Papers
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Total Citations
2
H-Index
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About
Gabriel Petrea is a forward-thinking researcher at the intersection of machine learning and higher education strategy, with a focus on transforming how institutions manage and predict student outcomes. His most-cited work, “Machine Learning in Education: Predicting Student Performance and Guiding Institutional Decisions” (2026), has already garnered 2 citations, signaling growing recognition of its practical impact. In this study, Petrea explores how ML technologies can be leveraged to plan, monitor, and forecast student performance, drawing on survey data from the Faculty of Industrial Engineering and Robotics. His key contributions lie in demonstrating how data-driven models can empower educators and administrators to make proactive, evidence-based decisions—moving beyond traditional reactive approaches. By centering student perspectives on ML adoption, Petrea bridges technical innovation with real-world educational needs. His research is particularly valuable for institutions seeking to optimize resource allocation and personalize learning pathways. As a researcher, Petrea is helping to shape a future where machine learning not only predicts academic success but also guides strategic institutional change, making him a notable voice in the evolving field of educational technology.
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Top Papers
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