Qinzi Zhang

18 papers A* 5A 4B 1Journal 8

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Empirical Tests of Optimization Assumptions in Deep Learning. CoRR Hoang Tran, Qinzi Zhang, Ashok Cutkosky
2024	A	`conf`	Fault-tolerant Consensus in Anonymous Dynamic Network. ICDCS Qinzi Zhang, Lewis Tseng
2024	J	`jnl`	Fault-tolerant Consensus in Anonymous Dynamic Network. CoRR Qinzi Zhang, Lewis Tseng
2024	A*	`conf`	Private Zeroth-Order Nonsmooth Nonconvex Optimization. ICLR Qinzi Zhang, Hoang Tran, Ashok Cutkosky
2024	J	`jnl`	Private Zeroth-Order Nonsmooth Nonconvex Optimization. CoRR Qinzi Zhang, Hoang Tran, Ashok Cutkosky
2024	A*	`conf`	Random Scaling and Momentum for Non-smooth Non-convex Optimization. ICML Qinzi Zhang, Ashok Cutkosky
2024	J	`jnl`	Random Scaling and Momentum for Non-smooth Non-convex Optimization. CoRR Qinzi Zhang, Ashok Cutkosky
2024	A	`conf`	The Power of Abstract MAC Layer: A Fault-Tolerance Perspective. DISC Qinzi Zhang, Lewis Tseng
2024	J	`jnl`	The Power of Abstract MAC Layer: A Fault-tolerance Perspective. CoRR Qinzi Zhang, Lewis Tseng
2022	A*	`conf`	Brief Announcement: Computability and Anonymous Storage-Efficient Consensus with an Abstract MAC Layer. PODC Lewis Tseng, Qinzi Zhang
2022	J	`jnl`	CRACAU: Byzantine Machine Learning Meets Industrial Edge Computing in Industry 5.0. IEEE Trans. Ind. Informatics Anran Du, Yicheng Shen, Qinzi Zhang, Lewis Tseng, Moayad Aloqaily
2022	J	`jnl`	Differentially Private Online-to-Batch for Smooth Losses. CoRR Qinzi Zhang, Hoang Tran, Ashok Cutkosky
2022	A*	`conf`	Differentially Private Online-to-batch for Smooth Losses. NeurIPS Qinzi Zhang, Hoang Tran, Ashok Cutkosky
2021	A*	`conf`	Practical approximate consensus algorithms for small devices in lossy networks. MobiCom Qinzi Zhang, Tigran Bantikyan, Lewis Tseng
2020	A	`conf`	Brief Announcement: Reaching Approximate Consensus When Everyone May Crash. DISC Lewis Tseng, Qinzi Zhang, Yifan Zhang
2020	B	`conf`	Echo-CGC: A Communication-Efficient Byzantine-Tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network. OPODIS Qinzi Zhang, Lewis Tseng
2020	J	`jnl`	Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network. CoRR Qinzi Zhang, Lewis Tseng
2020	A	`conf`	Exact Consensus under Global Asymmetric Byzantine Links. ICDCS Lewis Tseng, Qinzi Zhang, Saptaparni Kumar, Yifan Zhang

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.