Paul Almasan - RankMe

33 papers B 2C 1Journal 25Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Data-Driven Deployment of Reconfigurable Intelligent Surfaces in Cellular Networks. IEEE J. Sel. Areas Commun. Sina Beyraghi, Javad Shabanpour, Giovanni Geraci, Paul Almasan, Angel Lozano
2026	J	`jnl`	Direct-to-Device Connectivity for Integrated Communication, Navigation and Surveillance. CoRR Muhammad Asad Ullah, Davi Brilhante, Luís Eduardo Partichelli Potrich, José Suárez-Varela, Paul Almasan, Charles Cleary, Vadim Kramar
2025	J	`jnl`	Data-Driven Deployment of Reconfigurable Intelligent Surfaces in Cellular Networks. CoRR Sina Beyraghi, Javad Shabanpour, Giovanni Geraci, Paul Almasan, Angel Lozano
2025	J	`jnl`	Radio Propagation Modelling: To Differentiate or To Deep Learn, That Is The Question. CoRR Stefanos Bakirtzis, Paul Almasan, José Suárez-Varela, Gabriel O. Ferreira, Michail Kalntis, André Felipe Zanella, Ian J. Wassell, Andra Lutu
2025	J	`jnl`	Site-Specific RIS Deployment in Cellular Networks via Calibrated Ray Tracing. CoRR Sina Beyraghi, Javad Shabanpour, Giovanni Geraci, Paul Almasan, Angel Lozano
2024	—	`—`	Leveraging graph neural networks for optimization and traffic compression in network digital twins Paul Almasan
2023	—	`conf`	Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks. GNNet@CoNEXT Paul Almasan, Krzysztof Rusek, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros
2023	J	`jnl`	Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks. CoRR Paul Almasan, Krzysztof Rusek, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros
2023	—	`conf`	Enhancing 5G Radio Planning with Graph Representations and Deep Learning. 5G-MeMZ@SIGCOMM Paul Almasan, José Suárez-Varela, Andra Lutu, Albert Cabellos-Aparicio, Pere Barlet-Ros
2023	J	`jnl`	Enhancing 5G Radio Planning with Graph Representations and Deep Learning. CoRR Paul Almasan, José Suárez-Varela, Andra Lutu, Albert Cabellos-Aparicio, Pere Barlet-Ros
2023	J	`jnl`	Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities. IEEE Netw. José Suárez-Varela, Paul Almasan, Miquel Ferriol-Galmés, Krzysztof Rusek, Fabien Geyer, Xiangle Cheng, Xiang Shi, Shihan Xiao, Franco Scarselli, Albert Cabellos-Aparicio, Pere Barlet-Ros
2023	J	`jnl`	Leveraging Spatial and Temporal Correlations for Network Traffic Compression. CoRR Paul Almasan, Krzysztof Rusek, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros
2022	B	`conf`	Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies. NOMS Carlos Güemes-Palau, Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio
2022	J	`jnl`	Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies. CoRR Carlos Güemes-Palau, Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio
2022	J	`jnl`	Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case. Comput. Commun. Paul Almasan, José Suárez-Varela, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio
2022	J	`jnl`	Digital Twin Network: Opportunities and Challenges. CoRR Paul Almasan, Miquel Ferriol-Galmés, Jordi Paillisse, José Suárez-Varela, Diego Perino, Diego R. López, Antonio Agustin Pastor Perales, Paul Harvey, Laurent Ciavaglia, Leon Wong, Vishnu Ram, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros
2022	J	`jnl`	ENERO: Efficient real-time WAN routing optimization with Deep Reinforcement Learning. Comput. Networks Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio
2022	B	`conf`	Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing. CNSM Krzysztof Rusek, Paul Almasan, José Suárez-Varela, Piotr Cholda, Pere Barlet-Ros, Albert Cabellos-Aparicio
2022	J	`jnl`	Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing. CoRR Krzysztof Rusek, Paul Almasan, José Suárez-Varela, Piotr Cholda, Pere Barlet-Ros, Albert Cabellos-Aparicio
