Olena Pavliuk

16 papers B 5C 2Misc 4Journal 2Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Federated Learning for Wireless Communication Prediction - The Use Case of Internal Logistic System Based on AGV. IEEE Big Data Ireneusz Smolka, Olena Pavliuk, Rafal Cupek, Jakub Musial
2025	B	`conf`	Iterative Weighted-Voting Approach for Adaptive Time-Series Anomaly Correction in Federated AGV Systems. IEEE Big Data Olena Pavliuk, Myroslav Mishchuk
2024	—	`conf`	A Two-Stage Feature Selection Method for Neural Network Predictive Models for AGV. SMARTINDUSTRY Olena Pavliuk, Myroslav Mishchuk, Mykola Medykovskyy, Rafal Cupek
2024	Misc	`conf`	Approach for Smartwatch-Based Complex Human Activity Recognition in Internal Logistics Systems. CSIT Myroslav Mishchuk, Olena Pavliuk, Mykola Medykovskyy
2024	Misc	`conf`	Modern Methods of Data Preprocessing to Increase the Accuracy of AGV Battery Discharge Forecast. CSIT Olena Pavliuk, Mykola Medykovskyy, Rafal Cupek, Myroslav Mishchuk
2024	B	`conf`	Smartwatch-Based Human Staff Activity Classification: A Use-Case Study in Internal Logistics Systems Utilizing AGVs. IEEE Big Data Olena Pavliuk, Myroslav Mishchuk
2023	Misc	`conf`	An approach towards AGV battery cell voltage prediction using DL and data pre-processing. CSIT Mykola O. Medykovskyy, Rafal Cupek, Olena Pavliuk, Myroslav Mishchuk
2023	J	`jnl`	Machine-learning method for analyzing and predicting the number of hospitalizations of children during the fourth wave of the COVID-19 pandemic in the Lviv region. J. Reliab. Intell. Environ. Olena Pavliuk, Halyna Kolesnyk
2023	B	`conf`	Predicting AGV Battery Cell Voltage Using a Neural Network Approach with Preliminary Data Analysis and Processing. IEEE Big Data Olena Pavliuk, Mykola O. Medykovskyy, Tomasz Steclik
2023	J	`jnl`	Transfer Learning Approach for Human Activity Recognition Based on Continuous Wavelet Transform. Algorithms Olena Pavliuk, Myroslav Mishchuk, Christine Strauss
2022	C	`conf`	A novel Deep-Learning model for Human Activity Recognition based on Continuous Wavelet Transform. IDDM Olena Pavliuk, Myroslav Mishchuk
2022	Misc	`conf`	Analysis of the spread of COVID-19 in Ukraine using Google Trends tools. CSIT Mykola Medykovskyy, Olena Pavliuk, Myroslav Mishchuk
2022	B	`conf`	The forecast of the AGV battery discharging via the machine learning methods. IEEE Big Data Olena Pavliuk, Tomasz Steclik, Piotr Biernacki
2021	—	`conf`	An Investigation of Traffic and Optimization Opportunities of a Passenger Service System in JFK Airport. IT&AS Miloslav Chalupka, Kornelius Fuchs, Raphael Heinfling, Nikola Malesevic, Rory Traut, Olena Pavliuk
2021	C	`conf`	Experimental Evaluation of the Effectiveness of ANN-based Numerical Data Augmentation Methods for Diagnostics Tasks. IDDM Ivan Izonin, Roman Tkachenko, Roman Pidkostelnyi, Olena Pavliuk, Viktor Khavalko, Anatoliy Batyuk
2018	—	`conf`	Use of Machine Learning Technologys for the Electric Consumption Forecast. CSIT (1) Mvkola Medykovskvi, Olena Pavliuk, Roman Sydorenko

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.