Daniel Caballero

14 papers C 3Journal 7Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	AI-Based System for Assistance in Minimally Invasive Renal Procedures Using Mixed Reality. First Steps. IbPRIA (2) Emilio Delgado, Daniel Caballero, Lucía Salazar-Carrasco, Ignacio Sánchez-Varo, Jesús León-Regalado, Juan Alberto Sánchez-Margallo, Roberto Rodríguez-Echeverría, Francisco M. Sánchez-Margallo
2025	C	`conf`	CHYMERA: AI-Powered System for Automated and Explainable Quality Assessment of Chest Radiographs. BIBE Lucia Borrego, Christian Mata, Inés Del Val, Daniel Caballero, Lydia Canales, Josep Munuera
2025	J	`jnl`	Optimization of an artificial neural network for predicting stress in robot-assisted laparoscopic surgery based on EDA sensor data. Int. J. Comput. Assist. Radiol. Surg. Daniel Caballero, Manuel J. Pérez-Salazar, Juan Alberto Sánchez-Margallo, Francisco M. Sánchez-Margallo
2024	J	`jnl`	Applying artificial intelligence on EDA sensor data to predict stress on minimally invasive robotic-assisted surgery. Int. J. Comput. Assist. Radiol. Surg. Daniel Caballero, Manuel J. Pérez-Salazar, Juan Alberto Sánchez-Margallo, Francisco M. Sánchez-Margallo
2024	J	`jnl`	Comparative Study of Ergonomics in Conventional and Robotic-Assisted Laparoscopic Surgery. Sensors Manuel J. Pérez-Salazar, Daniel Caballero, Juan Alberto Sánchez-Margallo, Francisco M. Sánchez-Margallo
2021	J	`jnl`	Finding the Largest Volume Parallelepipedon of Arbitrary Orientation in a Solid. IEEE Access Rubén Molano, Daniel Caballero, Pablo García Rodríguez, María Mar Ávila, Juan Pedro Torres, Maria Luisa Durán, José Carlos Sancho, Andrés Caro
2021	J	`jnl`	Optimization of the image acquisition procedure in low-field MRI for non-destructive analysis of loin using predictive models. PeerJ Comput. Sci. Daniel Caballero, Trinidad Pérez-Palacios, Andrés Caro, Mar Ávila, Teresa Antequera
2020	J	`jnl`	Radial textures: a new algorithm to analyze meat quality on MRI. Multim. Tools Appl. Daniel Caballero
2019	J	`jnl`	Magnetic Resonance Imaging, texture analysis and regression techniques to non-destructively predict the quality characteristics of meat pieces. Eng. Appl. Artif. Intell. María Mar Ávila, Maria Luisa Durán, Daniel Caballero, Teresa Antequera, Trinidad Pérez-Palacios, Eva Cernadas, Manuel Fernández Delgado
2019	—	`conf`	Non-destructively Prediction of Quality Parameters of Dry-Cured Iberian Ham by Applying Computer Vision and Low-Field MRI. IbPRIA (1) Juan Pedro Torres, Mar Ávila, Andrés Caro, Trinidad Pérez-Palacios, Daniel Caballero
2018	C	`conf`	Radial Textures: A New Approach to Analyze Meat Quality by Using MRI. CIARP Daniel Caballero, Andrés Caro, José Manuel Amigo, María Mar Ávila, Teresa Antequera, Trinidad Pérez-Palacios
2017	—	`conf`	Development of a New Fractal Algorithm to Predict Quality Traits of MRI Loins. CAIP (1) Daniel Caballero, Andrés Caro, José Manuel Amigo, Anders B. Dahl, Bjarne K. Ersbøll, Trinidad Pérez-Palacios
2015	C	`conf`	Including 3D-textures in a Computer Vision System to Analyze Quality Traits of Loin. ICVS María Mar Ávila, Daniel Caballero, Maria Luisa Durán, Andrés Caro, Trinidad Pérez-Palacios, Teresa Antequera
2013	—	`conf`	A Variability Model for Template Personalization in Mobile Prosumer Environments. AINA Workshops Ramón Alcarria, Tomás Robles, Augusto Morales Dominguez, Sergio Gonzalez-Miranda, Daniel Caballero

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.