Ladan Khoshnevisan

17 papers B 1C 1Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Scalable structurally-guided consensus for distributed learning-based fault isolation in networked dynamical systems. Appl. Soft Comput. Mohammadreza Ghorbani, Ladan Khoshnevisan, Mohammad Pirani, Amir Khajepour
2025	J	`jnl`	A Novel Parameter-Tying Theorem in Multi-Model Adaptive Systems: Systematic Approach for Efficient Model Selection. CoRR Farid Mafi, Ladan Khoshnevisan, Mohammad Pirani, Amir Khajepour
2025	J	`jnl`	A Secure Adaptive Resilient Neural Network-Based Control of Heterogeneous Connected Automated Vehicles Subject to Cyber Attacks. IEEE Trans. Veh. Technol. Ladan Khoshnevisan, Xinzhi Liu
2025	J	`jnl`	An Efficient Continual Learning Framework for Multivariate Time Series Prediction Tasks with Application to Vehicle State Estimation. CoRR Arvin Hosseinzadeh, Ladan Khoshnevisan, Mohammad Pirani, Shoja'eddin Chenouri, Amir Khajepour
2025	J	`jnl`	Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation. CoRR Farid Mafi, Ladan Khoshnevisan, Mohammad Pirani, Amir Khajepour
2025	J	`jnl`	Multi-Objective Agent-Based Model Predictive Controller for Plug-and-Play Vehicle Control. IEEE Trans. Intell. Transp. Syst. Jiaming Zhong, Ladan Khoshnevisan, Shucheng Huang, Mohammad Pirani, Yash Vardhan Pant, Amir Khajepour
2025	C	`conf`	Optimism Induction Attack on Deep Reinforcement Learning with Control Barrier Function Safety Filter for Autonomous Driving. ACC Saeedeh Lohrasbi, Ladan Khoshnevisan, Apurva Narayan, Nasser Lashgarian Azad, Pulei Xiong
2025	J	`jnl`	Resilient Neural-Variable-Structure Consensus Control for Nonlinear MASs with Singular Input Gain Under DoS Attacks. CoRR Ladan Khoshnevisan, Xinzhi Liu
2024	J	`jnl`	A Neural-Lyapunov-Based Adaptive Resilient Cruise Control of Platoons Subject to Cyber-Attacks on Leaders. IEEE Control. Syst. Lett. Ladan Khoshnevisan, Xinzhi Liu
2024	J	`jnl`	Levelized-cost optimal design of long-distance CO2 transportation facilities. Comput. Chem. Eng. Mohamed Mazhar Laljee, Farzad Hourfar, Yuri Leonenko, Ladan Khoshnevisan, Hedia Fgaier, Ali Almansoori, Ali Elkamel
2022	J	`jnl`	Integral sliding-mode robust observer-based congestion control for wireless access networks. J. Control. Decis. Ladan Khoshnevisan, Farzad Rajaei Salmasi, Xinzhi Liu
2022	—	`conf`	Lyapunov Analysis of Least Squares Based Direct Adaptive Control. CDC Nursefa Zengin, Baris Fidan, Ladan Khoshnevisan
2020	J	`jnl`	Mixed Comput. Chem. Eng. Farzad Hourfar, Ladan Khoshnevisan, Behzad Moshiri, Karim Salahshoor, Ali Elkamel
2019	J	`jnl`	Fractional order predictive sliding-mode control for a class of nonlinear input-delay systems: singular and non-singular approach. Int. J. Syst. Sci. Ladan Khoshnevisan, Xinzhi Liu
2016	J	`jnl`	A robust and high-performance queue management controller for large round trip time networks. Int. J. Syst. Sci. Ladan Khoshnevisan, Farzad Rajaei Salmasi
2015	J	`jnl`	A rate-based robust queue management system through multi-loop internal model controller with initial value compensation. J. Control. Decis. Ladan Khoshnevisan, Farzad Rajaei Salmasi
2015	B	`conf`	Robust queue management for TCP-based large round trip time networks with wireless access link. WCNC Ladan Khoshnevisan, Farzad Rajaei Salmasi, Vahid Shah-Mansouri

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.