at UW
Optional synchronous live events and programming
All incoming or current UW graduate students are welcome to register for GSRI.
For questions, email: uwlibidteam@uw.edu.
July 27, 2026 – July 31, 2026
UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in fall quarter – 10/1/2026!
_________________________________________
September 2026 UW Medical AI & Data Science Journal Club
Monday, September 21, 2026: 1:00pm Pacific Time
Presenter Faiz Moazzam will discuss the paper: Development and validation of a deep learning model to predict visual and anatomical prognosis of anti-VEGF therapy for neovascular age-related macular degeneration (KongMing Study): a prospective, nationwide, multicentre study
Join us in person: F107, 750 Republican St, Seattle 98109
-or-
via Zoom: https://washington.zoom.us/j/92158637394?pwd=pi87aK9LVz5Jx7KTPgVq0SX7d2xNIL.1
Meeting ID: 921 5863 7394
Passcode: 424586
Bio: Faiz Moazzam is an incoming second-year student. He joined the Computational Ophthalmology Lab in October 2025 and presented his work earlier this year at ARVO 2026. Faiz is currently finalizing his first manuscript and recently participated in a summer fellowship in biomedical machine learning. Faiz is excited to explore the connections between ophthalmology and retinal biomarkers for Alzheimer’s/dementia, and especially how it connects to machine learning. He is looking for new opportunities to learn and grow as a student and engineer and is excited to connect and collaborate. https://www.linkedin.com/in/faiz-moazzam/
_________________________________________
The UW Medical AI & Data Science Journal Club is led by Acting Assistant Professor, Yue Wu, PhD, , UW Medicine Computational Ophthalmology Lab. Our journal club is open to all who are interested, providing an opportunity to exchange ideas, ask questions, and critique scientific methods related to artificial intelligence and big data that support our collective goal of creating better health.
We generally meet on 2nd Mondays, 1-2pm Pacific Time in person and via zoom (exception: 3rd Monday in September 2026).
At each meeting, the presenter provides an overview of a paper they selected, providing their thoughts and interpretation, and then the presentation is followed by questions and discussion among participants.
We are seeking additional presenters for 2026-2027. If you are interested in presenting, or would like to be added to our mailing list, please contact Emily Heindsmann.
ANNOUNCEMENTS
Washington Health Summary (WAHS) won a Phase 1 Award in the Office of the National Coordinator for Health IT-sponsored EHIgnite Challenge. The award provides a small amount of prize money and a chance to compete in Phase 2. https://healthit.gov/blog/interoperability/nine-teams-one-mission-meet-the-ehignite-phase-1-winners/
WAHS is an app that supports patient-controlled integration and sharing of health records using standard such as FHIR for native data representation, the US Core FHIR API required by the federal 21st Century Cures Act, Blue Button and other Insurance industry standards for patient facing access, Occupational Data for Health, Advance Directives, and SMART Health Links for secure sharing of verified health data. WAHS is a joint initiative of the UW Clinical Informatics Research Group, the UW Digital Initiatives Group, and the Washington State Department of Health.
https://myhealthsummary.demo.cirg.uw.edu/. Contact Bill Lober or Jan Flowers.
_________________________________________
Please join us in congratulating Dr. Faisal Yaseen who successfully passed his final dissertation defense!
Title: Uncertainty-Aware Multimodal and Multiscale Treatment Response Prediction in Advanced Non-Small Cell Lung Cancer
Abstract: Managing patients with metastatic non-small cell lung cancer (mNSCLC) remains challenging due to highly variable responses to standard of care chemoimmunotherapy, with many patients experiencing toxicity and limited clinical benefit. These variable responses are associated with spatially complex heterogeneity that manifests across patients, between organs, and within tumors on medical imaging. Despite its widespread use to inform treatment decisions, programmed death ligand 1 (PD-L1) expression provides limited predictive value and is sensitive to sampling variability due to tumor heterogeneity. Furthermore, conventional response assessment by the Response Evaluation Criteria in Solid Tumors (RECIST) is based on changes in tumor size and does not capture functional or spatial variation within lesions, limiting its ability to guide treatment selection, adaptation, and radiotherapy planning. Current clinical decision-making is also primarily based on point predictions that do not quantify uncertainty, reducing their reliability in high stakes clinical settings. This dissertation addresses these limitations through a progression from biomarker discovery to an uncertainty aware, multimodal, and multiscale framework of informatics methods for treatment response prediction in advanced NSCLC.
