Dai Hai Nguyen

18 papers A 2Journal 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization. CoRR Dai Hai Nguyen, Duc Dung Nguyen, Atsuyoshi Nakamura, Hiroshi Mamitsuka
2025	A	`conf`	Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization. UAI Dai Hai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura
2025	J	`jnl`	Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization. CoRR Dai Hai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura
2025	A	`conf`	Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference. AISTATS Dai Hai Nguyen, Tetsuya Sakurai, Hiroshi Mamitsuka
2024	J	`jnl`	Moreau-Yoshida variational transport: a general framework for solving regularized distributional optimization problems. Mach. Learn. Dai Hai Nguyen, Tetsuya Sakurai
2023	J	`jnl`	Mirror variational transport: a particle-based algorithm for distributional optimization on constrained domains. Mach. Learn. Dai Hai Nguyen, Tetsuya Sakurai
2023	J	`jnl`	Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization Problems. CoRR Dai Hai Nguyen, Tetsuya Sakurai
2023	J	`jnl`	On a linear fused Gromov-Wasserstein distance for graph structured data. Pattern Recognit. Dai Hai Nguyen, Koji Tsuda
2023	J	`jnl`	Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference. CoRR Dai Hai Nguyen, Tetsuya Sakurai, Hiroshi Mamitsuka
2022	J	`jnl`	A Particle-Based Algorithm for Distributional Optimization on \textit{Constrained Domains} via Variational Transport and Mirror Descent. CoRR Dai Hai Nguyen, Tetsuya Sakurai
2022	J	`jnl`	On a linear fused Gromov-Wasserstein distance for graph structured data. CoRR Dai Hai Nguyen, Koji Tsuda
2021	J	`jnl`	A generative model for molecule generation based on chemical reaction trees. CoRR Dai Hai Nguyen, Koji Tsuda
2021	J	`jnl`	Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels. Mach. Learn. Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
2021	J	`jnl`	Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels. CoRR Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
2020	J	`jnl`	Potential Application of Gold Nanospheres as a Surface Plasmon Resonance Based Sensor for In-Situ Detection of Residual Fungicides. Sensors Hang Nguyen Thi Nhat, Ngoc Thuy Trang Le, Nguyen Thi Phuong Phong, Dai Hai Nguyen, Minh-Tri Nguyen-Le
2019	J	`jnl`	ADAPTIVE: leArning DAta-dePendenT, concIse molecular VEctors for fast, accurate metabolite identification from tandem mass spectra. Bioinform. Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
2019	J	`jnl`	Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches. Briefings Bioinform. Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
2018	J	`jnl`	SIMPLE: Sparse Interaction Model over Peaks of moLEcules for fast, interpretable metabolite identification from tandem mass spectra. Bioinform. Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.