Facundo Palomino-Quispe

11 papers Misc 1Journal 7Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	A Deformable Convolutional Neural Network with Dual Attention for Multi-Exposure HDR Reconstruction. SIBGRAPI Quefren Leher, Josue Lopez-Cabrejos, Gustavo Ferreti, Lucas Hildelbrano Costa Carvalho, Ana Gabriela Alvarez, Thuanne Paixão, Ana Beatriz Alvarez, Facundo Palomino-Quispe
2025	J	`jnl`	A Low Computational Cost Deep Learning Approach for Localization and Classification of Diseases and Pests in Coffee Leaves. IEEE Access Clécio Elias Silva E. Silva, Jonatan Borges Fragoso, Thuanne Paixão, Ana Beatriz Alvarez, Facundo Palomino-Quispe
2025	J	`jnl`	Adaptive Contrastive Learning in Vision Transformer for Non-Invasive Hemoglobin Estimation From Conjunctival Images. IEEE Access Jose Humberto Fuentes-Beingolea, Facundo Palomino-Quispe
2025	J	`jnl`	Denoising Diffusion Probabilistic Models for Cloud Removal and Land Surface Temperature Retrieval From a Single Sample. IEEE Access Quefren Leher, Emili Silva Bezerra, Thuanne Paixão, Facundo Palomino-Quispe, Ana Beatriz Alvarez
2025	J	`jnl`	Illumination-Robust Conjunctival Image Preprocessing for Accurate Segmentation and Anemia Detection Using Deep Learning. Int. J. Online Biomed. Eng. Jose Humberto Fuentes-Beingolea, Facundo Palomino-Quispe, Julio Cesar Herrera-Levano, Willy Vargas-Mateos, Ruben Florez, Ana Beatriz Alvarez
2024	J	`jnl`	A Real-Time Embedded System for Driver Drowsiness Detection Based on Visual Analysis of the Eyes and Mouth Using Convolutional Neural Network and Mouth Aspect Ratio. Sensors Ruben Florez, Facundo Palomino-Quispe, Ana Beatriz Alvarez, Roger Jesus Coaquira-Castillo, Julio Cesar Herrera-Levano
2024	J	`jnl`	Exploratory Analysis Using Deep Learning for Water-Body Segmentation of Peru's High-Mountain Remote Sensing Images. Sensors William Isaac Perez-Torres, Diego Armando Uman-Flores, Andres Benjamin Quispe-Quispe, Facundo Palomino-Quispe, Emili Silva Bezerra, Quefren Leher, Thuanne Paixão, Ana Beatriz Alvarez
2023	Misc	`conf`	Development of Simplified Lumbar Spine Mechanism Implemented with Tendon-Driven Motion. MMAR Thuanne Paixão, Ana Beatriz Alvarez, Ruben Florez, Facundo Palomino-Quispe, Lucas Angst, Luis Maggi
2023	—	`conf`	Fuzzy Control for Simplified Lumbar Spine Robotic Mechanism Motion. ICNSC Thuanne Paixão, Ana Beatriz Alvarez, Ruben Florez, Facundo Palomino-Quispe
2023	J	`jnl`	Fuzzy Controller Implemented for Movement of a Tendon-Driven 3D Robotic Lumbar Spine Mechanism. Sensors Thuanne Paixão, Ana Beatriz Alvarez, Ruben Florez, Facundo Palomino-Quispe
2023	—	`conf`	Motion Control of a Robotic Lumbar Spine Model. IWBBIO (1) Thuanne Paixão, Ana Beatriz Alvarez, Ruben Florez, Facundo Palomino-Quispe

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.