Matt Jordan is a PhD candidate in Machine Learning at The University of Texas at Austin with a decade of software engineering and research experience bridging academia and industry. He previously engineered production systems at MaestroIQ and contributed to research projects at MIT CSAIL before joining AI2 as a research scientist collaborator on GitHub. Comfortable moving between rigorous theoretical work and pragmatic implementation, he focuses on making ML research reproducible and deployable. Based in Boston, he blends strong foundations in mathematics and computer science from MIT with hands-on development skills honed over years of engineering roles. Notably, his profile reflects both long-term research commitments and practical product engineering—an uncommon combination that helps translate prototype ideas into robust systems.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at The University of Texas at Austin
Mathematics and Computer Science, Mathematics and Computer Science at Massachusetts Institute of Technology
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