Raman Manivannan

18 papers Journal 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Multi-Head Attention ResCNN-BiGRU Model for Robust SOC Estimation in EVs Lithium-Ion Batteries Using Real-World Driving Data. IEEE Access N. Vigneswar, Raman Manivannan, Chala Merga Abdissa
2026	J	`jnl`	An Improved Robust H∞ Observer Framework for State-of-Charge Estimation of Lithium-Ion Batteries in Electric Vehicles. IEEE Access K. Vinothini, Raman Manivannan, Chala Merga Abdissa
2024	J	`jnl`	Generalized state estimation criteria for additive delayed memristor neural networks including leakage delay effect-flux-charge domain applications in energy storage systems. J. Frankl. Inst. Raman Manivannan
2023	J	`jnl`	Robust unified dissipativity vibration control design for offshore steel jacket platform in ocean environments under self-excited nonlinear wave force. J. Frankl. Inst. Raman Manivannan
2021	J	`jnl`	Extended Dissipativity Performance of High-Speed Train Including Actuator Faults and Probabilistic Time-Delays Under Resilient Reliable Control. IEEE Trans. Syst. Man Cybern. Syst. Jinde Cao, Raman Manivannan, Kil To Chong, Xiaoxiao Lv
2021	J	`jnl`	Quasi-stability and quasi-synchronization control of quaternion-valued fractional-order discrete-time memristive neural networks. Appl. Math. Comput. Ruoxia Li, Jinde Cao, Changfeng Xue, Raman Manivannan
2020	J	`jnl`	Design of Resilient Reliable Dissipativity Control for Systems With Actuator Faults and Probabilistic Time-Delay Signals via Sampled-Data Approach. IEEE Trans. Syst. Man Cybern. Syst. Raman Manivannan, Rajendran Samidurai, Jinde Cao, Matjaz Perc
2020	J	`jnl`	Generalized dissipativity state estimation for genetic regulatory networks with interval time-delay signals and leakage delays. Commun. Nonlinear Sci. Numer. Simul. Raman Manivannan, Jinde Cao, Kil To Chong
2019	J	`jnl`	Enhanced L2-L∞ state estimation design for delayed neural networks including leakage term via quadratic-type generalized free-matrix-based integral inequality. J. Frankl. Inst. Jinde Cao, Raman Manivannan, Kil To Chong, Xiaoxiao Lv
2018	J	`jnl`	An Arcak-type state estimation design for time-delayed static neural networks with leakage term based on unified criteria. Neural Networks Raman Manivannan, Satyananda Panda, Kil To Chong, Jinde Cao
2018	J	`jnl`	Design of extended dissipativity state estimation for generalized neural networks with mixed time-varying delay signals. Inf. Sci. Raman Manivannan, Rajendran Samidurai, Jinde Cao, Ahmed Alsaedi, Fuad E. Alsaadi
2018	J	`jnl`	New Criteria for Stability of Generalized Neural Networks Including Markov Jump Parameters and Additive Time Delays. IEEE Trans. Syst. Man Cybern. Syst. Rajendran Samidurai, Raman Manivannan, Choon Ki Ahn, Hamid Reza Karimi
2017	J	`jnl`	An improved delay-partitioning approach to stability criteria for generalized neural networks with interval time-varying delays. Neural Comput. Appl. Raman Manivannan, Rajendran Samidurai, Ramalingam Sriraman
2017	J	`jnl`	Exponential stability and extended dissipativity criteria for generalized neural networks with interval time-varying delay signals. J. Frankl. Inst. Raman Manivannan, G. Mahendrakumar, Rajendran Samidurai, Jinde Cao, Ahmed Alsaedi
2017	J	`jnl`	Further improved results on stability and dissipativity analysis of static impulsive neural networks with interval time-varying delays. J. Frankl. Inst. Raman Manivannan, Rajendran Samidurai, Quanxin Zhu
2017	J	`jnl`	Global exponential stability and dissipativity of generalized neural networks with time-varying delay signals. Neural Networks Raman Manivannan, Rajendran Samidurai, Jinde Cao, Ahmed Alsaedi, Fuad E. Alsaadi
2016	J	`jnl`	Delay-range-dependent passivity analysis for uncertain stochastic neural networks with discrete and distributed time-varying delays. Neurocomputing Rajendran Samidurai, Raman Manivannan
2015	J	`jnl`	Robust passivity analysis for stochastic impulsive neural networks with leakage and additive time-varying delay components. Appl. Math. Comput. Rajendran Samidurai, Raman Manivannan

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.