Anna Q. Email & Phone Number

Cupertino, California, Us

SwiftUI team

Cupertino, California, Us

Health team

Palo Alto, Ca, Us

• Developed significantly-improved insulin pump therapy initialization equation forms using observational study data.• Created first-in-class unsupervised learning algorithm to detect self-harm in patients with diabetes.• Investigated novel applications of customized insulin-curve modeling in automated insulin dosing systems and designed + merged addition to Loop app, which is used by 2000+ people with diabetes.

Redmond, Washington, Us

• Developed support experience for Azure Mobile iOS & Android apps using Xamarin Native and C#. The feature was successfully deployed to production and is live in the app.• Influenced and collaborated with cross-functional partners to implement 660% performance improvement to support ticket REST API used by all Azure customers.

Cupertino, California, Us

Video Apps team

• Designed new websites for Stanford American Indian Science and Engineering Society (AISES) and Stanford American Indian Organization using HTML, Javascript, and website design template.• Maintained both websites in collaboration with community leadership

Palo Alto, Ca, Us

• Engineered an in-app system, one of the first of its kind, with SwiftUI to allow patients to review their digital prescriptions for the Tidepool Loop iOS app, a closed-loop artificial pancreas system.• Worked collaboratively with design and product teams to create user-driven features that minimize cognitive burden and maximize safety.

Palo Alto, Ca, Us

• Developed a 400% faster Python-based implementation of the Loop automated insulin-dosing algorithm, then used the algorithm for issue report analysis and visualization.• Collaborated with 3 teams to ensure usability for a wide variety of use cases, including quality analysis and algorithm verification; PyLoopKit was used to demonstrate the safety of Loop to the FDA.• Gained experience with Swift, data analytics, Agile development, and Confluence/Jira.

• Independently built lower-cost, Python-based insulin pump with automated insulin delivery.• Utilized a Raspberry Pi, Python, and shell scripting.• Designed system to automatically adjust insulin rates and issue microboluses in response to blood glucose levels, as opposed to current systems that require the user to make manual insulin adjustments.• Won first place at 2019 American Indian Science and Engineering Society National Conference.

• Created a low cost (⅓ of a cent), sweat-based method to detect type 1 diabetes in situations that are currently challenging, such as with diagnosing infants.• Devised a method utilizing smartphone-colorimeter app to quantify ketone concentration.

Bar Harbor, Me, Us

• Investigated mechanisms of diabetes resistance to identify novel therapeutic targets for type 1 diabetes as a member of the Serreze Laboratory.• Work published in The Journal of Immunology.

Bachelor'S Degree, Computer Science; Notation In Spanish

High School Diploma