Emanuele Zangrando

13 papers A* 5B 1Journal 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Neural-HSS: Hierarchical Semi-Separable Neural PDE Solver. CoRR Pietro Sittoni, Emanuele Zangrando, Angelo A. Casulli, Nicola Guglielmi, Francesco Tudisco
2025	A*	`conf`	GeoLoRA: Geometric integration for parameter efficient fine-tuning. ICLR Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco, Jonas Kusch
2025	A*	`conf`	dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation. ICLR Emanuele Zangrando, Sara Venturini, Francesco Rinaldi, Francesco Tudisco
2024	J	`jnl`	GeoLoRA: Geometric integration for parameter efficient fine-tuning. CoRR Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco, Jonas Kusch
2024	A*	`conf`	Geometry-aware training of factorized layers in tensor Tucker format. NeurIPS Emanuele Zangrando, Steffen Schotthöfer, Gianluca Ceruti, Jonas Kusch, Francesco Tudisco
2024	J	`jnl`	Low-Rank Adversarial PGD Attack. CoRR Dayana Savostianova, Emanuele Zangrando, Francesco Tudisco
2024	J	`jnl`	Neural Rank Collapse: Weight Decay and Small Within-Class Variability Yield Low-Rank Bias. CoRR Emanuele Zangrando, Piero Deidda, Simone Brugiapaglia, Nicola Guglielmi, Francesco Tudisco
2023	B	`conf`	HIJACK: Learning-based Strategies for Sound Classification Robustness to Adversarial Noise. SMARTCOMP Derek Sweet, Emanuele Zangrando, Francesca Meneghello
2023	J	`jnl`	Rank-adaptive spectral pruning of convolutional layers during training. CoRR Emanuele Zangrando, Steffen Schotthöfer, Gianluca Ceruti, Jonas Kusch, Francesco Tudisco
2023	A*	`conf`	Robust low-rank training via approximate orthonormal constraints. NeurIPS Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco
2023	J	`jnl`	Robust low-rank training via approximate orthonormal constraints. CoRR Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco
2022	A*	`conf`	Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations. NeurIPS Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco
2022	J	`jnl`	Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations. CoRR Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco

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.