Research Assistant at University of North Carolina at Charlotte
Charlotte, North Carolina, United States
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Summary
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Ekkasit Pinyoanuntapong is a research-focused machine learning engineer and Ph.D. student at UNC Charlotte with nine years of experience building production ML systems and advancing spatiotemporal 3D human understanding. He has driven state-of-the-art results in text-to-motion and radar-based semi-supervised domain adaptation, and designed a multiaxial mixer architecture that boosted pose-model performance by double-digit margins. Prior industry roles at Cox Automotive and Snap combine robust MLOps and full-stack delivery—shipping high-accuracy lending models on AWS and vehicle recognition pipelines—alongside earlier work in real-time robotics and interactive multimedia. Comfortable moving between research and production, he blends deep model design with practical deployment, and his background in telecommunications and web/AV systems gives him an uncommon cross-domain perspective on multimodal perception problems.
9 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of North Carolina at Charlotte
Bachelor's degree Telecommunication Engineering, Bachelor's degree Telecommunication Engineering at Sirindhorn International Institute of Technology (SIIT), Thammasat University
Software Engineering Software Enginner, Software Engineering Software Enginner at Stevens Institute of Technology
Contributions:132 pushes, 2 branches in 3 years 11 months
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Ekkasit Pinyoanuntapong - Research Assistant at University of North Carolina at Charlotte