Abed AlRahman Al Makdah

24 papers A* 1C 2Journal 14Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Linear Dynamics meets Linear MDPs: Closed-Form Optimal Policies via Reinforcement Learning. CoRR Abed AlRahman Al Makdah, Oliver Kosut, Lalitha Sankar, Shaofeng Zou
2025	J	`jnl`	Online Optimization With Unknown Time-Varying Parameters. IEEE Control. Syst. Lett. Shivanshu Tripathi, Abed AlRahman Al Makdah, Fabio Pasqualetti
2025	J	`jnl`	Online Optimization with Unknown Time-varying Parameters. CoRR Shivanshu Tripathi, Abed AlRahman Al Makdah, Fabio Pasqualetti
2024	—	`conf`	A Data-driven Stability Test for LTI Systems. CDC Taosha Guo, Abed AlRahman Al Makdah, Pietro Tesi, Fabio Pasqualetti
2024	—	`conf`	Model-based and Data-based Output Feedback for External Positivity. CDC Abed AlRahman Al Makdah, Fabio Pasqualetti
2023	J	`jnl`	Imitation and Transfer Learning for LQG Control. CoRR Taosha Guo, Abed AlRahman Al Makdah, Vishaal Krishnan, Fabio Pasqualetti
2023	J	`jnl`	Imitation and Transfer Learning for LQG Control. IEEE Control. Syst. Lett. Taosha Guo, Abed AlRahman Al Makdah, Vishaal Krishnan, Fabio Pasqualetti
2023	J	`jnl`	Model-based and Data-based Dynamic Output Feedback for Externally Positive Systems. CoRR Abed AlRahman Al Makdah, Fabio Pasqualetti
2023	—	`conf`	On the Sample Complexity of the Linear Quadratic Gaussian Regulator. CDC Abed AlRahman Al Makdah, Fabio Pasqualetti
2023	J	`jnl`	On the Sample Complexity of the Linear Quadratic Gaussian Regulator. CoRR Abed AlRahman Al Makdah, Fabio Pasqualetti
2022	—	`conf`	Behavioral Feedback for Optimal LQG Control. CDC Abed AlRahman Al Makdah, Vishaal Krishnan, Vaibhav Katewa, Fabio Pasqualetti
2022	J	`jnl`	Behavioral Feedback for Optimal LQG Control. CoRR Abed AlRahman Al Makdah, Vishaal Krishnan, Vaibhav Katewa, Fabio Pasqualetti
2021	J	`jnl`	Learning Robust Feedback Policies from Demonstrations. CoRR Abed AlRahman Al Makdah, Vishaal Krishnan, Fabio Pasqualetti
2021	—	`conf`	Robust Adversarial Classification via Abstaining. CDC Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2021	J	`jnl`	Taming Adversarial Robustness via Abstaining. CoRR Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2020	J	`jnl`	A Fundamental Performance Limitation for Adversarial Classification. IEEE Control. Syst. Lett. Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2020	C	`conf`	Accuracy Prevents Robustness in Perception-based Control. ACC Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2020	C	`conf`	Accuracy Prevents Robustness in Perception-based Control. ACC Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2020	A*	`conf`	Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing. NeurIPS Vishaal Krishnan, Abed AlRahman Al Makdah, Fabio Pasqualetti
2020	J	`jnl`	Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing. CoRR Vishaal Krishnan, Abed AlRahman Al Makdah, Fabio Pasqualetti
2020	—	`conf`	On the Robustness of Data-Driven Controllers for Linear Systems. L4DC Anguluri Rajasekhar, Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2019	J	`jnl`	A Fundamental Performance Limitation for Adversarial Classification. CoRR Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2019	J	`jnl`	On the Robustness of Data-Driven Controllers for Linear Systems. CoRR Anguluri Rajasekhar, Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
2016	—	`conf`	Modeling and optimal three-dimensional trajectory tracking for an autonomous underwater vehicle. AIM Abed AlRahman Al Makdah, Elie A. Shammas, Naseem A. Daher, Imad H. Elhajj

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.