Pasquale Franciosa

15 papers B 1C 2Journal 9Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Generative and Predictive AI for digital twin systems in manufacturing. Frontiers Artif. Intell. Dan Dai, Baixiang Zhao, Zhiwen Yu, Pasquale Franciosa, Dariusz Ceglarek
2024	B	`conf`	Adaptive Domain-Enhanced Transfer Learning for Welding Defect Classification. SMC Dan Dai, Anand Mohan, Pasquale Franciosa, Tong Zhang, C. L. Philip Chen, Dariusz Ceglarek
2023	J	`jnl`	Object Shape Error Modelling and Simulation During Early Design Phase by Morphing Gaussian Random Fields. Comput. Aided Des. Manoj Babu, Pasquale Franciosa, Prashant Shekhar, Dariusz Ceglarek
2021	J	`jnl`	Building a Scalable and Interpretable Bayesian Deep Learning Framework for Quality Control of Free Form Surfaces. IEEE Access Sumit Sinha, Pasquale Franciosa, Dariusz Ceglarek
2021	J	`jnl`	Early Stage Variation Simulation and Visualization of Compliant Part Based on Parametric Space Envelope. IEEE Trans Autom. Sci. Eng. Chen Luo, Pasquale Franciosa, Darek Ceglarek, Zhonghua Ni, Zhijie Mo
2021	C	`conf`	Object Shape Error Correction using Deep Reinforcement Learning for Multi-Station Assembly Systems. INDIN Sumit Sinha, Pasquale Franciosa, Dariusz Ceglarek
2021	J	`jnl`	Object Shape Error Response Using Bayesian 3-D Convolutional Neural Networks for Assembly Systems With Compliant Parts. IEEE Trans. Ind. Informatics Sumit Sinha, Pasquale Franciosa, Dariusz Ceglarek
2020	J	`jnl`	Coverage path planning with targetted viewpoint sampling for robotic free-form surface inspection. Robotics Comput. Integr. Manuf. Emile Glorieux, Pasquale Franciosa, Dariusz Ceglarek
2020	C	`conf`	Object Shape Error Response using Bayesian 3D Convolutional Neural Networks for Assembly Systems with Compliant Parts. INDIN Sumit Sinha, Pasquale Franciosa, Dariusz Ceglarek
2020	J	`jnl`	Shape error modelling and simulation of 3D free-form surfaces during early design stage by morphing Gaussian Random Fields. CoRR Manoj Babu, Pasquale Franciosa, Darek Ceglarek
2019	—	`conf`	A Generalised Multi-Attribute Task Sequencing Approach for Robotics Optical Inspection Systems. MetroInd4.0&IoT Ferdinando Vitolo, Pasquale Franciosa, Darek Ceglarek, Stanislao Patalano, Massimiliano De Martino
2019	—	`conf`	Design and development of jigless assembly process: the case of complex aeronautical systems. MetroInd4.0&IoT Rocco Mozzillo, Paola Iaccarino, Ferdinando Vitolo, Pasquale Franciosa
2018	J	`jnl`	A Novel Geometric Tolerance Modeling Inspired by Parametric Space Envelope. IEEE Trans Autom. Sci. Eng. Chen Luo, Pasquale Franciosa, Darek Ceglarek, Zhonghua Ni, Fang Jia
2017	—	`conf`	Non-reproducible alignment and fitting algorithm effects on Laser Radar measurement. I2MTC Ercihan Kiraci, Pasquale Franciosa, Jason M. Warnett, Mark A. Williams
2008	J	`jnl`	Statistical variation analysis of multi-station compliant assemblies based on sensitivity matrix. Int. J. Comput. Appl. Technol. Salvatore Gerbino, Stanislao Patalano, Pasquale Franciosa

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.