Zain U. Hussain

11 papers Journal 9Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Medical Domain Knowledge Collaborative Graph Learning for Healthcare Event Prediction. Expert Syst. J. Knowl. Eng. Usman Naseem, Junaid Rashid, Haohui Lu, Dominic Ng, Zain U. Hussain, Amir Hussain
2025	J	`jnl`	Transfer Learning-Based Automatic Sentiment Annotation of a Twitter-Based Arabic Mental Illness (AMI) Dataset. Expert Syst. J. Knowl. Eng. Arwa Diwali, Kawther Saeedi, Kia Dashtipour, Mandar Gogate, Zain U. Hussain, Adam Howard, Amir Hussain
2024	J	`jnl`	A novel end-to-end deep convolutional neural network based skin lesion classification framework. Expert Syst. Appl. A. Razia Sulthana, Vinay Chamola, Zain U. Hussain, Faisal Albalwy, Amir Hussain
2024	J	`jnl`	Deep learning methods for early detection of Alzheimer's disease using structural MR images: a survey. Neurocomputing Sonia Ben Hassen, Mohamed Neji, Zain U. Hussain, Amir Hussain, Adel M. Alimi, Mondher Frikha
2022	J	`jnl`	A fuzzy-enhanced deep learning approach for early detection of Covid-19 pneumonia from portable chest X-ray images. Neurocomputing Cosimo Ieracitano, Nadia Mammone, Mario Versaci, Giuseppe Varone, Abder-Rahman Ali, Antonio Armentano, Grazia Calabrese, Anna Ferrarelli, Lorena Turano, Carmela Tebala, Zain U. Hussain, Zakariya Sheikh, Aziz Sheikh, Giuseppe Sceni, Amir Hussain, Francesco Carlo Morabito
2021	J	`jnl`	A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling. Sensors Muhamed Wael Farouq, Wadii Boulila, Zain U. Hussain, Asrar Rashid, Moiz Ali Shah, Sajid Hussain, Nathan Ng, Dominic Ng, Haris Hanif, M. Guftar Shaikh, Aziz Sheikh, Amir Hussain
2021	J	`jnl`	Real-Time Artifacts Reduction during TMS-EEG Co-Registration: A Comprehensive Review on Technologies and Procedures. Sensors Giuseppe Varone, Zain U. Hussain, Zakariya Sheikh, Adam Howard, Wadii Boulila, Mufti Mahmud, Newton Howard, Francesco Carlo Morabito, Amir Hussain
2020	J	`jnl`	A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19. IEEE J. Biomed. Health Informatics Jinchang Ren, Yijun Yan, Huimin Zhao, Ping Ma, Jaime Zabalza, Zain U. Hussain, Shaoming Luo, Qingyun Dai, Sophia Zhao, Aziz Sheikh, Amir Hussain, Huakang Li
2017	—	`conf`	Machine learning based computer-aided diagnosis of liver tumours. IEEE ICCI*CC Liaqat Ali, Khaled Khelil, Summrina Kanwal Wajid, Zain U. Hussain, Moiz Ali Shah, Adam Howard, Ahsan Adeel, Amir A. Shah, Unnam Sudhakar, Newton Howard, Amir Hussain
2016	—	`conf`	A Novel Fully Automated Liver and HCC Tumor Segmentation System Using Morphological Operations. BICS Liaqat Ali, Amir Hussain, Jingpeng Li, Newton Howard, Amir A. Shah, Unnam Sudhakar, Moiz Ali Shah, Zain U. Hussain
2016	J	`jnl`	A new recurrent neural network based predictive model for Faecal Calprotectin analysis: A retrospective study. CoRR Zeeshan Khawar Malik, Zain U. Hussain, Ziad Kobti, Charlie W. Lees, Newton Howard, Amir Hussain

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.