Abhishek Mallik

16 papers Misc 1Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	HumourHindiNet: Humour detection in Hindi web series using word embedding and convolutional neural network. ACM Trans. Asian Low Resour. Lang. Inf. Process. Akshi Kumar, Abhishek Mallik, Sanjay Kumar
2024	J	`jnl`	Modified node2vec and attention based fusion framework for next POI recommendation. Inf. Fusion Akshi Kumar, Deepak Kumar Jain, Abhishek Mallik, Sanjay Kumar
2024	J	`jnl`	OptNet-Fake: Fake News Detection in Socio-Cyber Platforms Using Grasshopper Optimization and Deep Neural Network. IEEE Trans. Comput. Soc. Syst. Sanjay Kumar, Akshi Kumar, Abhishek Mallik, Rishi Ranjan Singh
2024	J	`jnl`	TLP-NEGCN: Temporal Link Prediction via Network Embedding and Graph Convolutional Networks. IEEE Trans. Comput. Soc. Syst. Akshi Kumar, Abhishek Mallik, Sanjay Kumar
2024	J	`jnl`	Word2Vec and LSTM based deep learning technique for context-free fake news detection. Multim. Tools Appl. Abhishek Mallik, Sanjay Kumar
2023	J	`jnl`	COVID-19 Detection from Chest X-rays Using Trained Output Based Transfer Learning Approach. Neural Process. Lett. Sanjay Kumar, Abhishek Mallik
2023	J	`jnl`	Community detection in complex networks using stacked autoencoders and crow search algorithm. J. Supercomput. Sanjay Kumar, Abhishek Mallik, Sandeep Singh Sengar
2023	J	`jnl`	Fuzz-ClustNet: Coupled fuzzy clustering and deep neural networks for Arrhythmia detection from ECG signals. Comput. Biol. Medicine Sanjay Kumar, Abhishek Mallik, Akshi Kumar, Javier Del Ser, Guang Yang
2023	J	`jnl`	Influence maximization in social networks using transfer learning via graph-based LSTM. Expert Syst. Appl. Sanjay Kumar, Abhishek Mallik, B. S. Panda
2023	J	`jnl`	Opinion Leader Detection in Asian Social Networks using Modified Spider Monkey Optimization. ACM Trans. Asian Low Resour. Lang. Inf. Process. Sanjay Kumar, Akshi Kumar, Abhishek Mallik, Sakshi Dhall
2022	J	`jnl`	ConRec: malware classification using convolutional recurrence. J. Comput. Virol. Hacking Tech. Abhishek Mallik, Anavi Khetarpal, Sanjay Kumar
2022	J	`jnl`	Influence maximization in social networks using graph embedding and graph neural network. Inf. Sci. Sanjay Kumar, Abhishek Mallik, Anavi Khetarpal, Bhawani Sankar Panda
2022	J	`jnl`	Integrating node centralities, similarity measures, and machine learning classifiers for link prediction. Multim. Tools Appl. Sameer Anand, Rahul, Abhishek Mallik, Sanjay Kumar
2022	J	`jnl`	Link prediction in complex networks using node centrality and light gradient boosting machine. World Wide Web Sanjay Kumar, Abhishek Mallik, B. S. Panda
2012	—	`conf`	Contextual Suggestion. TREC Abhishek Mallik, Mandar Mitra, Kripabandhu Ghosh
2009	Misc	`conf`	Monitoring and Control of Level in a Petrochemical Industry using Radar Level Transmitter and LabVIEW. IKE Abhishek Mallik, Aruni Basu, Subrata Mallick

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.