Zarina I. Samigulina

15 papers B 2Journal 2Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Bio-Inspired Modified Framework for Advanced Predictive Maintenance. CENTERIS/ProjMAN/HCist Galina A. Samigulina, Zarina I. Samigulina, Daulet Bekeshev
2025	—	`conf`	Data-driven machinery faults detection techniques using Artificial Intelligence in Industry 4.0 concept. ANT/EDI40 Galina A. Samigulina, Zarina I. Samigulina, Daulet Bekeshev, Diana Butakova
2025	B	`conf`	Innovative Intellectual Multi-Agent System for Smart manufacturing. KES Galina A. Samigulina, Zarina I. Samigulina, Daulet Bekeshev, Diana Butakova
2025	—	`conf`	Integrating Neural and Immune Networks: A Bio-Inspired Paradigm for Industrial Diagnostics. ISMSI Galina A. Samigulina, Zarina I. Samigulina, Daulet Dinmukhamedovich Bekeshev
2023	B	`conf`	Development of a risk assessment methodology for intelligent technology of diagnosing industrial equipment for complex oil and gas facilities. KES Galina A. Samigulina, Zarina I. Samigulina
2023	—	`conf`	Development of an Approach for Multicomponent Evaluation of the Efficiency of Modified Algorithms of Artificial Immune Systems. EUSPN/ICTH Galina A. Samigulina, Zarina I. Samigulina
2022	—	`conf`	Biologically Inspired Unified Artificial Immune System for Industrial Equipment Diagnostic. LOD (2) Galina A. Samigulina, Zarina I. Samigulina
2022	—	`conf`	Development of a unified artificial immune system for complex objects control within the framework of the Industry 4.0 concept. CENTERIS/ProjMAN/HCist Galina A. Samigulina, Zarina I. Samigulina
2022	J	`jnl`	Diagnostics of industrial equipment and faults prediction based on modified algorithms of artificial immune systems. J. Intell. Manuf. Galina A. Samigulina, Zarina I. Samigulina
2021	—	`conf`	Development of a Unified Artificial Immune System for Intelligent Technology of Complex Industrial Automation Objects Control in the Oil and Gas Industry. KES-HCIS Galina A. Samigulina, Zarina I. Samigulina
2020	—	`conf`	Design of Technology for Prediction and Control System Based on Artificial Immune Systems and the Multi-agent Platform JADE. KES-AMSTA Galina A. Samigulina, Zarina I. Samigulina
2020	—	`conf`	Machine Learning for Big Data Analysis in Drug Design. LOD (2) Galina A. Samigulina, Zarina I. Samigulina
2019	J	`jnl`	Modified immune network algorithm based on the Random Forest approach for the complex objects control. Artif. Intell. Rev. Galina A. Samigulina, Zarina I. Samigulina
2017	—	`conf`	Immune Network Technology on the Basis of Random Forest Algorithm for Computer-Aided Drug Design. IWBBIO (1) Galina A. Samigulina, Zarina I. Samigulina
2016	—	`conf`	Intellectualization of the Data Processing in the Industrial Automatization on the Basis of Modern Equipment. IntelliSys (1) Galina A. Samigulina, Zarina I. Samigulina

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.