Qing Lan
Founder & AI Systems Architect at Daika AI
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolQing Lan is the founder and AI systems architect at Daika AI, combining a PhD in mechanical engineering with a decade of hands-on experience building production-ready AI systems that bridge research and real-world operations. He specializes in turning ambiguous problems, messy data, and high-stakes decisions into reliable, maintainable systems—emphasizing mathematical rigor, operational constraints, and long-term reliability over prototypes. Qing’s background includes accelerating Monte Carlo physics simulations by 10^5× with neural surrogates for clinical diffuse reflectance spectroscopy and leading ML work at Apache MXNet and Deep Java Library, contributing cross-platform demos from Spark to Android. He partners with engineering-driven companies and startups to design end-to-end decision-support and automation systems, and has quantified and delivered multi-phase roadmaps with strong ROI projections for enterprise automation. Based in Sunnyvale, he pairs deep computational fluency with product sensibility and a practical optimism that prioritizes robust execution. Outside work he trains in MMA, runs, and keeps a Sichuan hotpot tradition alive—small signals of discipline and culture that shape his collaborative style.
10 years of coding experience
6 years of employment as a software developer
Bachelor's degree Physics, Bachelor's degree Physics at Sichuan UniversitySummer Program Quantum Computing, Summer Program Quantum Computing at Fudan UniversityM.S. in Engineering Science & Technology Entrepreneurship, M.S. in Engineering Science & Technology Entrepreneurship at University of Notre Dame
Stackoverflow
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Github Skills (21)
pytorch10
spark10
image-classification10
mxnet10
machine-learning10
java10
ml10
scala10
mle10
javas10
deep-learning10
object-detection10
computer-vision10
web-development10
back-end-development9
Programming languages (10)
Github contributions (5)
deepjavalibrary/djl-demo
Apr 2020 - Aug 2022
Demo applications showcasing DJL
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:114 reviews, 61 commits, 200 PRs in 2 years 4 months
Contributions summary:Qing contributed to the `djl-demo` repository by adding new demo applications, specifically focusing on a Spark-based image classification example and an Android application for quick draw recognition. They also worked on the web demo, including frontend and backend modifications for a doodle game and interactive shell. These commits demonstrate the user's ability to integrate different AI models with diverse platforms, including web, Android, and Spark, with both frontend and backend implementations.
demo-applicationsmxnetdeep-learningaidjl
deepjavalibrary/djl
May 2019 - Jan 2023
An Engine-Agnostic Deep Learning Framework in Java
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:1 release, 703 reviews, 539 commits in 3 years 8 months
Contributions summary:Qing's commits indicate a focus on enhancing the machine learning pipeline and improving the functionality of the backend within the DJL framework. The user added a new example for stable diffusion, added support for reading a class from an input stream, and introduced features like a rotation method to image processing. They worked on improving the underlying framework by adding operations like cumprod and float types for performance enhancement.
pytorchmxnetcaffe2deep-learningagnostic
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