Daniel F. Leite

52 papers B 17C 1Misc 1Journal 24Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Evolving granular fuzzy control: Overview, case study on the chaotic Hénon map, and research outlook. Appl. Soft Comput. Daniel F. Leite, Reinaldo M. Palhares, Igor Skrjanc, Fernando A. C. Gomide
2025	J	`jnl`	From Model-Based and Adaptive Control to Evolving Fuzzy Control. CoRR Daniel F. Leite, Igor Skrjanc, Fernando A. C. Gomide
2024	—	`conf`	EGNN-C+: Interpretable Evolving Granular Neural Network and Application in Classification of Weakly-Supervised EEG Data Streams. EAIS Daniel F. Leite, Alisson Silva, Gabriella Casalino, Arnab Sharma, Danielle Fortunato, Axel-Cyrille Ngonga Ngomo
2024	—	`conf`	Interpretability Index Based on Balanced Volumes for Transparent Models and Agnostic Explainers. FUZZ Daniel F. Leite, Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo
2024	—	`conf`	Trading-Off Interpretability and Accuracy in Medical Applications: A Study Toward Optimal Explainability of Hoeffding Trees. FUZZ Arnab Sharma, Daniel F. Leite, Caglar Demir, Axel-Cyrille Ngonga Ngomo
2023	Misc	`conf`	Data Driven Fuzzy and Neural Dynamic Systems Modeling. ICMLC Daniel F. Leite, Fernando A. C. Gomide
2023	J	`jnl`	Interval incremental learning of interval data streams and application to vehicle tracking. Inf. Sci. Daniel F. Leite, Igor Skrjanc, Saso Blazic, Andrej Zdesar, Fernando A. C. Gomide
2022	B	`conf`	Data Driven Fuzzy Modeling Using Level Sets. FUZZ-IEEE Daniel F. Leite, Fernando A. C. Gomide, Ronald R. Yager
2022	B	`conf`	Explainable Log Parsing and Online Interval Granular Classification from Streams of Words. FUZZ-IEEE Leticia Decker, Daniel F. Leite, Daniele Bonacorsi
2022	—	`conf`	Fuzzy Linguistic Summaries for Explaining Online Semi-Supervised Learning. IS Katarzyna Kaczmarek-Majer, Gabriella Casalino, Giovanna Castellano, Daniel F. Leite, Olgierd Hryniewicz
2022	J	`jnl`	Unsupervised Learning and Online Anomaly Detection: An On-Condition Log-Based Maintenance System. Int. J. Embed. Real Time Commun. Syst. Leticia Decker, Daniel F. Leite, Francesco Minarini, Simone Rossi Tisbeni, Daniele Bonacorsi
2021	—	`conf`	Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games. LA-CCI Daniel F. Leite, Volnei Frigeri Jr., Rodrigo Medeiros
2021	J	`jnl`	Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games. CoRR Daniel F. Leite, Volnei Frigeri Jr., Rodrigo Medeiros
2021	J	`jnl`	Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model. CoRR Daniel F. Leite, Pedro Henrique Silva Coutinho, Iury Bessa, Murilo C. O. Camargos Filho, Luiz A. Q. Cordovil Júnior, Reinaldo M. Palhares
2021	J	`jnl`	Nonlinear modeling and robust LMI fuzzy control of overhead crane systems. J. Frankl. Inst. Charles Aguiar, Daniel F. Leite, Daniel Pereira, Goran Andonovski, Igor Skrjanc
2020	J	`jnl`	An overview on evolving systems and learning from stream data. Evol. Syst. Daniel F. Leite, Igor Skrjanc, Fernando A. C. Gomide
2020	—	`conf`	Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers. EAIS Leticia Decker, Daniel F. Leite, Fabio Viola, Daniele Bonacorsi
2020	J	`jnl`	Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers. CoRR Leticia Decker, Daniel F. Leite, Fabio Viola, Daniele Bonacorsi
2020	B	`conf`	EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams - With Application to Power Quality Disturbance Detection and Classification. FUZZ-IEEE Daniel F. Leite, Leticia Decker, Marcio Santana, Paulo Vitor de Campos Souza
2020	J	`jnl`	EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams - With Application to Power Quality Disturbance Detection and Classification. CoRR Daniel F. Leite, Leticia Decker, Marcio Santana, Paulo Vitor de Campos Souza
2020	J	`jnl`	Evolving neuro-fuzzy network for real-time high impedance fault detection and classification. Neural Comput. Appl. Sergio Silva, Pyramo Costa, Marcio Santana, Daniel F. Leite
2020	J	`jnl`	Fault detection in smart grids with time-varying distributed generation using wavelet energy and evolving neural networks. Evol. Syst. Fabricio P. Lucas, Pyramo Costa, Rose M. S. Batalha, Daniel F. Leite, Igor Skrjanc
2020	J	`jnl`	Incremental Missing-Data Imputation for Evolving Fuzzy Granular Prediction. IEEE Trans. Fuzzy Syst. Cristiano Garcia, Daniel F. Leite, Igor Skrjanc
2020	J	`jnl`	Optimal Rule-Based Granular Systems From Data Streams. IEEE Trans. Fuzzy Syst. Daniel F. Leite, Goran Andonovski, Igor Skrjanc, Fernando A. C. Gomide
2020	B	`conf`	Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach. FUZZ-IEEE Leticia Decker, Daniel F. Leite, Luca Giommi, Daniele Bonacorsi
