Farzan Shenavarmasouleh

15 papers Journal 11Unranked 4

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Deep Learning in Healthcare: An In-Depth Analysis. CoRR Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, Khaled M. Rasheed, Hamid R. Arabnia
2022	J	`jnl`	3D-model ShapeNet Core Classification using Meta-Semantic Learning. CoRR Farid Ghareh Mohammadi, Cheng Chen, Farzan Shenavarmasouleh, M. Hadi Amini, Beshoy Morkos, Hamid R. Arabnia
2022	J	`jnl`	Applications of Machine Learning in Healthcare and Internet of Things (IOT): A Comprehensive Review. CoRR Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Hamid R. Arabnia
2022	J	`jnl`	The application of Evolutionary and Nature Inspired Algorithms in Data Science and Data Analytics. CoRR Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Khaled Rasheed, Thiab R. Taha, M. Hadi Amini, Hamid R. Arabnia
2021	J	`jnl`	DRDrV3: Complete Lesion Detection in Fundus Images Using Mask R-CNN, Transfer Learning, and LSTM. CoRR Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini, Thiab R. Taha, Khaled Rasheed, Hamid R. Arabnia
2021	J	`jnl`	Data Analytics for Smart cities: Challenges and Promises. CoRR Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini, Hamid R. Arabnia
2021	J	`jnl`	Embodied AI-Driven Operation of Smart Cities: A Concise Review. CoRR Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
2021	—	`conf`	Evolutionary Algorithms and Efficient Data Analytics for Image Processing. IMCOM Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini, Hamid R. Arabnia
2021	—	`conf`	Internet of Things (IoT) in Healthcare: Applications, Challenges and Solutions. CSCI Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Hamid R. Arabnia
2021	—	`conf`	The application of Evolutionary and Nature Inspired Algorithms in Data Science and Data Analytics. CSCI Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Khaled Rasheed, Thiab R. Taha, M. Hadi Amini, Hamid R. Arabnia
2020	J	`jnl`	DRDr II: Detecting the Severity Level of Diabetic Retinopathy Using Mask RCNN and Transfer Learning. CoRR Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia
2020	J	`jnl`	DRDr: Automatic Masking of Exudates and Microaneurysms Caused By Diabetic Retinopathy Using Mask R-CNN and Transfer Learning. CoRR Farzan Shenavarmasouleh, Hamid R. Arabnia
2020	J	`jnl`	DeepMSRF: A novel Deep Multimodal Speaker Recognition framework with Feature selection. CoRR Ehsan Asali, Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, Prasanth Sengadu Suresh, Hamid R. Arabnia
2020	J	`jnl`	Malware Detection using Artificial Bee Colony Algorithm. CoRR Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini, Hamid R. Arabnia
2020	—	`conf`	Malware detection using artificial bee colony algorithm. UbiComp/ISWC Adjunct Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini, Hamid R. Arabnia

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.