Zhixiang Teoh is a software engineer with six years of experience building backend systems, Android features, and research-grade distributed systems for machine learning. Currently on DoorDash’s Launchpad team, he blends mobile and backend work and has interned on Chrome’s intelligence team at Google. His research at the University of Michigan accelerated a Bayesian encoder’s training by 90% through dataset caching and shuffling and explored QoS-aware multi-tiered memory systems, reflecting a practical bent for performance optimization. He’s shipped real-time geolocation and graph-backed services at startups and contributed WebXR media demos during an open-source stint showcased by Meta. Based in Ann Arbor, he pairs strong math and CS foundations with a curiosity for programming languages, databases, and open-source tooling.
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