Rabia Musheer Aziz

17 papers Journal 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Novel Technique for Image Captioning Based on Hierarchical Clustering and Deep Learning. SN Comput. Sci. Rizwan Ur Rahman, Pavan Kumar, Aditya Mohan, Rabia Musheer Aziz, Deepak Singh Tomar
2025	J	`jnl`	Feature selection using game Shapley improved grey wolf optimizer for optimizing cancer classification. Knowl. Inf. Syst. Sana Afreen, Ajay Kumar Bhurjee, Rabia Musheer Aziz
2025	J	`jnl`	Improving breast cancer classification with mRMR + SS0 + WSVM: a hybrid approach. Multim. Tools Appl. Abrar Yaqoob, Navneet Kumar Verma, Rabia Musheer Aziz
2024	J	`jnl`	A comprehensive evaluation of Marine predator chaotic algorithm for feature selection of COVID-19. Evol. Syst. Akash Saxena, Siddharth Singh Chouhan, Rabia Musheer Aziz, Vani Agarwal
2024	J	`jnl`	A two-phase cuckoo search based approach for gene selection and deep learning classification of cancer disease using gene expression data with a novel fitness function. Multim. Tools Appl. Amol Avinash Joshi, Rabia Musheer Aziz
2024	J	`jnl`	Cognizable crime rate prediction and analysis under Indian penal code using deep learning with novel optimization approach. Multim. Tools Appl. Rabia Musheer Aziz, Aftab Hussain, Prajwal Sharma
2024	J	`jnl`	Deep learning approach for brain tumor classification using metaheuristic optimization with gene expression data. Int. J. Imaging Syst. Technol. Amol Avinash Joshi, Rabia Musheer Aziz
2024	J	`jnl`	Optimizing Gene Selection and Cancer Classification with Hybrid Sine Cosine and Cuckoo Search Algorithm. J. Medical Syst. Abrar Yaqoob, Navneet Kumar Verma, Rabia Musheer Aziz
2023	J	`jnl`	A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection. BMC Bioinform. Rajul Mahto, Saboor Uddin Ahmed, Rizwan Ur Rahman, Rabia Musheer Aziz, Priyanka Roy, Saurav Mallik, Aimin Li, Mohd Asif Shah
2023	J	`jnl`	Applications and Techniques of Machine Learning in Cancer Classification: A Systematic Review. Hum. Centric Intell. Syst. Abrar Yaqoob, Rabia Musheer Aziz, Navneet Kumar Verma
2023	J	`jnl`	Computer vision model with novel cuckoo search based deep learning approach for classification of fish image. Multim. Tools Appl. Rabia Musheer Aziz, Nishq Poorav Desai, Mohammed Farhan Baluch
2022	J	`jnl`	Application of nature inspired soft computing techniques for gene selection: a novel frame work for classification of cancer. Soft Comput. Rabia Musheer Aziz
2022	J	`jnl`	Cuckoo Search-Based Optimization for Cancer Classification: A New Hybrid Approach. J. Comput. Biol. Rabia Musheer Aziz
2022	J	`jnl`	Nature-inspired metaheuristics model for gene selection and classification of biomedical microarray data. Medical Biol. Eng. Comput. Rabia Musheer Aziz
2019	J	`jnl`	Novel machine learning approach for classification of high-dimensional microarray data. Soft Comput. Rabia Musheer Aziz, Chandan Kumar Verma, Namita Srivastava
2017	J	`jnl`	A novel approach for dimension reduction of microarray. Comput. Biol. Chem. Rabia Musheer Aziz, Chandan Kumar Verma, Namita Srivastava
2017	J	`jnl`	Artificial neural network classification of microarray data using new hybrid gene selection method. Int. J. Data Min. Bioinform. Rabia Musheer Aziz, Chandan Kumar Verma, Manoj Jha, Namita Srivastava

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.