The work is structured around three distinct but complementary research objectives that collectively address these limitations. The dissertation first identifies fluorodeoxyglucose positron emission tomography (FDG-PET) imaging and circulating immune biomarkers, including T cell receptor and cytokine metrics, that are associated with treatment response and long-term outcomes in metastatic NSCLC, benchmarked against PD-L1. It then integrates these biomarkers into a multimodal framework that couples response prediction with conformal prediction to quantify patient-specific uncertainty, and demonstrates translational potential through a web-based clinical decision support prototype. To model spatial heterogeneity, it identifies a robust variogram that characterizes tumor spatial correlation across disease stages and treatment regimens. Building on this spatial foundation, it develops a multiscale framework for voxel-level response prediction across primary and metastatic lesions, and introduces a residual-variance conformal method that restores valid uncertainty under spatial dependence.
Across these contributions, a central informatics theme is that predictions become clinically useful only when their reliability is explicitly quantified. By embedding uncertainty quantification at every scale, from patient- to voxel-level, this dissertation moves beyond prediction sets and intervals toward trustworthy, clinically actionable outputs. Although developed and evaluated in advanced NSCLC, the resulting informatics methods are generalizable and can be adapted to other solid tumors and broader biomedical informatics domains.
_________________________________________
Please join us in congratulating Xiaoyi Zhang on successfully defending her doctoral dissertation!
Her dissertation, entitled “Advancing Population Health Management with Artificial Intelligence: Prediction, Interpretation and Outcome Measurement in Real-World Health Care Systems”, addressed critical gaps in the path from AI model development to practical utility, through development of clinically meaningful performance metrics; harmonization of data from outside a healthcare system for more accurate assessment of model performance; prioritization of actionable automated explanatory rules to bridge the gap from model decision to clinical action; assessment of the extent to which deep learning models can obviate the need for extensive feature engineering; and improvement of the granularity of outcome measurement. Xiaoyi gave a clear presentation of her extensive body of work in these areas, and how it advances healthcare AI from a focus on validation set accuracy toward clinical utility. She displayed her command of this work and knowledge of the field in the lively discussion session that followed.
_________________________________________
On June 3rd, the Institute for Medical Data Science (IMDS) held its 3rd annual IMDS Symposium at UW’s Center for Urban Horticulture. The keynote speaker was Jeff Leek, Vice President and CDO at Fred Hutch Cancer Center. Also, Andrew Connolly, Director of the eScience Institute, gave a presentation on UW’s deployment of data science and AI across campus. Additionally, there were presentations by previous IMDS Pilot Award recipients, as well as by key selected researchers from among the more than twenty poster presentations. To wrap up the day, IMDS Director and UW CRIO Shawn Murphy presented future directions for IMDS, including its focus on development of AI-based digital twins for patient representation.
The event was well-attended and sparked lively discussion, both following talks and presentations, as well as among attendees enjoying breaks and refreshments under the shaded early summer sunlight in the Center’s lovely, botanic courtyards. You can access recordings of the talks via the IMDS 2026 Symposium page. Keep an eye out in early 2027 for information regarding the next installment of the IMDS Symposium.