2020	J	`jnl`	Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach. CoRR Leticia Decker, Daniel F. Leite, Luca Giommi, Daniele Bonacorsi
2020	—	`conf`	Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering. EAIS Charles Aguiar, Daniel F. Leite
2020	J	`jnl`	Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering. CoRR Charles Aguiar, Daniel F. Leite
2019	J	`jnl`	Ensemble of evolving optimal granular experts, OWA aggregation, and time series prediction. Inf. Sci. Daniel F. Leite, Igor Skrjanc
2019	J	`jnl`	Evolvable fuzzy systems from data streams with missing values: With application to temporal pattern recognition and cryptocurrency prediction. Pattern Recognit. Lett. Cristiano Garcia, Ahmed Esmin, Daniel F. Leite, Igor Skrjanc
2019	J	`jnl`	Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A Survey. Inf. Sci. Igor Skrjanc, José Antonio Iglesias, Araceli Sanchis, Daniel F. Leite, Edwin Lughofer, Fernando A. C. Gomide
2019	B	`conf`	Multiobjective Optimization of Fully Autonomous Evolving Fuzzy Granular Models. FUZZ-IEEE Daniel F. Leite, Fernando A. C. Gomide, Igor Skrjanc
2019	B	`conf`	Nonlinear Fuzzy State-Space Modeling and LMI Fuzzy Control of Overhead Cranes. FUZZ-IEEE Daniel F. Leite, Charles Aguiar, Daniel Pereira, Gustavo Souza, Igor Skrjanc
2018	J	`jnl`	Ensemble of evolving data clouds and fuzzy models for weather time series prediction. Appl. Soft Comput. Eduardo A. Soares, Pyramo Costa, Bruno Costa, Daniel F. Leite
2018	J	`jnl`	Fuzzy clustering and fuzzy validity measures for knowledge discovery and decision making in agricultural engineering. Comput. Electron. Agric. Vania C. Mota, Flavio A. Damasceno, Daniel F. Leite
2018	B	`conf`	High Impedance Fault Detection in Time-Varying Distributed Generation Systems Using Adaptive Neural Networks. IJCNN Fabricio P. Lucas, Pyramo Costa, Rose M. S. Batalha, Daniel F. Leite
2018	B	`conf`	Incremental Gaussian Granular Fuzzy Modeling Applied to Hurricane Track Forecasting. FUZZ-IEEE Eduardo A. Soares, Heloisa A. Camargo, Suzana J. Camargo, Daniel F. Leite
2017	B	`conf`	Cloud-based evolving intelligent method for weather time series prediction. FUZZ-IEEE Eduardo A. Soares, Vania C. Mota, Ricardo Poucas, Daniel F. Leite
2017	B	`conf`	Fuzzy clustering methods applied to the evaluation of compost bedded pack barns. FUZZ-IEEE Vania C. Mota, Flavio A. Damasceno, Eduardo A. Soares, Daniel F. Leite
2016	B	`conf`	Fuzzy Granular Neural Network for incremental modeling of nonlinear chaotic systems. FUZZ-IEEE Daniel F. Leite, Marcio Santana, Ana Borges, Fernando A. C. Gomide
2015	J	`jnl`	Evolving Granular Fuzzy Model-Based Control of Nonlinear Dynamic Systems. IEEE Trans. Fuzzy Syst. Daniel F. Leite, Reinaldo M. Palhares, Víctor C. S. Campos, Fernando A. C. Gomide
2015	B	`conf`	Evolving ensemble of fuzzy models for multivariate time series prediction. FUZZ-IEEE Lourenco Bueno, Pyramo Costa, Israel Mendes, Enderson Cruz, Daniel F. Leite
2015	—	`ch.`	Incremental Granular Fuzzy Modeling Using Imprecise Data Streams. Fifty Years of Fuzzy Logic and its Applications Daniel F. Leite, Fernando A. C. Gomide
2013	J	`jnl`	Evolving granular neural networks from fuzzy data streams. Neural Networks Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
2012	—	`ch.`	Evolving Linguistic Fuzzy Models from Data Streams. Combining Experimentation and Theory Daniel F. Leite, Fernando A. C. Gomide
2012	J	`jnl`	Evolving fuzzy granular modeling from nonstationary fuzzy data streams. Evol. Syst. Daniel F. Leite, Rosangela Ballini, Pyramo Costa Jr., Fernando A. C. Gomide
2012	B	`conf`	Evolving fuzzy linear regression tree approach for forecasting sales volume of petroleum products. FUZZ-IEEE André Paim Lemos, Daniel F. Leite, Leandro Maciel, Rosangela Ballini, Walmir M. Caminhas, Fernando A. C. Gomide
2012	B	`conf`	Evolving granular neural network for fuzzy time series forecasting. IJCNN Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
2011	B	`conf`	Fuzzy granular evolving modeling for time series prediction. FUZZ-IEEE Daniel F. Leite, Fernando A. C. Gomide, Rosangela Ballini, Pyramo Costa Jr.
2010	B	`conf`	Evolving granular neural network for semi-supervised data stream classification. IJCNN Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
2010	C	`conf`	Granular Approach for Evolving System Modeling. IPMU Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
2009	B	`conf`	Evolving granular classification neural networks. IJCNN Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide

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.