I’m Anthi Terezaki, a Machine Learning Engineer who enjoys turning complex problems into practical ML solutions. I’ve built reinforcement learning and supervised learning models for energy applications—optimizing battery charge/discharge strategies and forecasting energy market signals—while also creating end-to-end data pipelines and evaluation frameworks for large-scale time-series datasets.
I’m also comfortable bridging research and real products through full-stack engineering. From production-ready backend/frontend components to deploying workflows with modern MLOps practices, I focus on clear communication, strong problem-solving, and fast iteration. My background across deep learning, optimization, computer vision, and quantitative finance keeps my work both mathematically grounded and broadly applicable.
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