2022	J	`jnl`	Network Digital Twin: Context, Enabling Technologies and Opportunities. CoRR Paul Almasan, Miquel Ferriol-Galmés, Jordi Paillisse, José Suárez-Varela, Diego Perino, Diego R. López, Antonio Agustin Pastor Perales, Paul Harvey, Laurent Ciavaglia, Leon Wong, Vishnu Ram, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros
2022	J	`jnl`	Network Digital Twin: Context, Enabling Technologies, and Opportunities. IEEE Commun. Mag. Paul Almasan, Miquel Ferriol-Galmés, Jordi Paillisse, José Suárez-Varela, Diego Perino, Diego R. López, Antonio Agustin Pastor Perales, Paul Harvey, Laurent Ciavaglia, Leon Wong, Vishnu Ram, Shihan Xiao, Xiang Shi, Xiangle Cheng, Albert Cabellos-Aparicio, Pere Barlet-Ros
2021	J	`jnl`	ENERO: Efficient Real-Time Routing Optimization. CoRR Paul Almasan, Shihan Xiao, Xiangle Cheng, Xiang Shi, Pere Barlet-Ros, Albert Cabellos-Aparicio
2021	J	`jnl`	Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities. CoRR José Suárez-Varela, Paul Almasan, Miquel Ferriol-Galmés, Krzysztof Rusek, Fabien Geyer, Xiangle Cheng, Xiang Shi, Shihan Xiao, Franco Scarselli, Albert Cabellos-Aparicio, Pere Barlet-Ros
2021	J	`jnl`	The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networks. CoRR José Suárez-Varela, Miquel Ferriol-Galmés, Albert López, Paul Almasan, Guillermo Bernárdez, David Pujol-Perich, Krzysztof Rusek, Loïck Bonniot, Christoph Neumann, François Schnitzler, François Taïani, Martin Happ, Christian Maier, Jia Lei Du, Matthias Herlich, Peter Dorfinger, Nick Vincent Hainke, Stefan Venz, Johannes Wegener, Henrike Wissing, Bo Wu, Shihan Xiao, Pere Barlet-Ros, Albert Cabellos-Aparicio
2021	J	`jnl`	The graph neural networking challenge: a worldwide competition for education in AI/ML for networks. Comput. Commun. Rev. José Suárez-Varela, Miquel Ferriol-Galmés, Albert López, Paul Almasan, Guillermo Bernárdez, David Pujol-Perich, Krzysztof Rusek, Loïck Bonniot, Christoph Neumann, François Schnitzler, François Taïani, Martin Happ, Christian Maier, Jia Lei Du, Matthias Herlich, Peter Dorfinger, Nick Vincent Hainke, Stefan Venz, Johannes Wegener, Henrike Wissing, Bo Wu, Shihan Xiao, Pere Barlet-Ros, Albert Cabellos-Aparicio
2021	C	`conf`	Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges. HPSR Paul Almasan, José Suárez-Varela, Bo Wu, Shihan Xiao, Pere Barlet-Ros, Albert Cabellos-Aparicio
2021	J	`jnl`	Towards Real-Time Routing Optimization with Deep Reinforcement Learning: Open Challenges. CoRR Paul Almasan, José Suárez-Varela, Bo Wu, Shihan Xiao, Pere Barlet-Ros, Albert Cabellos-Aparicio
2020	J	`jnl`	RouteNet: Leveraging Graph Neural Networks for Network Modeling and Optimization in SDN. IEEE J. Sel. Areas Commun. Krzysztof Rusek, José Suárez-Varela, Paul Almasan, Pere Barlet-Ros, Albert Cabellos-Aparicio
2019	—	`conf`	Challenging the generalization capabilities of Graph Neural Networks for network modeling. SIGCOMM Posters and Demos José Suárez-Varela, Sergi Carol-Bosch, Krzysztof Rusek, Paul Almasan, Marta Arias, Pere Barlet-Ros, Albert Cabellos-Aparicio
2019	J	`jnl`	Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case. CoRR Paul Almasan, José Suárez-Varela, Arnau Badia-Sampera, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio
2019	J	`jnl`	RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN. CoRR Krzysztof Rusek, José Suárez-Varela, Paul Almasan, Pere Barlet-Ros, Albert Cabellos-Aparicio
2019	—	`conf`	Towards more realistic network models based on Graph Neural Networks. CoNEXT Companion Arnau Badia-Sampera, José Suárez-Varela, Paul Almasan, Krzysztof Rusek, Pere Barlet-Ros, Albert Cabellos-Aparicio
2018	J	`jnl`	Securing the Control-plane Channel and Cache of Pull-based ID/LOC Protocols. CoRR Paul Almasan, Jordi Paillisse, Alberto Rodríguez-Natal, Pere Barlet-Ros, Florin Coras, Vina Ermagan, Fabio Maino, Albert Cabellos-Aparicio

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.