Yaning Lin - RankMe

20 papers Journal 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	N -player Pareto game for the discrete-time Markov jump systems with multiplicative noises using off-policy reinforcement learning. Math. Comput. Simul. Chunling Bo, Yaning Lin, Yuxia Li
2026	J	`jnl`	Pareto-based Stackelberg solutions for the mean-field type discrete-time stochastic systems with cooperative followers. J. Comput. Appl. Math. Shuaichen Geng, Yaning Lin
2025	J	`jnl`	Stackelberg-Nash solution to the mean-field stochastic difference game with two followers. Syst. Control. Lett. Shuaichen Geng, Yaning Lin, Weihai Zhang
2025	J	`jnl`	Two-player LQ Stackelberg difference game with open-loop strategy under stochastic discrete-time dynamics in finite horizon. J. Comput. Appl. Math. Yaning Lin, Shuaichen Geng, Weihai Zhang
2024	J	`jnl`	Incentive Feedback Stackelberg Strategy in Mean-Field Type Stochastic Difference Games. J. Syst. Sci. Complex. Wenhui Gao, Yaning Lin, Weihai Zhang
2024	J	`jnl`	Open-loop and closed-loop Nash equilibria for the LQ stochastic difference game. J. Comput. Appl. Math. Wenhui Gao, Yaning Lin
2023	J	`jnl`	Feedback Stackelberg Solution for Mean-Field Type Stochastic Systems with Multiple Followers. J. Syst. Sci. Complex. Yaning Lin, Weihai Zhang
2023	J	`jnl`	Incentive feedback Stackelberg strategy for the discrete-time stochastic systems. J. Frankl. Inst. Wenhui Gao, Yaning Lin, Weihai Zhang
2022	J	`jnl`	Incentive feedback Stackelberg strategy for stochastic systems with state-dependent noise. J. Frankl. Inst. Yaning Lin, Wenhui Gao, Weihai Zhang
2021	J	`jnl`	Linear quadratic open-loop Stackelberg game for stochastic systems with Poisson jumps. J. Frankl. Inst. Yaning Lin
2021	J	`jnl`	Pareto efficiency in the infinite horizon mean-field type cooperative stochastic differential game. J. Frankl. Inst. Yaning Lin, Weihai Zhang
2020	J	`jnl`	Necessary/sufficient conditions for Pareto optimality in finite horizon mean-field type stochastic differential game. Autom. Yaning Lin
2019	J	`jnl`	An Open-Loop Stackelberg Strategy for the Linear Quadratic Mean-Field Stochastic Differential Game. IEEE Trans. Autom. Control. Yaning Lin, Xiushan Jiang, Weihai Zhang
2019	J	`jnl`	Feedback Stackelberg strategies for the discrete-time mean-field stochastic systems in infinite horizon. J. Frankl. Inst. Yaning Lin
2019	J	`jnl`	Linear Quadratic Pareto Game of the Stochastic Systems in Infinite Horizon. J. Optim. Theory Appl. Yaning Lin
2018	J	`jnl`	Infinite horizon linear quadratic Pareto game of the stochastic singular systems. J. Frankl. Inst. Yaning Lin, Tianliang Zhang, Weihai Zhang
2018	J	`jnl`	Necessary and sufficient conditions for Pareto optimality of the stochastic systems in finite horizon. Autom. Yaning Lin, Xiushan Jiang, Weihai Zhang
2018	J	`jnl`	Pareto-based guaranteed cost control of the uncertain mean-field stochastic systems in infinite horizon. Autom. Yaning Lin, Tianliang Zhang, Weihai Zhang
2017	J	`jnl`	Linear quadratic Pareto optimal control problem of stochastic singular systems. J. Frankl. Inst. Weihai Zhang, Yaning Lin, Ling-Rong Xue
2016	J	`jnl`	Global output tracking control for high-order stochastic nonlinear systems with SISS inverse dynamics and time-varying delays. J. Frankl. Inst. Ling-Rong Xue, Weihai Zhang, Yaning Lin

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.