Zhengyuan Zhu is a machine learning engineer with a decade of experience building production-grade AI systems, currently designing the multi-agent orchestration behind Adobe Experience Platform’s enterprise assistant. He combines a strong NLP research background—15 papers on misinformation detection, fact-checking, and knowledge graphs during a PhD at UT Arlington—with hands-on systems engineering that routes and composes dozens of specialized agents in real time for tens of thousands of users. His MuRAR multimodal retrieval-augmented reasoning work won Best Demonstration at COLING 2025 and led to an Adobe patent, reflecting a knack for turning research into scalable product features. Pragmatic and detail-oriented, he improved agent routing accuracy to 89% through context-aware ranking and builds grounded response synthesis pipelines that prioritize trust and provenance. Based in the Bay Area, he balances academic rigor with production impact, focused on making multi-agent AI reliable at enterprise scale.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of Texas at Arlington
Bachelor's Degree, Information Management and Information Systems, Bachelor's Degree, Information Management and Information Systems at Tianjin University of Finance and Economics
Contributions:35 commits, 29 pushes, 1 branch in 3 months
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Zhengyuan Zhu - Machine Learning Engineer at Adobe