Rafid Mostafiz

13 papers C 1Journal 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ReDAG-RT: Global Rate-Priority Scheduling for Real-Time Multi-DAG Execution in ROS 2. CoRR Md. Mehedi Hasan, Rafid Mostafiz, Bikash Kumar Paul, Md. Abir Hossain, Ziaur Rahman
2025	J	`jnl`	CLIN-LLM: A Safety-Constrained Hybrid Framework for Clinical Diagnosis and Treatment Generation. CoRR Md. Mehedi Hasan, Rafid Mostafiz, Md. Abir Hossain, Bikash Kumar Paul
2025	J	`jnl`	Dehazing using Generative Adversarial Network - A Review. SN Comput. Sci. Amina Khatun, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin, Md. Abdul Hadi
2025	J	`jnl`	Sentra-Guard: A Multilingual Human-AI Framework for Real-Time Defense Against Adversarial LLM Jailbreaks. CoRR Md. Mehedi Hasan, Ziaur Rahman, Rafid Mostafiz, Md. Abir Hossain
2024	J	`jnl`	XEMLPD: an explainable ensemble machine learning approach for Parkinson disease diagnosis with optimized features. Int. J. Speech Technol. Fahmida Khanom, Shuvo Biswas, Mohammad Shorif Uddin, Rafid Mostafiz
2023	J	`jnl`	MultiResEdge: A deep learning-based edge detection approach. Intell. Syst. Appl. Kanija Muntarina, Rafid Mostafiz, Fahmida Khanom, Sumaita Binte Shorif, Mohammad Shorif Uddin
2022	J	`jnl`	Automatic Brain Tumor Detection From MRI Using Curvelet Transform and Neural Features. Int. J. Ambient Comput. Intell. Rafid Mostafiz, Mohammad Shorif Uddin, Iffat Jabin, Muhammad Minoar Hossain, Mohammad Motiur Rahman
2022	J	`jnl`	COVID-19 Along with Other Chest Infection Diagnoses Using Faster R-CNN and Generative Adversarial Network. ACM Trans. Spatial Algorithms Syst. Rafid Mostafiz, Mohammad Shorif Uddin, Khandaker Mohammad Mohi Uddin, Mohammad Motiur Rahman
2022	J	`jnl`	Covid-19 detection in chest X-ray through random forest classifier using a hybridization of deep CNN and DWT optimized features. J. King Saud Univ. Comput. Inf. Sci. Rafid Mostafiz, Mohammad Shorif Uddin, Nur-A-Alam, Md. Mahfuz Reza, Mohammad Motiur Rahman
2021	J	`jnl`	MRI-based brain tumor detection using the fusion of histogram oriented gradients and neural features. Evol. Intell. Rafid Mostafiz, Mohammad Shorif Uddin, Nur-A-Alam, Md. Mahmodul Hasan, Mohammad Motiur Rahman
2020	J	`jnl`	An intelligent system for gastrointestinal polyp detection in endoscopic video using fusion of bidimensional empirical mode decomposition and convolutional neural network features. Int. J. Imaging Syst. Technol. Rafid Mostafiz, Mosaddik Hasan, Imran Hossain, Mohammad Motiur Rahman
2020	J	`jnl`	Focal Liver Lesion Detection in Ultrasound Image Using Deep Feature Fusions and Super Resolution. Mach. Learn. Knowl. Extr. Rafid Mostafiz, Mohammad Motiur Rahman, A. K. M. Kamrul Islam, Saeid Belkasim
2018	C	`conf`	Computer-Aided Speckle Noise Analysis in Ultrasound Images Through Fusion of Convolutional Neural Network and Wavelet Transform with Linear Discriminate Analysis. IJCCI Rafid Mostafiz, Md. Mezbahul Islam, Md. Motiur Rahman

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.