DanielLam
Guangzhou City, Guangdong Province, China
Summary
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SeniorDaniel Lam is a computer science student and AI-focused engineer at UT Austin who blends research-grade robotics work with production-ready generative AI systems. He has 11 years of engineering experience building low-latency robot control pipelines (sub-10ms with ROS and TensorFlow) and training custom models for dynamic manipulation, alongside shipping full-stack RAG-based AI assistants that cut information lookup times by 80%. At Lockheed Martin he prototyped a VS Code AI assistant using Llama 3.3 that improved developer productivity by 40%, and he currently leads internal technology for a $25M+ sustainable building portfolio. Comfortable across Python, C/C++, TypeScript, PyTorch and LangChain, he moves smoothly between research, systems engineering, and product delivery—often translating simulation insights into real-time control and cloud-deployed tools. Notably, he pairs hands-on robotics experiments with scalable software architecture, accelerating both lab research and organizational workflows.
11 years of coding experience
Github Skills (148)
charting10
http-client10
svg10
javascript10
charts10
elm10
echarts10
data-visualization10
mind-mapping10
redux-saga10
visjs10
typescript10
vue10
nodejs10
visualization10
Programming languages (10)
Github contributions (5)
DanielWLam/iShadowsocks
Dec 2015 - Jan 2016
Contributions:9 commits, 7 pushes, 1 branch in 18 days
DanielWLam/learning
Dec 2015 - Feb 2018
Contributions:71 pushes, 1 branch in 2 years 2 months
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