Yang Li

16 papers Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	A data-driven method for performance analysis and improvement in production systems with quality inspection. J. Intell. Manuf. Jun-Qiang Wang, Yun-Lei Song, Peng-Hao Cui, Yang Li
2023	J	`jnl`	Correction to: A data-driven method for performance analysis and improvement in production systems with quality inspection. J. Intell. Manuf. Jun-Qiang Wang, Yun-Lei Song, Peng-Hao Cui, Yang Li
2022	J	`jnl`	Data-driven modelling, analysis and improvement of multistage production systems with predictive maintenance and product quality. Int. J. Prod. Res. Peng-Hao Cui, Jun-Qiang Wang, Yang Li
2022	J	`jnl`	Energy-Saving Control in Multistage Production Systems Using a State-Based Method. IEEE Trans Autom. Sci. Eng. Yang Li, Peng-Hao Cui, Jun-Qiang Wang, Qing Chang
2022	J	`jnl`	Predictive Maintenance Decision Making Based on Reinforcement Learning in Multistage Production Systems. IEEE Access Maomao Feng, Yang Li
2021	J	`jnl`	An Improved Aggregation Method for Performance Analysis of Bernoulli Serial Production Lines. IEEE Trans Autom. Sci. Eng. Fei-Yi Yan, Jun-Qiang Wang, Yang Li, Peng-Hao Cui
2019	J	`jnl`	Energy Economics in Multistage Manufacturing Systems With Quality Control: A Modeling and Improvement Approach. IEEE Access Junqiang Wang, Yang Li
2018	J	`jnl`	Event-Based Supervisory Control for Energy Efficient Manufacturing Systems. IEEE Trans Autom. Sci. Eng. Yang Li, Qing Chang, Jun Ni, Michael P. Brundage
2017	J	`jnl`	An event-based analysis of condition-based maintenance decision-making in multistage production systems. Int. J. Prod. Res. Yang Li, Qirong Tang, Qing Chang, Michael P. Brundage
2016	J	`jnl`	Implementing a Real-Time, Energy-Efficient Control Methodology to Maximize Manufacturing Profits. IEEE Trans. Syst. Man Cybern. Syst. Michael P. Brundage, Qing Chang, Yang Li, Jorge Arinez, Guoxian Xiao
2016	J	`jnl`	Sustainable Manufacturing Performance Indicators for a Serial Production Line. IEEE Trans Autom. Sci. Eng. Michael P. Brundage, Qing Chang, Yang Li, Jorge Arinez, Guoxian Xiao
2015	J	`jnl`	Data-Driven Analysis of Downtime Impacts in Parallel Production Systems. IEEE Trans Autom. Sci. Eng. Yang Li, Qing Chang, Guoxian Xiao, Jorge Arinez
2015	J	`jnl`	Market Demand Oriented Data-Driven Modeling for Dynamic Manufacturing System Control. IEEE Trans. Syst. Man Cybern. Syst. Yang Li, Qing Chang, Michael P. Brundage, Stephan R. Biller, Jorge Arinez, Guoxian Xiao
2014	J	`jnl`	Energy Efficiency Management of an Integrated Serial Production Line and HVAC System. IEEE Trans Autom. Sci. Eng. Michael P. Brundage, Qing Chang, Yang Li, Guoxian Xiao, Jorge Arinez
2014	—	`conf`	Utilizing energy opportunity windows and energy profit bottlenecks to reduce energy consumption per part for a serial production line. CASE Michael P. Brundage, Qing Chang, Yang Li, Jorge Arinez, Guoxian Xiao
2013	—	`conf`	Energy efficiency management of an integrated serial production line and HVAC system. CASE Michael Brundage, Qing Chang, Yang Li, Guoxian Xiao, Jorge Arinez

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.