Taghreed Alghamdi

16 papers B 2C 1Journal 5Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Cost-optimized cloud resource management for video streaming: ARIMA predictive approach. Clust. Comput. Mahmoud Darwich, Taghreed Alghamdi, Kasem Khalil, Yasser Ismail, Magdy A. Bayoumi
2024	C	`conf`	Interconnected Traffic Forecasting Using Time Distributed Encoder-Decoder Multivariate Multi-Step LSTM. IV Sifatul Mostafi, Taghreed Alghamdi, Khalid Elgazzar
2023	—	`conf`	Deep Learning Approach for Cost and Storage Optimization of Video Streaming in Cloud Environments. SmartCloud Mahmoud Darwich, Taghreed Alghamdi, Magdy A. Bayoumi
2023	—	`conf`	Deep Learning-Enabled Efficient Storage and Retrieval of Video Streams in the Cloud. SmartCloud Mahmoud Darwich, Taghreed Alghamdi, Magdy A. Bayoumi
2023	—	`conf`	HD Maps for Connected and Automated Vehicles: Enabling Technologies and Future Directions. SM Ghadeer Abdelkader, Taghreed Alghamdi, Khalid Elgazzar, Alaa M. Khamis
2023	J	`jnl`	RegTraffic: A Regression Based Traffic Simulator for Spatiotemporal Traffic Modeling, Simulation and Visualization. CoRR Sifatul Mostafi, Taghreed Alghamdi, Khalid Elgazzar
2022	J	`jnl`	A Comparative Study on Traffic Modeling Techniques for Predicting and Simulating Traffic Behavior. Future Internet Taghreed Alghamdi, Sifatul Mostafi, Ghadeer Abdelkader, Khalid Elgazzar
2022	B	`conf`	RegTraffic: A Regression based Traffic Simulator for Spatiotemporal Traffic Modeling, Simulation and Visualization. IJCNN Sifatul Mostafi, Taghreed Alghamdi, Khalid Elgazzar
2022	J	`jnl`	Revisiting the Internet of Things: New Trends, Opportunities and Grand Challenges. CoRR Khalid Elgazzar, Haytham Khalil, Taghreed Alghamdi, Ahmed Badr, Ghadeer Abdelkader, Abdelrahman Elewah, Rajkumar Buyya
2021	—	`conf`	A Bayesian Linear Regression Approach to Predict Traffic Congestion. WF-IoT Sifatul Mostafi, Taghreed Alghamdi, Khalid Elgazzar
2021	—	`conf`	Deep learning Arabic printed document knowledge extraction. ICFNDS Taghreed Alghamdi, Samia Snoussi, Lobna Hsairi
2021	—	`conf`	Improving Spatiotemporal Traffic Prediction in Adversary Weather Conditions Using Hierarchical Bayesian State Space Modeling. ITSC Taghreed Alghamdi, Khalid Elgazzar, Sifatul Mostafi, James Ng
2021	J	`jnl`	Spatiotemporal Traffic Prediction Using Hierarchical Bayesian Modeling. Future Internet Taghreed Alghamdi, Khalid Elgazzar, Taysseer Sharaf
2020	—	`conf`	Canny edge detection towards deep learning Arabic document classification. ICFNDS Taghreed Alghamdi, Samia Snoussi, Lobna Hsairi
2020	—	`conf`	Spatiotemporal Prediction Using Hierarchical Bayesian Modeling. ICCSPA Taghreed Alghamdi, Khalid Elgazzar, Taysseer Sharaf
2019	B	`conf`	Forecasting Traffic Congestion Using ARIMA Modeling. IWCMC Taghreed Alghamdi, Khalid Elgazzar, Magdi Bayoumi, Taysseer Sharaf, Sumit Shah

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.