Rong Ge

Rong Ge is the Cue Family Associate Professor of Computer Science at Duke University's Trinity College of Arts & Sciences, also serving as Director of Graduate Studies for the Computer Science PhD program since 2023. His research focuses on theoretical computer science and machine learning, with contributions to non-convex optimization, neural networks, and algorithm design. Ge holds a PhD from Princeton University (2013) and was a Microsoft Research postdoc before joining Duke.

His work bridges foundational theory with practical machine learning challenges, emphasizing provable guarantees for algorithms in settings like sparse coding, phase retrieval, and transformer models. Recent grants include leadership of the THEORINET initiative (Simons/National Science Foundation) and NSF CAREER funding. Ge advises multiple PhD students and teaches courses in algorithms and machine learning theory.

• Education: PhD in Computer Science (Princeton University, 2013)
• Awards: Alfred P. Sloan Research Fellowship (2019-2023)
• Key Research Areas: Optimization landscapes, neural network theory, self-supervised learning, and robust statistical methods

Publications emphasize theoretical insights into neural networks' behavior, including calibration mechanisms, depth separation, and edge-of-stability dynamics. His work frequently combines mathematical rigor with real-world applicability in areas like natural language processing and vision-language models.

Grants include $2.5M THEORINET collaboration (2020-2025) and NSF-funded projects addressing non-convex optimization landscapes. Advising focuses on developing students' capacity for theoretical innovation with practical impact.