Sajjad Shafiei

14 papers B 1Journal 10Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Predicting the Duration of Traffic Incidents for Sydney Greater Metropolitan Area using Machine Learning Methods. Int. J. Intell. Transp. Syst. Res. Artur Grigorev, Sajjad Shafiei, Hanna Grzybowska, Adriana Simona Mihaita
2024	J	`jnl`	An Agent-Based Simulation Approach for Urban Road Pricing Considering the Integration of Autonomous Vehicles With Public Transport. IEEE Trans. Intell. Transp. Syst. Sajjad Shafiei, Hussein Dia, Wen Wu, Hanna Grzybowska, A. K. Qin
2024	J	`jnl`	Predicting the duration of traffic incidents for Sydney greater metropolitan area using machine learning methods. CoRR Artur Grigorev, Sajjad Shafiei, Hanna Grzybowska, Adriana Simona Mihaita
2023	J	`jnl`	Arterial corridor travel time prediction under non-recurring conditions. J. Intell. Transp. Syst. Sajjad Shafiei, Eileen Wang, Hanna Grzybowska, Chen Cai
2023	B	`conf`	Training Physics- Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction. IJCNN Bo Wang, A. K. Qin, Sajjad Shafiei, Hussein Dia, Adriana Simona Mihaita, Hanna Grzybowska
2023	J	`jnl`	Training Physics-Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction. CoRR Bo Wang, A. K. Qin, Sajjad Shafiei, Hussein Dia, Adriana Simona Mihaita, Hanna Grzybowska
2022	—	`conf`	Traffic disruption modelling with mode shift in multi-modal networks. ITSC Dong Zhao, Adriana Simona Mihaita, Yuming Ou, Sajjad Shafiei, Hanna Grzybowska, Kai Qin, Gary Tan, Mo Li, Hussein Dia
2021	J	`jnl`	An Open GMNS Dataset of a Dynamic Multi-Modal Transportation Network Model of Melbourne, Australia. Data Fatemeh Nourmohammadi, Mohammadhadi Mansourianfar, Sajjad Shafiei, Ziyuan Gu, Meead Saberi
2019	J	`jnl`	A simple contagion process describes spreading of traffic jams in urban networks. CoRR Meead Saberi, Mudabber Ashfaq, Homayoun Hamedmoghadam, Seyed Amir Hosseini, Ziyuan Gu, Sajjad Shafiei, Divya Jayakumar Nair, Vinayak V. Dixit, Lauren Gardner, S. Travis Waller, Marta C. González
2019	—	`conf`	Nonlinearity in Time-Dependent Origin-Destination Demand Estimation in Congested Networks. ITSC Sajjad Shafiei, Meead Saberi, Hai L. Vu
2019	J	`jnl`	Optimal distance- and time-dependent area-based pricing with the Network Fundamental Diagram. CoRR Ziyuan Gu, Sajjad Shafiei, Zhiyuan Liu, Meead Saberi
2019	J	`jnl`	Trip Table Estimation and Prediction for Dynamic Traffic Assignment Applications. CoRR Sajjad Shafiei, Adriana Simona Mihaita, Chen Cai
2018	J	`jnl`	Calibration and validation of a simulation-based dynamic traffic assignment model for a large-scale congested network. Simul. Model. Pract. Theory Sajjad Shafiei, Ziyuan Gu, Meead Saberi
2016	—	`conf`	Application of an exact gradient method to estimate dynamic origin-destination demand for melbourne network. ITSC Sajjad Shafiei, Meead Saberi, Majid Sarvi

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.