XuanLong Nguyen
Papers
3
Total Citations
11
H-Index
2
About
XuanLong Nguyen is a researcher whose work bridges machine learning, optimal transport, and functional data analysis. His key contributions lie in developing robust, unsupervised learning methods for complex, high-dimensional data, particularly in dynamic environments. Notably, his 2022 paper on "Robust unsupervised learning of temporal dynamic vehicle-to-vehicle interactions" (7 citations) introduces novel approaches for modeling and understanding time-varying interactions in transportation systems, a critical area for autonomous driving and traffic management. Nguyen is also a pioneer in extending optimal transport theory to functional data, as demonstrated in his 2021 work on "Functional Optimal Transport: Mapping Estimation and Domain Adaptation for Functional Data" (2 citations). This work formulates a groundbreaking framework for mapping distributions on function spaces using Hilbert-Schmidt operators, enabling domain adaptation and transfer learning for data like curves, surfaces, or time series. By tackling the infinite-dimensional nature of functional data, Nguyen provides powerful tools for fields ranging from signal processing to biomedical imaging. His research is characterized by its theoretical depth and practical relevance, making significant strides in how we model, compare, and adapt complex, structured data.
Research Focus
Key Achievements
Top Papers
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