Ayman Zeine is a Senior Data Engineer with 11 years of experience applying deep learning, signal processing, and computer vision to real-world problems across academia and industry. A Lehigh CS graduate, he has led development of scalable research tools—most notably the MoSeq behavior-segmentation API at Harvard Medical School—using Python, Dask, and interactive visualization stacks to handle big data and diagnostics. His work spans applied ML in neurobiology and electrophysiology, indoor RF-based object localization (co-inventing an RNN-driven sensing method), and production integrations for web and iOS applications. Currently driving data engineering at Sungage Financial, he blends research-grade modeling with production engineering best practices. Colleagues describe him as a pragmatic researcher who consistently turns experimental ML into reliable, deployable systems.
11 years of coding experience
5 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Lehigh University
Contributions:2 PRs, 23 pushes, 2 branches in 4 months
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