UPCOMING EXAMS
Final Exam
Title: Quantitative MR Imaging Markers for Breast Cancer Risk Prediction
Student: Wesley Surento
Date/Time: Tuesday, August 11, 10-12pm PT
In-Person Location: Fred Hutch Yale Building
823 Yale Ave N, Seattle, WA 98109, Room J6-102 (6th floor)
Zoom: : https://washington.zoom.us/my/jhgennari?pwd=TUx0clkwKzdnS1ZQV1dXRnZqMWMzZz09
Abstract: Breast cancer risk assessment can help early prediction and intervention planning, lower mortality, and improve care outcomes. Many current tools utilize risk factors such as age, menopausal status, personal biopsy history, and family history of breast cancer. Although these characteristics do a reasonable job at capturing risk, they omit all information from imaging studies such as mammograms or MRIs. Even when negative for disease, analysis of these images could provide a number of markers that might also capture risk. There remains much unexplored potential in leveraging imaging markers as part of risk assessment models for prevention and early prediction.
In this work, we aim to develop and assess a new risk prediction model that incorporates MRI-derived features along with clinical risk factors.
In the first step, I collected relevant risk factors for predicting cancer within 5 years from the MRI for a cohort of high-risk patients. I built a REDcap data repository to store their clinical risk factors obtained from electronic health records, such as select demographic information, menopausal status, BRCA mutation, and family history of breast cancer.
In the second step, I identified predictive quantitative breast MRI markers. I extracted quantitative markers of background parenchymal enhancement using an image processing pipeline which I helped develop, and proceeded to assess their ability to predict 5-year cancer risk.
In the third step, I performed multimodal combination of imaging markers and clinical risk factors to predict 5-year cancer. We also explored the performance of these combinations for several cohort subsets. Our findings showed that multimodal combination of imaging markers can improve the predictive performance of a conventional risk assessment tool.
COMMUNITY BUILDING
Graduate Student Research Institute
September 14-18, 2026, Virtual
Join the UW Libraries this summer for the eighth annual Graduate Student Research Institute (GSRI)! The Graduate Student Research Institute (GSRI) is a free and asynchronous multi-day online workshop offered by the UW Libraries with the goal of motivating new and returning UW graduate students to explore tools and strategies to research smarter, not harder.
GSRI can help you to:
Learn skills and strategies for effective academic research
Become familiar with core tools and resources for research productivity
Connect with relevant support units across the UW campuses
Build community with other UW students and campus support staff
Students receive five days of online guidance and support from a team of Libraries volunteers as they work through key content and activities from the openly available Graduate Student Research Institute site. There are no required meeting times and learning can take place anytime within the span of the workshop session.
Additional benefits for registered students include access to:
Daily tips and resources for research, using the Libraries, and being a graduate student at UW
Optional synchronous live events and programming
All incoming or current UW graduate students are welcome to register for GSRI.
For questions, email: uwlibidteam@uw.edu.
July 20, 2026 – July 24, 2026
UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in fall quarter – 10/1/2026!
_________________________________________
PAPERS, PUBLICATIONS & PRESENTATIONS
- Zhang, C. Wilson, H. Eyre, D. Reed, G. Luo, and S.B. Zeliadt. Extracting Pain Severity and Functional Interference from Clinical Narratives Using Domain-Informed Large Language Models: Study Protocol. JMIR Research Protocols, 2026.
