Fabrizio Carpi

18 papers B 1Journal 10Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learned Precoding-Oriented CSI Feedback in Multi-Cell Multi-User MIMO Systems. IEEE Trans. Wirel. Commun. Fabrizio Carpi, Sivarama Venkatesan, Jinfeng Du, Harish Viswanathan, Siddharth Garg, Elza Erkip
2025	—	`conf`	AI/ML-Based Asymmetric Modulation Constellations and Pilotless Communications. VTC2025-Spring Caleb K. Lo, Fabrizio Carpi, Joonyoung Cho, Charlie Jianzhong Zhang
2025	J	`jnl`	Learning-Based Compress-and-Forward Schemes for the Relay Channel. IEEE J. Sel. Areas Commun. Ezgi Özyilkan, Fabrizio Carpi, Siddharth Garg, Elza Erkip
2024	—	`conf`	Learned Pulse Shaping Design for PAPR Reduction in DFT-s-OFDM. SPAWC Fabrizio Carpi, Soheil Rostami, Joonyoung Cho, Siddharth Garg, Elza Erkip, Charlie Jianzhong Zhang
2024	J	`jnl`	Learned Pulse Shaping Design for PAPR Reduction in DFT-s-OFDM. CoRR Fabrizio Carpi, Soheil Rostami, Joonyoung Cho, Siddharth Garg, Elza Erkip, Charlie Jianzhong Zhang
2024	J	`jnl`	Learning-Based Compress-and-Forward Schemes for the Relay Channel. CoRR Ezgi Özyilkan, Fabrizio Carpi, Siddharth Garg, Elza Erkip
2024	—	`conf`	Neural Compress-and-Forward for the Relay Channel. SPAWC Ezgi Özyilkan, Fabrizio Carpi, Siddharth Garg, Elza Erkip
2024	J	`jnl`	Neural Compress-and-Forward for the Relay Channel. CoRR Ezgi Özyilkan, Fabrizio Carpi, Siddharth Garg, Elza Erkip
2023	J	`jnl`	Experimental analysis of RSSI-based localization algorithms with NLOS pre-mitigation for IoT applications. Comput. Networks Fabrizio Carpi, Marco Martalò, Luca Davoli, Antonio Cilfone, Yingjie Yu, Yi Wang, Gianluigi Ferrari
2023	—	`conf`	Precoding-oriented Massive MIMO CSI Feedback Design. ICC Fabrizio Carpi, Sivarama Venkatesan, Jinfeng Du, Harish Viswanathan, Siddharth Garg, Elza Erkip
2023	J	`jnl`	Precoding-oriented Massive MIMO CSI Feedback Design. CoRR Fabrizio Carpi, Sivarama Venkatesan, Jinfeng Du, Harish Viswanathan, Siddharth Garg, Elza Erkip
2021	—	`conf`	Single-Shot Compression for Hypothesis Testing. SPAWC Fabrizio Carpi, Siddharth Garg, Elza Erkip
2021	J	`jnl`	Single-Shot Compression for Hypothesis Testing. CoRR Fabrizio Carpi, Siddharth Garg, Elza Erkip
2019	B	`conf`	Learned Belief-Propagation Decoding with Simple Scaling and SNR Adaptation. ISIT Mengke Lian, Fabrizio Carpi, Christian Häger, Henry D. Pfister
2019	J	`jnl`	Learned Belief-Propagation Decoding with Simple Scaling and SNR Adaptation. CoRR Mengke Lian, Fabrizio Carpi, Christian Häger, Henry D. Pfister
2019	—	`conf`	RSSI-based Methods for LOS/NLOS Channel Identification in Indoor Scenarios. ISWCS Fabrizio Carpi, Luca Davoli, Marco Martalò, Antonio Cilfone, Yingjie Yu, Yi Wang, Gianluigi Ferrari
2019	—	`conf`	Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding. Allerton Fabrizio Carpi, Christian Häger, Marco Martalò, Riccardo Raheli, Henry D. Pfister
2019	J	`jnl`	Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding. CoRR Fabrizio Carpi, Christian Häger, Marco Martalò, Riccardo Raheli, Henry D. Pfister

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.