Joe Breda
About Me
I am on the Job Market
I am a final year PhD student in the Ubiquitous Computing Lab at the University of Washington advised by Shwetak Patel. I am also currently a student researcher at Google leading evaluations of LLMs for differential diagnosis with Daniel McDuff.
My research is on developing and evaluating artificial intelligence and human-centric sensing to enhance public health and societal well-being. I do this through population-scale deployment studies and by extending the capacity of technologies people already use with novel sensing and intervention. Some applications I've worked on include AI for accessible healthcare, infectious disease prevention, promoting sustainable and healthy behavior, and urbanism.
Recent News
- FeverPhone highlighted in GetMobile Column Article! August 2025
- Joined Google to evaluate LLMs for accessible symptom checking differential diagnosis through a population-scale deployment. July 2025
- Successfully Defended my Thesis, titled "Ubiquitous Computing Platforms as Scalable Surrogates in Public Health and Well-being" May 2025
- ProxiCycle featured in NPR All Things Considered! May 2025
- Two papers on improving navigation platforms for active transportation accepted to CHI 2025!
- FeverPhone won Distinguished Paper Award at Ubicomp 2024!
- Spent the summer of 2024 deploying smart bicycle sensors in Seattle.
- Thailand Rideshare Study Published in CSCW 2024!
- Traveled to the NIH in DC to conduct a clinical trials, October 2023.
- Traveled to Cancun to present FeverPhone at Ubicomp 2023.
- Traveled to Germany for the 10th Heidelberg Laureate Forum!
- Traveled to Thailand again to deploy mobile AQI sensors with motorcycle drivers, July 2023.
- FeverPhone Published in IMWUT 2023!
- Traveled to Thailand to conduct qualitative interviews wtih rideshare drivers, August 2022.
- Left my Student Researcher Position at Google, August 2022.
- Spent Summer 2022 part-time at Google and part-time conducting a clinical trial for FeverPhone at UW Northwest Hospital.
Research Approach
My research is impact-driven, motivated by socio-technical alignment of AI and population-scale sensing. I run human-factors studies through population-scale deployments, prospective cohort studies, and human-expert evaluations to understand the complexity of aligning these technologies with real populations to support their collective needs.
To reach populations at scale, I often leverage or repurpose society-scale technologies people already use as platforms to develop novel systems that can be made broadly accessible. This includes systems built into consumer-facing AI chatbots for accessible healthcare, leveraging biomarkers from wearable devices for infectious disease prevention, and crowdsensing geospatial signals influencing human behavior in urban environment from smartphones.
Notable Experiences
I have collaborated with a variety of stakeholders and instutitions including: the National Institute of Health (NIH), UW Medicine's Emergency Department, and local cycling and pedestrian activist organizations to deploy novel personal health and environmental sensing systems.
Previously, I was a Student Researcher at Google Research where I worked on geospatial computer vision models for forecasting driver safety to improve Google Maps.
I have also traveled to Bangkok and Chiang Mai Thailand to conduct a mixed-methods study and mobile sensor deployment to understand the experience of gig-workers in relation to severe pollution exposure.
I also founded and lead the Allen School Graduate Entrepreneurship Club and helped start the CS4Env cross-department collaborative initiative.
Personal Interests
Outside of research, I like to make CGI posters, compose and produce electronic music, play guitar, and take photos. I am particulary inspired by ambience, harsh noise, procedurally generated art, contrasting natural and synthetic textures, and the design of everyday things. I also like cycling, bouldering, creative writing, making iced pour-over coffee, and engaging with public space.
Publications
Lessons Learned From FeverPhone: Towards Scalable, Accessible At-Home Diagnostics via Fever Detection on Unmodified Smartphones
GetMobile: Mobile Computing and Communications, 2025 pdf
ProxiCycle: Passively Mapping Cyclist Safety Using Smart Handlebars for Near-Miss Detection
Conference on Human Factors in Computing Systems (CHI), 2025 pdf GeekWire
UW News Video | Appeared on NPR All Things Considered & Short Wave!
NightLight: A smartphone middleware application for passively mapping nighttime sidewalk light data for improved pedestrian routing
Conference on Human Factors in Computing Systems (CHI), 2025 pdf
* Indicates equal contribution
Exploring and characterizing large language models for embedded system development and debugging
Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, CHI LBW 2024 pdf
Proceedings of the ACM on Human-Computer Interaction (CSCW), 2024 pdf
* Indicates equal contribution
Thermal Earring: Low-power Wireless Earring for Longitudinal Earlobe Temperature Sensing
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2024 pdf
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2023 pdf Gizmodo
Understanding People's Concerns and Attitudes Towards Smart Cities
Conference on Human Factors in Computing Systems (CHI), 2023 pdf
Passively Sensing SARS-CoV-2 RNA in Public Transit Buses
Science of the Total Environment, 2022 pdf
Phone-based ambient temperature sensing using opportunistic crowdsensing and machine learning
Sustainable Computing: Informatics and Systems, 2021 pdf
Hanging Gardens of Babylon: Reframing Urban Agriculture as an Opportunity for Social Engagement
Self-Sustainable CHI'20 pdf
Hot or Not: Leveraging Mobile Devices for Ubiquitous Temperature Sensing
BuildSys'19 pdf
Staring at the Sun: A Physical Black-box Solar Performance Model
BuildSys'18 pdf
Fancy That: Measuring Electricity Grid Voltage Using a Phone and a Fan
COMPASS'18 pdf
