Samuel G. Fadel

20 papers B 1Journal 14Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	VIKING: Deep variational inference with stochastic projections. CoRR Samuel G. Fadel, Hrittik Roy, Nicholas Krämer, Yevgen Zainchkovskyy, Stas Syrota, Alejandro Valverde Mahou, Carl Henrik Ek, Søren Hauberg
2024	J	`jnl`	Explaining the Impact of Training on Vision Models via Activation Clustering. CoRR Ahcène Boubekki, Samuel G. Fadel, Sebastian Mair
2024	J	`jnl`	Leveraging Activations for Superpixel Explanations. CoRR Ahcène Boubekki, Samuel G. Fadel, Sebastian Mair
2024	—	`conf`	Self-supervised Siamese Autoencoders. IDA (1) Friederike Baier, Sebastian Mair, Samuel G. Fadel
2023	J	`jnl`	Self-Supervised Siamese Autoencoders. CoRR Friederike Baier, Sebastian Mair, Samuel G. Fadel
2021	—	`—`	Learning in non-euclidean domains : from graphs to generative modeling = Aprendizado em domínios não-euclidianos : de grafos à modelagem generativa Samuel G. Fadel
2021	—	`conf`	Principled Interpolation in Normalizing Flows. ECML/PKDD (2) Samuel G. Fadel, Sebastian Mair, Ricardo da Silva Torres, Ulf Brefeld
2020	J	`jnl`	Neural relational inference for disaster multimedia retrieval. Multim. Tools Appl. Samuel G. Fadel, Ricardo da Silva Torres
2020	J	`jnl`	Principled Interpolation in Normalizing Flows. CoRR Samuel G. Fadel, Sebastian Mair, Ricardo da Silva Torres, Ulf Brefeld
2018	J	`jnl`	Exploiting ConvNet Diversity for Flooding Identification. IEEE Geosci. Remote. Sens. Lett. Keiller Nogueira, Samuel G. Fadel, Ícaro C. Dourado, Rafael de Oliveira Werneck, Javier A. V. Muñoz, Otávio A. B. Penatti, Rodrigo Tripodi Calumby, Lin Tzy Li, Jefersson A. dos Santos, Ricardo da Silva Torres
2018	B	`conf`	Graph-Based Early-Fusion for Flood Detection. ICIP Rafael de Oliveira Werneck, Ícaro C. Dourado, Samuel G. Fadel, Salvatore Tabbone, Ricardo da Silva Torres
2018	J	`jnl`	Link Prediction in Dynamic Graphs for Recommendation. CoRR Samuel G. Fadel, Ricardo da Silva Torres
2018	J	`jnl`	UPDis: A user-assisted projection technique for distance information. Inf. Vis. Tácito T. A. T. Neves, Samuel G. Fadel, Gladys M. H. Mamani, Francisco M. Fatore, Fernando Vieira Paulovich
2017	—	`conf`	Data-Driven Flood Detection using Neural Networks. MediaEval Keiller Nogueira, Samuel G. Fadel, Ícaro C. Dourado, Rafael de Oliveira Werneck, Javier A. V. Muñoz, Otávio A. B. Penatti, Rodrigo Tripodi Calumby, Lin Li, Jefersson Alex dos Santos, Ricardo da Silva Torres
2017	J	`jnl`	Exploiting ConvNet Diversity for Flooding Identification. CoRR Keiller Nogueira, Samuel G. Fadel, Ícaro C. Dourado, Rafael de Oliveira Werneck, Javier A. V. Muñoz, Otávio A. B. Penatti, Rodrigo Tripodi Calumby, Lin Tzy Li, Jefersson A. dos Santos, Ricardo da Silva Torres
2017	J	`jnl`	Visualizing the Hidden Activity of Artificial Neural Networks. IEEE Trans. Vis. Comput. Graph. Paulo E. Rauber, Samuel G. Fadel, Alexandre X. Falcão, Alexandru C. Telea
2016	—	`conf`	RECOD @ Placing Task of MediaEval 2016: A Ranking Fusion Approach for Geographic-Location Prediction of Multimedia Objects. MediaEval Javier A. V. Muñoz, Lin Tzy Li, Ícaro C. Dourado, Keiller Nogueira, Samuel G. Fadel, Otávio Augusto Bizetto Penatti, Jurandy Almeida, Luís A. M. Pereira, Rodrigo Tripodi Calumby, Jefersson A. dos Santos, Ricardo da Silva Torres
2015	J	`jnl`	Análise Visual utilizando Projeções Multidimensionais. RITA Tácito Trindade de Araújo Tiburtino Neves, Samuel G. Fadel, Danilo Barbosa Coimbra, Fernando Vieira Paulovich
2015	J	`jnl`	LoCH: A neighborhood-based multidimensional projection technique for high-dimensional sparse spaces. Neurocomputing Samuel G. Fadel, Francisco M. Fatore, Felipe S. L. G. Duarte, Fernando Vieira Paulovich
2014	J	`jnl`	Nmap: A Novel Neighborhood Preservation Space-filling Algorithm. IEEE Trans. Vis. Comput. Graph. Felipe S. L. G. Duarte, Fabio Sikansi, Francisco M. Fatore, Samuel G. Fadel, Fernando Vieira Paulovich

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.