- D’Amore JD, Vallapu ER, Samal L, Karras BT, Lober WB. From Pandemic Response to Kill the Clipboard: Patient-Controlled Sharing of Health Data Using International Patient Summary (IPS) and QR codes.Appl Clin Inform. 2026 May;17(3):559-567. doi: 10.1055/a-2902-8515. Epub 2026 Jun 29. PMID: 42372787; PMCID: PMC13354518
https://pubmed.ncbi.nlm.nih.gov/42372787/
_________________________________________
UPCOMING EXAMS
Final Exam
Title: Uncertainty-Aware Multimodal and Multiscale Treatment Response Prediction in Advanced Non-Small Cell Lung Cancer
Student: Faisal Yaseen
Date/Time: Tuesday, July 28, 10-12pm PT
In-Person Location: SLU C122
Zoom: : https://washington.zoom.us/my/jhgennari?pwd=TUx0clkwKzdnS1ZQV1dXRnZqMWMzZz09
Abstract: Managing patients with metastatic non-small cell lung cancer (mNSCLC) remains challenging due to highly variable responses to standard of care chemoimmunotherapy, with many patients experiencing toxicity and limited clinical benefit. These variable responses are associated with spatially complex heterogeneity that manifests across patients, between organs, and within tumors on medical imaging. Despite its widespread use to inform treatment decisions, programmed death ligand 1 (PD-L1) expression provides limited predictive value and is sensitive to sampling variability due to tumor heterogeneity. Furthermore, conventional response assessment by the Response Evaluation Criteria in Solid Tumors (RECIST) is based on changes in tumor size and does not capture functional or spatial variation within lesions, limiting its ability to guide treatment selection, adaptation, and radiotherapy planning. Current clinical decision-making is also primarily based on point predictions that do not quantify uncertainty, reducing their reliability in high stakes clinical settings. This dissertation addresses these limitations through a progression from biomarker discovery to an uncertainty aware, multimodal, and multiscale framework of informatics methods for treatment response prediction in advanced NSCLC.
The work is structured around three distinct but complementary research objectives that collectively address these limitations. The dissertation first identifies fluorodeoxyglucose positron emission tomography (FDG-PET) imaging and circulating immune biomarkers, including T cell receptor and cytokine metrics, that are associated with treatment response and long-term outcomes in metastatic NSCLC, benchmarked against PD-L1. It then integrates these biomarkers into a multimodal framework that couples response prediction with conformal prediction to quantify patient-specific uncertainty, and demonstrates translational potential through a web-based clinical decision support prototype. To model spatial heterogeneity, it identifies a robust variogram that characterizes tumor spatial correlation across disease stages and treatment regimens. Building on this spatial foundation, it develops a multiscale framework for voxel-level response prediction across primary and metastatic lesions, and introduces a residual-variance conformal method that restores valid uncertainty under spatial dependence.
Across these contributions, a central informatics theme is that predictions become clinically useful only when their reliability is explicitly quantified. By embedding uncertainty quantification at every scale, from patient- to voxel-level, this dissertation moves beyond prediction sets and intervals toward trustworthy, clinically actionable outputs. Although developed and evaluated in advanced NSCLC, the resulting informatics methods are generalizable and can be adapted to other solid tumors and broader biomedical informatics domains.
_________________________________________
COMMUNITY BUILDING
Discover UW Medicine Summer Markets
Celebrate the sunshine and support local creators at the annual UW Medicine Summer Markets! Hosted by the Whole U, local vendors will be rotating around hospital campuses throughout July and August.
Market hours are 10:00 AM – 2:00 PM and Market Locations:
Thursday, July 30 – Harborview Medical Center
Tuesday, August 18 – UWMC – Northwest
Tuesday, August 25 – UWMC – Montlake
This seasonal event series will rotate across our campuses, providing employees an excellent midday destination to explore an array of items, including:
- Handcrafted jewelry and accessories
- Photography, art prints and stationery
- Candles, soaps and home goods
- Apparel and specialty items
- Local treats and food options
LEARN MORE
Subscribe to the OHCE Monthly Newsletter Here!
July 13, 2026 – July 17, 2026
UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in fall quarter – 10/1/2026!
_________________________________________
COMMUNITY BUILDING
Discover UW Medicine Summer Markets
Celebrate the sunshine and support local creators at the annual UW Medicine Summer Markets! Hosted by the Whole U, local vendors will be rotating around hospital campuses throughout July and August.
Market hours are 10:00 AM – 2:00 PM and Market Locations:
Thursday, July 30 – Harborview Medical Center
Tuesday, August 18 – UWMC – Northwest
Tuesday, August 25 – UWMC – Montlake
This seasonal event series will rotate across our campuses, providing employees an excellent midday destination to explore an array of items, including:
- Handcrafted jewelry and accessories
- Photography, art prints and stationery
- Candles, soaps and home goods
- Apparel and specialty items
- Local treats and food options
LEARN MORE
Subscribe to the OHCE Monthly Newsletter Here!
