Paul Schmiedmayer

Instructor at Stanford University

Palo Alto, California, United States
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Summary

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Rockstar
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Top School
Paul 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.
code9 years of coding experience
job8 years of employment as a software developer
bookDoctoral Candidate, Computer Science, Doctoral Candidate, Computer Science at Technical University of Munich
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Github Skills (174)

healthkit10
researchkit10
proximity10
estimote10
runner10
medical10
swiftui10
udp10
apple-health10
non-blocking10
github-actions-runner10
blocking10
swift10
high-performance10
chatbot10

Programming languages (15)

PowerShellC++TeXHTMLJupyter NotebookKotlinTypeScriptDockerfile

Github contributions (5)

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StanfordSpezi/SpeziLLM

May 2023 - Mar 2025

Large Language Model (LLM) module for the Spezi Ecosystem
Contributions:20 releases, 92 reviews, 55 PRs in 1 year 9 months
chatbotgptioslarge-language-modelsllm
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
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Paul Schmiedmayer - Instructor at Stanford University