Rahul Karmakar

20 papers C 2Journal 16Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A non-dominated archived multi-objective harmony search algorithm for identifying influencers in social networks. Comput. J. Taniya Chatterjee, Puja Bhakta, Mili Ghosh, Rahul Karmakar, Debaditya Barman
2026	J	`jnl`	Intelligent breast cancer diagnosis: K-means-based oversampling and comparative feature selection for enhanced classification. Eng. Appl. Artif. Intell. Rahul Karmakar, Akhil Kumar Das, Saroj Kr. Biswas, Ardhendu Mandal, Arijit Bhattacharya, Debasmita Saha, Debapriya Sarkar
2026	J	`jnl`	NAMSA: A Non-Dominated Archived Multi-Objective Simulated Annealing Algorithm for Detecting Influencers in Social Networks. IEEE Access Puja Bhakta, Debaditya Barman, Taniya Chatterjee, Mili Ghosh, Rahul Karmakar, Abu Sufian, Marco Leo, Cosimo Distante
2026	J	`jnl`	Neuro -symbolic continual learning with replay and elastic weight consolidation: A case study in mental health risk assessment. Knowl. Based Syst. Sayan Pal, Rahul Karmakar
2026	—	`conf`	Neuro-Symbolic AI-Driven Mental Health Risk Prediction with Human-Readable Rule Extraction and Interactive Explainability. ICAA Sayan Pal, Rahul Karmakar
2025	J	`jnl`	An Explainable AI Model for Binary LJ Fluids. CoRR Israrul H. Hashmi, Rahul Karmakar, Marripelli Maniteja, Kumar Ayush, Tarak K. Patra
2025	J	`jnl`	Breast Cancer Prediction using Stacking Models & Hyperparameter Tuning. Inteligencia Artif. Rahul Karmakar, Akhil Kumar Das, Debapriya Sarkar, Saroj Kumar Biswas, Ardhendu Mandal, Arijit Bhattacharya
2024	J	`jnl`	A data balancing approach towards design of an expert system for Heart Disease Prediction. CoRR Rahul Karmakar, Udita Ghosh, Arpita Pal, Sattwiki Dey, Debraj Malik, Priyabrata Sain
2024	J	`jnl`	A graphical tool for formal verification using Event-B modeling. Multim. Tools Appl. Rahul Karmakar
2024	J	`jnl`	Deep Learning-based Sentiment Analysis of Olympics Tweets. CoRR Indranil Bandyopadhyay, Rahul Karmakar
2024	J	`jnl`	Elevating security and disease forecasting in smart healthcare through artificial neural synchronized federated learning. Clust. Comput. Tao Hai, Arindam Sarkar, Muammer Aksoy, Rahul Karmakar, Sarbajit Manna, Amrita Prasad
2024	J	`jnl`	Extrapolative ML Models for Copolymers. CoRR Israrul H. Hashmi, Himanshu, Rahul Karmakar, Tarak K. Patra
2024	J	`jnl`	GAN-guided artificial neural collaborative complex computation for efficient neural synchronization. Multim. Tools Appl. Arindam Sarkar, Rahul Karmakar, Mandira Roy
2024	J	`jnl`	Secured mutual wireless communication using real and imaginary-valued artificial neuronal synchronization and attack detection. Eng. Appl. Artif. Intell. Chengzhi Jiang, Arindam Sarkar, Abdulfattah Noorwali, Rahul Karmakar, Kamal M. Othman, Sarbajit Manna
2023	J	`jnl`	BCPUML: Breast Cancer Prediction Using Machine Learning Approach - A Performance Analysis. SN Comput. Sci. Rahul Karmakar, Subhranil Chatterjee, Akhil Kumar Das, Ardhendu Mandal
2023	J	`jnl`	Neural session key exchange in the Industrial Internet of Things using hyperchaotic-guided vector-valued artificial neural synchronization. Eng. Appl. Artif. Intell. Tao Hai, Arindam Sarkar, Rahul Karmakar, Mohammad Zubair Khan, Ayman Noor, Talal H. Noor, Abhinav Kumar, A. Yvaz
2021	J	`jnl`	A Prototype Modeling of Smart Irrigation System Using Event-B. SN Comput. Sci. Rahul Karmakar, Bidyut Biman Sarkar
2021	C	`conf`	Formal Verification Techniques: A Comparative Analysis for Critical System Design. ISDA Rahul Karmakar
2020	—	`conf`	Event Ordering Using Graphical Notation for Event-B Models. CISIM Rahul Karmakar, Bidyut Biman Sarkar, Nabendu Chaki
2020	C	`conf`	Formal Verification of Safety-Critical Systems: A Case-Study in Airbag System Design. ISDA Susmita Guha, Akash Nag, Rahul Karmakar

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.