_________________________________________
Biomedical Trainee Empowered Wellness Circle (Virtual), Cancer Consortium
Empowered Wellness Circle, a time for biomedical trainees to focus on health and wellbeing with each other and a local counselor. All biomedical postdocs, grad students, and postbacs in Fred Hutch, University of Washington, and Seattle Children’s labs/groups are welcome – and no sign-up necessary. The group meets every fourth Wednesday of the month.
Next meeting July 22 @ 3:00 pm – 4:30 pm
Event Link: Biomedical Trainee Empowered Wellness Circle
June 29, 2026 – July 3, 2026
UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in fall quarter – 10/1/2026!
_________________________________________
ANNOUNCEMENTS
Please join us in congratulating Cat Kim who successfully passed her Masters Thesis Defense!
Title: Geocoding Pipeline Development and Data Quality Assessment For Enhancing Precision Medicine Research
Abstract: Geographic location shapes health outcomes through environmental exposures, socioeconomic conditions, and access to care. However, the quality of geocoded address data to facilitate these inferences remains poorly characterized to understand the estimation error and performance nationwide. This thesis presents a geocoding benchmarking study evaluating the DeGAUSS geocoding framework across a curated reference dataset of over 270,000 public locations spanning U.S. states and territories. A sensitivity analysis across five match score thresholds demonstrates that relaxing quality criteria increases coverage while producing increases in median positional error nationally. Geographic stratification reveals performance variation across regions, including higher error rates in U.S. territories that should be investigated further given the limited sample sizes. A principled spatial outlier removal method based on state boundary validation distinguishes geocoder misclassification from reference data error. Together, these findings suggest that geocoding quality standards may need to incorporate geographic context to support accurate residential linkage in integrative precision medicine research.
_________________________________________
Philips Ultrasound Shanghai, is hiring Acoustic Engineer/Internship. Philips Ultrasound Shanghai, is a member of Philips Healthcare Ultrasound, is a leader in design, development, and manufacture of medical ultrasound transducers for a variety of applications for more than 15 years. The company offers a rich family of high quality and high performing transducers to medical ultrasound customers. This position is in Philips Ultrasound Shanghai’s R&D Department, reporting to transducer R&D Director. As an R&D team member, this position will contribute to the company’s core competency for acoustic design of Philips Ultrasound Shanghai transducers with high quality and high efficiency, and meeting operation metrics on yield, defects, capacity, and delivery.
Candidates can apply by following the link:
https://philips.wd3.myworkdayjobs.com/jobs-and-careers/job/Shanghai/Acoustic-Engineer-Internship_586212
PAPERS, PUBLICATIONS & PRESENTATIONS
- Babitts, A., Chen, A. T., Ehde, D. M., Goode, A. P., Jarvik, J. G., Cizik, A. M., Meier, E. N., Friedly, J. L., Horn, M. E., Suri, P., Burke, C., Rundell, S. D. (accepted). Comparing low and high recovery expectations among those with lumbar spinal stenosis: A network analysis. Pain Medicine.DOI: 10.1093/pm/pnag059.
- Chen, A. T., Choi, B., Tveleneva, A., Wang, L. C., Kang, R. A., Conway, M., Wong, S. H. (accepted). Looking back: Exploring growth through retrospective views of substance use stigma-related experiences. Stigma & Health. DOI: 1037/sah0000691.
- Pollack, L. R., Downey, L., Engelberg, R. A., Sibley, J., Ko, L. K., Domoto-Reilly, K., Brumback, L. C., Chen, A. T., Sharma, R. K. (accepted). Language preference is associated with goals-of-care communication and end-of-life care in dementia. Journal of General Internal Medicine. DOI: 10.1007/s11606-026-10372-z.
