1. Dai Hai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura, 'Multiple Wasserstein gradient descent for multi-objective distributional optimization', UAI 2025
2. Dai Hai Nguyen, Tetsuya Sakurai, Hiroshi Mamitsuka, 'Wasserstein gradient flow over Variational parameter space for variational inference', AISTATS 2025
3. Dai Hai Nguyen, Tetsuya Sakurai, 'Moreau-Yoshida Variational Transport: a general framework for solving regularized distributional optimization problems', Machine Learning 2024
4. Dai Hai Nguyen, Tetsuya Sakurai, 'Mirror Variational Transport: A Particle-based Algorithm for Distributional Optimization on Constrained Domains', Machine Learning 2023
5. Dai Hai Nguyen, Koji Tsuda, 'On a linear fused Gromov-Wasserstein distance for graph structured data', Pattern Recognition 2023
6. Haishan Zhang, Dai Hai Nguyen, Koji Tsuda, 'Differentiable optimization layers enhance GNN-based mitosis detection', Scientific Reports 2023
7. Dai Hai Nguyen, Koji Tsuda, 'Generating reaction trees with cascaded variational autoencoders', The Journal of Chemical Physics 2022
8. Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka, 'Machine Learning for Metabolic Identification', Creative Complex Systems, Springer, Singapore, 2021
9. Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka, 'Learning Subtree Pattern Importance for Weisfeiler-Lehman based Graph Kernels', Machine Learning 2021
10. Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka, 'ADAPTIVE: leArning DAta-dePendenT, concise molecular VEctors for fast, accurate metabolite identification from tandem mass spectra', Bioinformatics
Research Experience
Jan., 2025 - Present: Associate Professor at Hokkaido University; Apr., 2022 - Dec., 2024: Assistant Professor at the University of Tsukuba; Nov., 2020-Mar., 2022: Postdoctoral Researcher at the University of Tokyo; Oct., 2017-Sep., 2019: JSPS Research Fellow (DC2) at Kyoto University.
Education
Oct., 2017-Sep., 2020, PhD. student @ Kyoto University, Japan; Sep., 2008-Aug., 2013, Undergraduate @ Hanoi University of Science and Technology, Vietnam.
Background
Research Interests: machine learning, especially Convex Optimization, Kernel Methods, Optimal Transport, Information Geometry.