Eduardo P. de Aguiar

13 papers B 2C 1Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Autonomous data partitioning for type-2 fuzzy set based time series. Evol. Syst. Arthur Caio Vargas Pinto, Larissa C. C. da Silva, Petrônio C. L. Silva, Frederico G. Guimarães, Eduardo P. de Aguiar
2023	—	`conf`	Deep Learning-Based Handover Prediction for 5G and Beyond Networks. ICC João Paulo S. H. Lima, Álvaro Augusto M. de Medeiros, Eduardo P. de Aguiar, Edelberto F. Silva, Vicente A. de Sousa Jr., Marcelo L. Nunes, Alysson L. Reis
2023	J	`jnl`	Multifractal Analysis of the Brazilian Electricity Market. IEEE Access Alessandro L. Castro, André Luís Marques Marcato, Eduardo P. de Aguiar
2023	J	`jnl`	UAV Power Line Tracking Control Based on a Type-2 Fuzzy-PID Approach. Robotics Guilherme A. N. Pussente, Eduardo P. de Aguiar, André L. M. Marcato, Milena F. Pinto
2022	J	`jnl`	Semi-supervised deep rule-based approach for the classification of Wagon Bogie springs condition. Evol. Syst. Carlos M. Viriato Neto, Luca G. Honorio, Eduardo P. de Aguiar
2021	J	`jnl`	A New Model to Distinguish Railhead Defects Based on Set-Membership Type-2 Fuzzy Logic System. Int. J. Fuzzy Syst. Eduardo P. de Aguiar, Thiago E. Fernandes, Fernando M. de A. Nogueira, Daniel Discini Silveira, Marley M. B. R. Vellasco, Moisés Vidal Ribeiro
2021	B	`conf`	Self-Organised Direction Aware Data Partitioning for Type-2 Fuzzy Time Series Prediction. FUZZ-IEEE Arthur Caio Vargas Pinto, Petrônio C. L. Silva, Frederico G. Guimarães, Christian Wagner, Eduardo P. de Aguiar
2019	J	`jnl`	Type-1 and singleton fuzzy logic system trained by a fast scaled conjugate gradient methods for dealing with binary classification problems. Neurocomputing Renan Piazzaroli Finotti Amaral, Moisés Vidal Ribeiro, Eduardo P. de Aguiar
2017	J	`jnl`	An enhanced receiver for an impulsive UWB-based PLC system for low-bit rate applications. Digit. Signal Process. Marlon Lucas Gomes Salmento, Eduardo P. de Aguiar, Ândrei Camponogara, Moisés Vidal Ribeiro
2017	B	`conf`	Computing derivatives in interval type-2 fuzzy logic systems trained by steepest descent method for fault classification in a switch machine. FUZZ-IEEE Eduardo P. de Aguiar, Renan P. F. Amaral, Marley M. B. R. Vellasco, Moisés Vidal Ribeiro
2017	J	`jnl`	Set-Membership Type-1 Fuzzy Logic System Applied to Fault Classification in a Switch Machine. IEEE Trans. Intell. Transp. Syst. Eduardo P. de Aguiar, Fernando M. de A. Nogueira, Marley M. B. R. Vellasco, Moisés Vidal Ribeiro
2016	J	`jnl`	EANN 2014: a fuzzy logic system trained by conjugate gradient methods for fault classification in a switch machine. Neural Comput. Appl. Eduardo P. de Aguiar, Fernando M. de A. Nogueira, Renan P. F. Amaral, Diego F. Fabri, Sérgio C. de A. Rossignoli, José Geraldo Ferreira, Marley M. B. R. Vellasco, Ricardo Tanscheit, Pedro C. G. da S. Vellasco, Moisés Vidal Ribeiro
2014	C	`conf`	Classification of Events in Switch Machines Using Bayes, Fuzzy Logic System and Neural Network. EANN Eduardo P. de Aguiar, Fernando M. de A. Nogueira, Renan P. F. Amaral, Diego F. Fabri, Sérgio C. de A. Rossignoli, José Geraldo Ferreira, Marley M. B. R. Vellasco, Ricardo Tanscheit, Moisés Vidal Ribeiro, Pedro C. G. da S. Vellasco

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.