Tien-jui Lee

Tien-Jui Lee is a software engineer who worked on human-computer interaction, ubiquitous computing, and sensor-enabled embedded systems in the University of Washington's Ubiquitous Computing Lab. A 2015 University of Washington Electrical & Computer Engineering report identified him as an electrical-engineering Ph.D. student and described his work on MagnifiSense; the lab's current members page lists him as a founding software engineer at Dropzone AI. DBLP's author record associates TienJui Lee with the University of Washington and lists five UbiComp/CHI papers from 2011–2018. These sources support the identity and research history, but they do not publicly confirm a degree-award year, so this profile does not add a specific graduation year or assert that the Ph.D. was awarded.

• Present (verified September 2026)·Dropzone AI·Founding Software Engineer
  • This is the current label on the University of Washington Ubicomp Lab member page; no start date or detailed duties are inferred.
• 2011–2018 (public publication record)·University of Washington / Ubicomp Lab·Researcher and doctoral researcher
  • DBLP lists five publications associated with the University of Washington; the university's 2015 report explicitly describes him as an electrical-engineering Ph.D. student.

• University of Washington | Doctoral study in Electrical Engineering
  • The university's 2015 report confirms doctoral-student status at that time. This review did not find a publicly verifiable degree-award year, so the profile does not convert that status into an awarded Ph.D.

• MagnifiSense (2015): Infers device interaction with wrist-worn passive magneto-inductive sensors, including appliance-use identification and exploration of individual carbon-footprint tracking. Project page · University of Washington report
• Seismo (2018): Uses a smartphone's built-in accelerometer and camera to estimate pulse transit time for blood-pressure monitoring. Project page
• An Ultra-low-power Human Body Motion Sensor (2012): Uses static electric-field sensing for low-power human-motion sensing. Project page

The profile was checked against the public sources above on September 23, 2026. The LinkedIn landing page redirected to a sign-in/registration wall. No personal homepage, GitHub, Google Scholar, or ORCID account was confirmed in this review; same-name accounts and project repositories were not attributed to him. Roles, member pages, and URLs may change; consult the original pages for current details.