Luciano Resende is an AI/ML platform leader with about 19 years of experience building enterprise-grade, open-source-first data and analytics platforms, currently shaping AI infrastructure at Apple from San Francisco. He is the creator and a top contributor to Elyra and a principal architect behind Jupyter Enterprise Gateway, projects that scale Jupyter workflows across Spark and Kubernetes for real-world ML lifecycles. Luciano blends deep systems and DevOps expertise—contributing to Apache Spark, Toree, Zeppelin and other flagship projects—with hands-on work in build, release automation and CI/CD that reliably moves research notebooks into production. A seasoned engineering manager and ASF mentor, he pairs product-oriented Agile leadership with low-level engineering chops, often improving build systems and kernel integrations that most users never see but depend on.
19 years of coding experience
12 years of employment as a software developer
MS (Incomplete), Computer Software Engineering, MS (Incomplete), Computer Software Engineering at Harvard University
Bachelor of Science (B.S.), Computer Science, Bachelor of Science (B.S.), Computer Science at Universidade Federal de Mato Grosso
Contributions:2 reviews, 122 commits, 38 PRs in 3 years 8 months
Contributions summary:Luciano primarily contributed to the Apache Bahir project by introducing build configurations and scripts, including a script for changing Scala versions. They refactored and added examples, particularly related to MQTT integration, and fixed test configurations. Additionally, the user created release helper scripts and modified existing scripts to improve the release process, including support for release from branch and tag-based releases.
Contributions:24 reviews, 132 commits, 90 PRs in 6 years
Contributions summary:Luciano primarily focused on updating and maintaining the Apache Toree project's build and dependency management. They updated sbt plugins, including sbt-assembly and sbt-dependency-graph, to newer versions. The user also implemented changes to the build process to integrate with Hadoop distributions and ensure compatibility, along with fixing test failures. Furthermore, they made adjustments to configuration options and the release process with a release build script.
incubatingapachebig-dataapache-sparkjava
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