Paul Schmiedmayer
Instructor at Stanford Division of Computational Medicine
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolPaul Schmiedmayer is an instructor and AI leader at Stanford with nine years of experience building data-driven, patient-facing digital health systems that run on resource-constrained devices. He leads digital health and AI efforts at the Mussallem Center for Biodesign and helps develop the Stanford Spezi ecosystem to enable interoperable, privacy-preserving clinical interventions and novel digital biomarkers. His work spans academic research, applied AI, teaching CS342, and hands-on engineering—shipping models to smartphones and smart devices to create scalable closed-loop care. A Swift enthusiast with a background from Technical University of Munich and research stints at CMU and Apple, he blends rigorous doctoral-level methods with product-minded implementation. Paul’s uncommon focus is on validating AI in real-world deployments that balance cost, privacy, and equity, not just algorithmic performance.
9 years of coding experience
9 years of employment as a software developer
Doctoral Candidate Computer Science, Doctoral Candidate Computer Science at Technical University of Munich
Github Skills (171)
healthkit10
researchkit10
proximity10
ruby10
automation10
linter10
linting10
firebase10
swiftui10
apple-health10
static-analysis10
non-blocking10
localization10
swift10
gpt10
Programming languages (15)
Github contributions (5)
Apodini/Template-Repository
Jul 2021 - Jan 2022
This repository serves as a template repository for the Apodini organization.
Contributions:3 releases, 1 review, 17 commits in 6 months
templateserves
StanfordSpezi/SpeziMedication
Nov 2023 - Jan 2025
Medication module of the Stanford Spezi framework
Contributions:5 releases, 4 reviews, 17 PRs in 1 year 2 months
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