- Poster:
Du, J., Chen, A. T., Cole, C. L., Zhou, J., Bui, J. (accepted). Designing for engagement: A user-centered approach to developing a historical digital collection. To be presented at DH 2026, July 27-31, 2026. Daejeon, South Korea.
COMMUNITY BUILDING
Biomedical Trainee Empowered Wellness Circle (Virtual), Cancer Consortium
Empowered Wellness Circle, a time for biomedical trainees to focus on health and wellbeing with each other and a local counselor. All biomedical postdocs, grad students, and postbacs in Fred Hutch, University of Washington, and Seattle Children’s labs/groups are welcome – and no sign-up necessary. The group meets every fourth Wednesday of the month.
Next meeting July 22 @ 3:00 pm – 4:30 pm
Event Link: Biomedical Trainee Empowered Wellness Circle
June 22, 2026 – June 26, 2026
UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in fall quarter – 10/1/2026!
_________________________________________
Institute for Systems Biology SEMINAR
MAJ Kathryn A. McGuckin, PhD
Deputy Chief, Department of Virology, Walter Reed Army Institute of Research,
Armed Forces Research Institute of Medical Sciences Bangkok, Thailand
Talk Title: Integrating Multi-modal Data Frameworks for Modernized Biosurveillance to Enhance Global Health Security
Thursday, July 2nd
11:00-12:00 pm | ISB 106 or via Zoom
Institute for Systems Biology | 401 Terry Ave N, Seattle, Washington 98109
For more information contact:
Thea Swanson | thea.swanson@isbscience.org | 206-732-1209
ANNOUNCEMENTS
From Jacob Edelson:
BIME’s very own, Jenni Logue will be performing at the World Cup with the sounders, so keep an eye out if you are watching the game tonight at 8pm PST.
She will be playing the cymbals with the Sounder’s Sound Waves at the half-time show of the Iran vs Egypt game.
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UPCOMING EXAMS
Master’s Defense
Title: Geocoding Pipeline Development and Data Quality Assessment For Enhancing Precision Medicine Research
Student: Cat Kim
Date/Time: Monday, June 30, 12pm PT
In-Person Location: South Lake Union, Room C122
Zoom: https://washington.zoom.us/j/93471587664
Abstract: Geographic location shapes health outcomes through environmental exposures, socioeconomic conditions, and access to care. However, the quality of geocoded address data to facilitate these inferences remains poorly characterized to understand the estimation error and performance nationwide. This thesis presents a geocoding benchmarking study evaluating the DeGAUSS geocoding framework across a curated reference dataset of over 270,000 public locations spanning U.S. states and territories. A sensitivity analysis across five match score thresholds demonstrates that relaxing quality criteria increases coverage while producing increases in median positional error nationally. Geographic stratification reveals performance variation across regions, including higher error rates in U.S. territories that should be investigated further given the limited sample sizes. A principled spatial outlier removal method based on state boundary validation distinguishes geocoder misclassification from reference data error. Together, these findings suggest that geocoding quality standards may need to incorporate geographic context to support accurate residential linkage in integrative precision medicine research.
June 15, 2026 – June 19, 2026
UPCOMING LECTURES AND SEMINARS
BIME 590 – See you in fall quarter – 10/1/2026!
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Institute for Systems Biology SEMINAR
MAJ Kathryn A. McGuckin, PhD
Deputy Chief, Department of Virology, Walter Reed Army Institute of Research,
Armed Forces Research Institute of Medical Sciences Bangkok, Thailand
Talk Title: Integrating Multi-modal Data Frameworks for Modernized Biosurveillance to Enhance Global Health Security
Thursday, July 2nd
11:00-12:00 pm | ISB 106 or via Zoom
Institute for Systems Biology | 401 Terry Ave N, Seattle, Washington 98109
For more information contact:
Thea Swanson | thea.swanson@isbscience.org | 206-732-1209
ANNOUNCEMENTS
The University of Washington Welcomes New Chief Data Officer for UW Medicine
The University of Washington is delighted to announce that Yuan Luo, PhD, FACMI, FAIMBE, FAMIA, FIAHSI, will be joining the University of Washington as a Professor in the Department of Biomedical Informatics and Medical Education (BIME). In addition to being a core BIME faculty member, he will serve as Chief Data Officer for UW Medicine and Associate Vice President for Data, Analytics and AI Integration for UW Medicine, with a focus on clinical transformation reporting to Alexander Chiu, MD, Executive Vice Dean and Senior Vice President for Medical Affairs.
