Omar Qasem

12 papers Journal 9Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Reinforcement-Learning, Optimal Approach to In Situ Power Hardware-in-the-Loop Interface Control for Testing Inverter-Based Resources: Theory and Application of the Adaptive Dynamic Programming Based on the Hybrid Iteration to Tackle Uncertain Dynamics. IEEE Trans. Ind. Electron. Masoud Davari, Omar Qasem, Weinan Gao, Frede Blaabjerg, Panos C. Kotsampopoulos, Georg Lauss, Nikos D. Hatziargyriou
2025	—	`conf`	Reinforcement Learning-Based Optimal Control for Continuous-Time Quantized Systems via Adaptive Dynamic Programming. SSD Omar Qasem, Weinan Gao, Omar Rawhi Daoud
2024	J	`jnl`	Experimental Validation of Data-Driven Adaptive Optimal Control for Continuous-Time Systems Via Hybrid Iteration: An Application to Rotary Inverted Pendulum. IEEE Trans. Ind. Electron. Omar Qasem, Hector M. Gutierrez, Weinan Gao
2024	J	`jnl`	Hybrid Iteration ADP Algorithm to Solve Cooperative, Optimal Output Regulation Problem for Continuous-Time, Linear, Multiagent Systems: Theory and Application in Islanded Modern Microgrids With IBRs. IEEE Trans. Ind. Electron. Omar Qasem, Masoud Davari, Weinan Gao, Daniel R. Kirk, Tianyou Chai
2024	J	`jnl`	Robust Policy Iteration of Uncertain Interconnected Systems With Imperfect Data. IEEE Trans Autom. Sci. Eng. Omar Qasem, Weinan Gao
2023	J	`jnl`	Adaptive optimal control of continuous-time nonlinear affine systems via hybrid iteration. Autom. Omar Qasem, Weinan Gao, Kyriakos G. Vamvoudakis
2023	J	`jnl`	Autonomous Satellite Docking via Adaptive Optimal Output Rregulation: A Reinforcement Learning Approach. CoRR Omar Qasem, Madhur Tiwari, Hector Gutierrez
2023	J	`jnl`	Control of Small Spacecraft by Optimal Output Regulation: A Reinforcement Learning Approach. CoRR Joao Leonardo Silva Cotta, Omar Qasem, Paula do Vale Pereira, Hector Gutierrez
2022	—	`conf`	Adaptive Dynamic Programming and Data-Driven Cooperative Optimal Output Regulation with Adaptive Observers. CDC Omar Qasem, Khalid Jebari, Weinan Gao
2022	J	`jnl`	Adaptive Dynamic Programming and Data-Driven Cooperative Optimal Output Regulation with Adaptive Observers. CoRR Omar Qasem, Khalid Jebari, Weinan Gao
2021	—	`conf`	Adaptive Optimal Control of Continuous-Time Linear Systems via Hybrid Iteration. SSCI Omar Qasem, Weinan Gao, Tao Bian
2019	J	`jnl`	Full-order and reduced-order observers for linear parameter-varying systems with one-sided Lipschitz nonlinearities and disturbances using parameter-dependent Lyapunov function. J. Frankl. Inst. Ali Abdullah, Omar Qasem

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.