Parag Kumar Guha Thakurta

14 papers Misc 1Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep neural network based multitask strategy for soil amendment in sustainable agriculture. Int. J. Mach. Learn. Cybern. Manas Kumar Mohanty, Samarjit Kar, Parag Kumar Guha Thakurta
2026	Misc	`conf`	EvoRoute: An Evolutionary Multi-Agent Framework for Sustainable and Congestion-Aware Routing in Intelligent Transportation Systems. COMSNETS Subha Sankar Chakraborty, Parag Kumar Guha Thakurta
2025	J	`jnl`	An intelligent geographic information system-based framework for energy efficient street lighting. Signal Image Video Process. Kazi Amrin Kabir, Parag Kumar Guha Thakurta, Samarjit Kar
2025	J	`jnl`	Q-ACRY: Efficient Q-learning based Adaptive Crop Rotation technique for maximizing Yield. Expert Syst. Appl. Manas Kumar Mohanty, Samarjit Kar, Parag Kumar Guha Thakurta
2024	J	`jnl`	ANNEGA: an artificial neural network embedded genetic algorithm approach for energy efficient street lighting. Evol. Intell. Pragna Labani Sikdar, Samarjit Kar, Parag Kumar Guha Thakurta
2024	—	`conf`	Classification of Tomato Maturity Levels: An Efficient Approach with Statistical Features. CICBA (1) Subha Sankar Chakraborty, Parag Kumar Guha Thakurta
2024	J	`jnl`	Efficient healthcare supply chain: A prioritized multi-task learning approach with task-specific regularization. Eng. Appl. Artif. Intell. Soumyadipta Kar, Manas Kumar Mohanty, Parag Kumar Guha Thakurta
2024	J	`jnl`	Energy Aware Routing in Wireless Sensor Networks for Agricultural Monitoring: A Deep Q-Network Based Framework. SN Comput. Sci. Ranadeep Dey, Parag Kumar Guha Thakurta, Samarjit Kar
2023	J	`jnl`	Agricultural commodity price prediction model: a machine learning framework. Neural Comput. Appl. Manas Kumar Mohanty, Parag Kumar Guha Thakurta, Samarjit Kar
2023	J	`jnl`	Efficacious tuning in energy efficient street lighting. Int. J. Ad Hoc Ubiquitous Comput. Pragna Labani Sikdar, Abhinav Anurag, Parag Kumar Guha Thakurta
2022	J	`jnl`	Multiobjective energy efficient street lighting framework: A data analysis approach. Appl. Intell. Pragna Labani Sikdar, Samarjit Kar, Parag Kumar Guha Thakurta
2021	J	`jnl`	An energy efficient street lighting framework: ANN-based approach. Innov. Syst. Softw. Eng. Pragna Labani Sikdar, Parag Kumar Guha Thakurta
2018	J	`jnl`	An energy efficient teaching learning based optimization approach for common content distribution in mobile ad hoc networks. Comput. Electr. Eng. Mahendra Maiti, Srijit Mukherjee, Parag Kumar Guha Thakurta
2018	J	`jnl`	Energy Efficient Routing to Improve Lifetime in MANET: A Clustering Approach. J. Commun. Chinmoy Kalita, Parag Kumar Guha Thakurta

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.