Federico Giannini

13 papers B 3Journal 8Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Practical Guide to Streaming Continual Learning.
CoRR
Andrea Cossu, Federico Giannini, Giacomo Ziffer, Alessio Bernardo, Alexander Gepperth, Emanuele Della Valle, Barbara Hammer, Davide Bacciu
2026 J jnl
A practical guide to streaming continual learning.
Neurocomputing
Andrea Cossu, Federico Giannini, Giacomo Ziffer, Alessio Bernardo, Alexander Gepperth, Emanuele Della Valle, Barbara Hammer, Davide Bacciu
2026 J jnl
Don't Look Back in Anger: MAGIC Net for Streaming Continual Learning with Temporal Dependence.
CoRR
Federico Giannini, Sandro D'andrea, Emanuele Della Valle
2026 J jnl
MAcPNN: Mutual Assisted Learning on Data Streams with Temporal Dependence.
CoRR
Federico Giannini, Emanuele Della Valle
2026 J jnl
Streaming Continual Learning for Unified Adaptive Intelligence in Dynamic Environments.
CoRR
Federico Giannini, Giacomo Ziffer, Andrea Cossu, Vincenzo Lomonaco
2026 J jnl
cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time Series.
CoRR
Federico Giannini, Giacomo Ziffer, Emanuele Della Valle
2025 B conf
Don't Look Back in Anger: MAGIC Net for Streaming Continual Learning with Temporal Dependence.
IEEE Big Data
Federico Giannini, Sandro D'andrea, Emanuele Della Valle
2024 — conf
Addressing Temporal Dependence, Concept Drifts, and Forgetting in Data Streams.
DELTA
Federico Giannini, Emanuele Della Valle
2024 J jnl
Grounding Stream Reasoning Research.
TGDK
Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, Giacomo Ziffer
2024 B conf
MAcPNN: Mutual Assisted Learning on Data Streams with Temporal Dependence.
IEEE Big Data
Federico Giannini, Emanuele Della Valle
2024 J jnl
Streaming Continual Learning for Unified Adaptive Intelligence in Dynamic Environments.
IEEE Intell. Syst.
Federico Giannini, Giacomo Ziffer, Andrea Cossu, Vincenzo Lomonaco
2024 B conf
Tenet: Benchmarking Data Stream Classifiers in Presence of Temporal Dependence.
IEEE Big Data
Giacomo Ziffer, Federico Giannini, Emanuele Della Valle
2023 — conf
cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time Series.
PAKDD (4)
Federico Giannini, Giacomo Ziffer, Emanuele Della Valle

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.