“I am honored and excited to join the University of Washington, BIME and UW Medicine at a time when data, analytics, and AI are becoming central to the future of health care, research, education, and operational transformation,” says Dr. Luo. “UW has extraordinary strengths across medicine, biomedical informatics, computer science, population health, and translational research. I look forward to working with colleagues across the enterprise to build practical, responsible, and high-impact data and AI capabilities that advance UW Medicine’s mission.”
Dr. Luo is currently a Professor in the Department of Preventive Medicine at Northwestern University Feinberg School of Medicine, Chief AI Officer for the Northwestern University Clinical and Translational Sciences Institute and the Institute for AI in Medicine, and Founding Director of the Center for Collaborative AI in Healthcare. He is a nationally recognized leader in healthcare AI, biomedical informatics, and clinical and translational data science. He has served as Co-Chair of the Standards Working Group on the PCORI Methodology Committee, a member of the National Quality Forum’s AI in Quality Measures Technical Expert Panel, and a member of the Board of Directors of the American Medical Informatics Association.
During his time at Northwestern, Dr. Luo has led major NIH-funded research programs, cross-institutional collaborations, as well as data and AI governance and strategy efforts. His work has advanced collaborative infrastructure and programs including the CRITICAL consortium, the SOAR platform, the Healthcare AI Forum, and the AI4H Clinics. He has also mentored faculty, trainees, and research teams while contributing to national leadership in biomedical informatics and healthcare AI.
Dr. Tarczy-Hornoch, Chair of BIME and outgoing Chief Data Officer for UW Medicine says, “We are delighted to have Dr. Luo join UW bringing deep expertise in biomedical informatics, data science and AI. He will further extend the breadth and depth of the expertise of the current faculty in BIME in biomedical informatics, computing, data science and AI. This is particularly critical today with a key objective of the UW Strategic Framework being UW and UW Medicine lead in the responsible development and use of big data, AI and other emerging technologies to advance next-generation healthcare. Dr. Luo in his CDO and AVP roles will join a collaboration of faculty and leaders focused on this objective across UW, UW Medicine, BIME, the Institute for Medical Data Science, the Institute for Translational Health Sciences, and UW Medicine Information Technology Services.”
“Dr. Luo’s appointment comes at an important moment for UW Medicine as we accelerate the responsible use of data, analytics, and AI to improve care delivery, support discovery, and strengthen our operations,” says Eric Neil, Chief Information Officer for UW Medicine. “His leadership will advance us on our journey to turn data into meaningful improvements for patients, clinicians, researchers, and the communities we serve.”
Alexander Chiu, MD, Executive Vice Dean and Senior Vice President for Medical Affairs adds, “Dr. Luo’s appointment as Associate Vice President for Data, Analytics and AI Integration represents a pivotal step forward for UW Medicine. His deep expertise in data science, clinical informatics, and AI strategy will drive us to modernize how we structure, govern, and activate our data—creating a more unified, accessible, and high-impact enterprise data foundation that strengthens our readiness for AI. This work will accelerate our ability to deploy AI at scale, unlocking capabilities that enable clinical transformation, and support operational excellence across UW Medicine’s broader business functions.”
Dr. Luo’s position begins effective July 16, 2026.
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After an impressive 50 year career at the University of Washington, Professor Doug Schaad, PhD is retiring from the department of BIME in the Division of Medical Education at the end of June. We are pleased to announce that BIME faculty have voted in support for him to return as an Emeritus faculty member, a lifelong designation that recognizes his achievements and meritorious record, as of July 1, 2026. Please join us in acknowledging and thanking Doug for his years of service and many contributions to the Division of Medical Education.
