Julio Dominguez is a Cellular Automation Engineer with a decade of hands-on experience applying software and data skills to wireless networks and neuroscience research. A UC San Diego Cognitive Science graduate specializing in machine learning with a computer science minor, he programs in Python, C/C++/C#, and Java to build automation, analysis, and testing tools that accelerated test automation at Qualcomm and characterized handover failures at Apple-level live LTE/NR networks. He has a track record of turning manual processes into scalable pipelines—reducing implementation times from months to under a week and automating ~80% of test cases—while delivering dashboards used for executive decisions. Comfortable at the intersection of research and production, he has debugged neural-network bugs that impacted 30% of lab projects and presented work at multiple conferences. Based in San Diego, he combines domain expertise in RF performance KPIs with machine-learning intuition to uncover nonobvious degradation patterns and drive measurable operational improvements.
Contributions:3 PRs, 28 pushes, 3 branches in 1 year 6 months
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