Tan D. Tran

16 papers A* 2B 1Journal 9Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fast approximation algorithm for non-monotone DR-submodular maximization under size constraint. J. Comb. Optim. Tan D. Tran, Canh V. Pham
2025	J	`jnl`	Fast Approximation Algorithm for Non-Monotone DR-submodular Maximization under Size Constraint. CoRR Tan D. Tran, Canh V. Pham
2025	J	`jnl`	Fast Stochastic Greedy Algorithm for k-Submodular Cover Problem. CoRR Hue T. Nguyen, Tan D. Tran, Long Giang Nguyen, Canh V. Pham
2025	J	`jnl`	Practical algorithm for minimum cost submodular cover problem with performance guarantees. Optim. Lett. Canh V. Pham, Tan D. Tran, Dung T. K. Ha, Quat V. Phu
2024	A*	`conf`	Improved Parallel Algorithm for Non-Monotone Submodular Maximization under Knapsack Constraint. IJCAI Tan D. Tran, Canh V. Pham, Dung T. K. Ha, Phuong N. H. Pham
2024	J	`jnl`	Improved Parallel Algorithm for Non-Monotone Submodular Maximization under Knapsack Constraint. CoRR Tan D. Tran, Canh V. Pham, Dung T. K. Ha, Phuong N. H. Pham
2024	J	`jnl`	Improved approximation algorithms for k-submodular maximization under a knapsack constraint. Comput. Oper. Res. Dung T. K. Ha, Canh V. Pham, Tan D. Tran
2023	—	`conf`	Improved Streaming Algorithm for Minimum Cost Submodular Cover Problem. CSoNet Tan D. Tran, Canh V. Pham, Dung P. Trung, Uyen T. Nguyen
2023	A*	`conf`	Linear Query Approximation Algorithms for Non-monotone Submodular Maximization under Knapsack Constraint. IJCAI Canh V. Pham, Tan D. Tran, Dung K. T. Ha, My T. Thai
2023	J	`jnl`	Linear Query Approximation Algorithms for Non-monotone Submodular Maximization under Knapsack Constraint. CoRR Canh V. Pham, Tan D. Tran, Dung K. T. Ha, My T. Thai
2023	—	`conf`	Maximizing a $k$-Submodular Maximization Function under an Individual Knapsack Constraint. SoICT Tan D. Tran, Canh V. Pham, Dung Ha
2023	—	`conf`	Robust Approximation Algorithms for Non-Monotone k-Submodular Maximization Under a Knapsack Constraint. KSE Dung K. T. Ha, Canh V. Pham, Tan D. Tran, Huan X. Hoang
2023	J	`jnl`	Robust Approximation Algorithms for Non-monotone k-Submodular Maximization under a Knapsack Constraint. CoRR Dung T. K. Ha, Canh V. Pham, Tan D. Tran, Huan X. Hoang
2022	B	`conf`	Fast Streaming Algorithms for k-Submodular Maximization under a Knapsack Constraint. DSAA Canh V. Pham, Dung K. T. Ha, Huan X. Hoang, Tan D. Tran
2015	J	`jnl`	Flexible and Efficient Wireless Sensor Networks for Detecting Rainfall-Induced Landslides. Int. J. Distributed Sens. Networks Chinh D. Nguyen, Tan D. Tran, Duc-Nghia Tran, Tue Huu Huynh, Duc T. Nguyen
2009	—	`conf`	Novel synthesis design of a 3-DOF silicon piezoresistive micro accelerometer. NEMS Tan D. Tran, Minh D. Nguyen, Long T. Nguyen, Tue Huu Huynh, Thuy P. Nguyen

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.