G. Joselin Retna Kumar

12 papers Journal 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A power-efficient IoT mechanism with adaptive recurrent temporal optimized convolutional learning (ARTOCL) scheme for real-time urban air quality monitoring. Discov. Internet Things S. Gunasekar, G. Pius Agbulu, G. Joselin Retna Kumar
2025	J	`jnl`	Optimizing Robotic Task Sequencing and Trajectory Planning (TSTP): A Multi-Objective Hybrid Optimization Approach Coupled with Reinforcement Learning (DRL). J. Circuits Syst. Comput. Aniruddha Joshi, G. Joselin Retna Kumar
2024	J	`jnl`	A Deep Transfer Learning Approach for Addressing Yaw Pose Variation to Improve Face Recognition Performance. Intell. Autom. Soft Comput. M. Jayasree, K. A. Sunitha, A. Brindha, Punna Rajasekhar, Govindan Aravamuthan, G. Joselin Retna Kumar
2024	J	`jnl`	A LoRa-Based Internet of Things Smart Irrigation Control Solution with Hybrid Classifier CNN-SVM. Wirel. Pers. Commun. G. Pius Agbulu, G. Joselin Retna Kumar
2024	J	`jnl`	IESDCC-KM: an improved energy-saving distributed cluster-chain K-communication scheme for smart sensor networks. Int. J. Syst. Assur. Eng. Manag. G. Pius Agbulu, G. Joselin Retna Kumar, S. Gunasekar
2022	J	`jnl`	A cloud-assisted mesh sensor network solution for public zone air pollution real-time data acquisition. J. Ambient Intell. Humaniz. Comput. G. Joselin Retna Kumar, G. Pius Agbulu, T. V. Rahul, A. V. Natarajan, K. Gokul
2022	J	`jnl`	Air Quality Predictions in Urban Areas Using Hybrid ARIMA and Metaheuristic LSTM. Comput. Syst. Sci. Eng. S. Gunasekar, G. Joselin Retna Kumar, G. Pius Agbulu
2022	J	`jnl`	PECDF-CMRP: A Power-Efficient Compressive Data Fusion and Cluster-Based Multi-hop Relay-Assisted Routing Protocol for IoT Sensor Networks. Wirel. Pers. Commun. G. Pius Agbulu, G. Joselin Retna Kumar, Asokan Vimala Juliet, S. Adurrashid Hassan
2021	J	`jnl`	A New Hybrid BAT-ANFIS-Based Power Tracking Technique for Partial Shaded Photovoltaic Systems. Int. J. Fuzzy Syst. Ronit Sarkar, G. Joselin Retna Kumar, R. Sridhar, S. Vidyasagar
2020	J	`jnl`	A lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks. Int. J. Distributed Sens. Networks G. Pius Agbulu, G. Joselin Retna Kumar, Asokan Vimala Juliet
2020	J	`jnl`	AERAA-DAR: Algorithm for Energy-Resourceful Attribute-aware Data Aggregation and Routing In Wireless Sensor Networks. Ad Hoc Sens. Wirel. Networks G. Pius Agbulu, G. Joselin Retna Kumar, Asokan Vimala Juliet
2014	J	`jnl`	Neuro fuzzy based Performance Analysis of multiband ultra Wide band orthogonal frequency Division Multiplexing System. J. Comput. Sci. G. Joselin Retna Kumar, K. S. Shaji

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.