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Walter H. Curioso, MD, MPH, PhD, FIAHSI (wcurioso@uw.edu), Affiliate Professor in the Department of Biomedical Informatics and Medical Education (BIME), University of Washington School of Medicine, has been selected as an invited speaker at Patient-Powered Digital Health 2026: Co-Designing Scalable Digital Health Solutions for a Trusted, Patient-First Future, an international conference hosted by Harvard Medical School and Beth Israel Deaconess Medical Center in Boston, Massachusetts, on June 22–24, 2026.
Dr. Curioso will present “AI-Enabled Socio-Technical System for Tuberculosis Diagnosis: Real-World Implementation and Patient-Centered Impact in Resource-Constrained Settings,” highlighting lessons learned from the implementation of an NIH-funded artificial intelligence–enabled tuberculosis diagnostic system in Peru and its implications for scalable, patient-centered AI in low- and middle-income countries.
Dr. Curioso is the only speaker from Peru and the only representative from Latin America selected to present in the conference’s peer-reviewed program, which includes experts from Harvard Medical School, Beth Israel Deaconess Medical Center, the U.S. Food and Drug Administration (FDA), Mass General Brigham, HL7 International, IEEE, and leading global digital health organizations.
Conference website:
https://www.dcinetwork.org/patients2026
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Larry, Jacob Edelson and Kari Stephens are going to give a talk to the UW Psychiatric Addiction Case Conference on “Chronic Pain – Is there an app for that and mental health co-morbidities?”
They would like to invite any who are interested to attend. They will be covering the work they’ve been doing within the EquiP PC study to develop dimensions of digital solutions that deliver clinical interventions to patients that could improve quality of life. They will also cover what apps they’ve been identifying and rating, and will engage the audience in questions to get their feedback to help hone our thinking.
It’s from 12-1:30pm PST this Thursday 6/18/26 and free for all to attend. Please register here if you plan to attend: https://redcap.iths.org/surveys/?s=DCHE4PL4LE.
Here’s the link to join on Thursday: https://zoom.us/j/713494945
PAPERS, PUBLICATIONS & PRESENTATIONS
- Title:Mobile health (mHealth) applications for community health workers in low- and middle-income countries: A scoping review
Authors: Chak Charoensilpchai, Zoljargal Lkhagvajav, and Anne M. Turner
DOI: https://doi.org/10.1016/j.ijmedinf.2026.106531
Free Access Link: https://authors.elsevier.com/a/1nE-j4xGJ-KIKS (Provides free access to the final version on ScienceDirect before July 29. No signup, registration, or fees are required, so anyone is welcome to read or download it.)
UPCOMING EXAMS
Master’s Defense
Title: Geocoding Pipeline Development and Data Quality Assessment For Enhancing Precision Medicine Research
Student: Cat Kim
Date/Time: Monday, June 30, 12pm PT
In-Person Location: South Lake Union, Room C122
Zoom: https://washington.zoom.us/j/93471587664
Abstract: Geographic location shapes health outcomes through environmental exposures, socioeconomic conditions, and access to care. However, the quality of geocoded address data to facilitate these inferences remains poorly characterized to understand the estimation error and performance nationwide. This thesis presents a geocoding benchmarking study evaluating the DeGAUSS geocoding framework across a curated reference dataset of over 270,000 public locations spanning U.S. states and territories. A sensitivity analysis across five match score thresholds demonstrates that relaxing quality criteria increases coverage while producing increases in median positional error nationally. Geographic stratification reveals performance variation across regions, including higher error rates in U.S. territories that should be investigated further given the limited sample sizes. A principled spatial outlier removal method based on state boundary validation distinguishes geocoder misclassification from reference data error. Together, these findings suggest that geocoding quality standards may need to incorporate geographic context to support accurate residential linkage in integrative precision medicine research.