G. Soundararajan

14 papers Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Improved results on finite-time synchronization of shunting inhibitory cellular neural networks with time-varying delays via impulsive pinning hybrid control. J. Frankl. Inst. Otankhan Maikenov, G. Soundararajan, Rakkiyappan Rajan, Ardak Kashkynbayev
2025	J	`jnl`	Output sampling synchronization and state estimation in flux-charge domain memristive neural networks with leakage and time-varying delays. Neural Networks G. Soundararajan, R. Suvetha, Minvydas Ragulskis, P. Prakash
2024	J	`jnl`	Co-existence of robust output-feedback synchronization and anti-synchronization of delayed discrete-time neural networks with its application. Comput. Appl. Math. K. Sri Raja Priyanka, G. Soundararajan, Ardak Kashkynbayev, Gnaneswaran Nagamani
2024	J	`jnl`	Exponential H∞ filtering for complex-valued uncertain discrete-time neural networks with time-varying delays. Commun. Nonlinear Sci. Numer. Simul. G. Soundararajan, Gnaneswaran Nagamani, Ardak Kashkynbayev
2024	J	`jnl`	Finite-time contractive stability for fractional-order nonlinear systems with delayed impulses: Applications to neural networks. Neurocomputing P. Gokul, G. Soundararajan, Ardak Kashkynbayev, R. Rakkiyappan
2023	J	`jnl`	Exponential H∞ synchronization and anti-synchronization of delayed discrete-time complex-valued neural networks with uncertainties. Math. Comput. Simul. K. Sri Raja Priyanka, G. Soundararajan, Ardak Kashkynbayev, Gnaneswaran Nagamani
2023	J	`jnl`	Non-fragile output-feedback synchronization for delayed discrete-time complex-valued neural networks with randomly occurring uncertainties. Neural Networks G. Soundararajan, Gnaneswaran Nagamani
2022	J	`jnl`	Exponential extended dissipative performance for delayed discrete-time neural networks under memoryless resilient-based observer design. J. Frankl. Inst. B. Adhira, Gnaneswaran Nagamani, G. Soundararajan
2021	J	`jnl`	Delay-Dependent and Independent State Estimation for BAM Cellular Neural Networks with Multi-Proportional Delays. Circuits Syst. Signal Process. Gnaneswaran Nagamani, A. Karnan, G. Soundararajan
2020	J	`jnl`	An LMI Based State Estimation for Fractional-Order Memristive Neural Networks with Leakage and Time Delays. Neural Process. Lett. Gnaneswaran Nagamani, M. Shafiya, G. Soundararajan
2020	J	`jnl`	Robust event-triggered reliable control for T-S fuzzy uncertain systems via weighted based inequality. Inf. Sci. Gnaneswaran Nagamani, Young Hoon Joo, G. Soundararajan, Reza Mohajerpoor
2020	J	`jnl`	Robust extended dissipativity analysis for Markovian jump discrete-time delayed stochastic singular neural networks. Neural Comput. Appl. Gnaneswaran Nagamani, G. Soundararajan, Ramasamy Subramaniam, Muhammad Azeem
2020	J	`jnl`	Robust state estimation for fractional-order delayed BAM neural networks via LMI approach. J. Frankl. Inst. Gnaneswaran Nagamani, M. Shafiya, G. Soundararajan, Mani Prakash
2019	J	`jnl`	Observer-based exponential stabilization for time-delay systems via augmented weighted integral inequality. J. Frankl. Inst. Gnaneswaran Nagamani, C. Karthik, G. Soundararajan

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.