Yangjing Zhang

11 papers A 1Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	A	`conf`	DNNLasso: Scalable Graph Learning for Matrix-Variate Data. AISTATS Meixia Lin, Yangjing Zhang
2024	J	`jnl`	DNNLasso: Scalable Graph Learning for Matrix-Variate Data. CoRR Meixia Lin, Yangjing Zhang
2024	—	`conf`	EFormer-VPR: Fusing Events and Frames with Transformer for Visual Place Recognition. ITSC Yangjing Zhang, Yanqing Shen, Ziyu Zhu, Renwei Hai, Shitao Chen, Nanning Zheng
2024	J	`jnl`	Learning graph Laplacian with MCP. Optim. Methods Softw. Yangjing Zhang, Kim-Chuan Toh, Defeng Sun
2024	J	`jnl`	On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models. J. Mach. Learn. Res. Yangjing Zhang, Ying Cui, Bodhisattva Sen, Kim-Chuan Toh
2023	J	`jnl`	Strong Variational Sufficiency for Nonlinear Semidefinite Programming and Its Implications. SIAM J. Optim. Shiwei Wang, Chao Ding, Yangjing Zhang, Xinyuan Zhao
2022	J	`jnl`	On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations. J. Mach. Learn. Res. Hong T. M. Chu, Kim-Chuan Toh, Yangjing Zhang
2021	J	`jnl`	An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems. SIAM J. Math. Data Sci. Ning Zhang, Yangjing Zhang, Defeng Sun, Kim-Chuan Toh
2020	J	`jnl`	A Proximal Point Dual Newton Algorithm for Solving Group Graphical Lasso Problems. SIAM J. Optim. Yangjing Zhang, Ning Zhang, Defeng Sun, Kim-Chuan Toh
2020	J	`jnl`	An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems. Math. Program. Yangjing Zhang, Ning Zhang, Defeng Sun, Kim-Chuan Toh
2020	J	`jnl`	Learning Graph Laplacian with MCP. CoRR Yangjing Zhang, Kim-Chuan Toh, Defeng Sun

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.