Oleksander Barmak

14 papers C 1Journal 4Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Autonomous Identification of Distinctive Landmarks from Earth Surface Images. CMIS Zakhar Ostrovskyi, Oleksander Barmak, Iurii Krak
2025	—	`conf`	Detection of military targets from images using deep learning models 15-27. IntelITSIS Dmytro Borovyk, Oleksander Barmak, Volodymyr Lytvynenko
2025	—	`conf`	Hierarchical neural network model for identifying similar objects in drone images. ExplAI Dmytro Borovyk, Oleksander Barmak, Pawel Komada, Sergii Babichev
2025	—	`ed.`	Proceedings of the 1st Workshop on Advanced AI in Explainability and Ethics for the Sustainable Development Goals (ExplAI-2025), Khmelnytskyi, Ukraine, November 7, 2025. ExplAI Tetiana Hovorushchenko, Oleksander Barmak, Abdel-Badeeh M. Salem, Pavlo Radiuk
2025	J	`jnl`	Unsupervised Knowledge Extraction of Distinctive Landmarks from Earth Imagery Using Deep Feature Outliers for Robust UAV Geo-Localization. Mach. Learn. Knowl. Extr. Zakhar Ostrovskyi, Oleksander Barmak, Pavlo Radiuk, Iurii Krak
2024	—	`conf`	An Approach to Model Network Dynamics of a Decentralized Supply Chain Network Using Optimal Predictive Control. UkrPROG Vladyslav A. Kuznetsov, Iurii Krak, Oleksander Barmak, Hrygorii Kudin, Anatolii Kulias, Rostyslav Trokhymchuk
2024	—	`conf`	Explainable Artificial Intelligence: Transitioning DL Model Decisions to User-Understandable Features in Healthcare. ProfIT AI Pavlo Radiuk, Oleksander Barmak, Eduard Manziuk, Iurii Krak
2024	J	`jnl`	Integration of Contextual Descriptors in Ontology Alignment for Enrichment of Semantic Correspondence. CoRR Eduard Manziuk, Oleksander Barmak, Pavlo Radiuk, Vladislav A. Kuznetsov, Iurii Krak, Sergiy Yakovlev
2024	J	`jnl`	Multi-Stage Segmentation and Cascade Classification Methods for Improving Cardiac MRI Analysis. CoRR Vitalii Slobodzian, Pavlo Radiuk, Oleksander Barmak, Iurii Krak
2024	—	`conf`	Multi-stage Segmentation and Cascade Classification Methods for Improving Cardiac MRI Analysis. IT&I Vitalii Slobodzian, Pavlo Radiuk, Oleksander Barmak, Iurii Krak
2024	—	`conf`	Representation of Trustworthiness Components in AI Systems: A Formalized Approach Considering Interconnections and Overlap. ProfIT AI Eduard Manziuk, Oleksander Barmak, Pavlo Radiuk, Vladislav A. Kuznetsov, Iurii Krak
2024	J	`jnl`	Toward explainable deep learning in healthcare through transition matrix and user-friendly features. Frontiers Artif. Intell. Oleksander Barmak, Iurii Krak, Sergiy Yakovlev, Eduard Manziuk, Pavlo Radiuk, Vladislav A. Kuznetsov
2022	C	`conf`	Human-in-the-Loop Approach Based on MRI and ECG for Healthcare Diagnosis. IDDM Pavlo Radiuk, Oleksii Kovalchuk, Vitalii Slobodzian, Eduard Manziuk, Oleksander Barmak, Iurii Krak
2022	—	`conf`	Visual Analytics-Based Method for Sentiment Analysis of COVID-19 Ukrainian Tweets. ISDMCI Oleksii Kovalchuk, Vitalii Slobodzian, Olena Sobko, Maryna Molchanova, Olexander Mazurets, Oleksander Barmak, Iurii Krak, Nataliia Savina

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.