Bagesh Kumar - RankMe

13 papers Journal 3Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Lost in Translation? A Comparative Study on the Cross-Lingual Transfer of Composite Harms. CoRR Vaibhav Shukla, Hardik Sharma, Adith N. Reganti, Soham Wasmatkar, Bagesh Kumar, Vrijendra Singh
2024	—	`conf`	Enhancing Visual Question Answering with Beam Search in Transformer Models. CICBA (1) Pratiksh Kumar, Rishik Gupta, Vanshika Mishra, Prakhar Shukla, Bagesh Kumar, Pratham Bhatia, Abhinav Upadhyay
2024	—	`conf`	Talk to Your Brain: Artificial Personalized Intelligence for Emotionally Adaptive AI Interactions. CVMI Sandeep Varma, Shivam, Sarun Natarajan, Biswarup Ray, Bagesh Kumar, Om Dabral
2023	—	`conf`	A Natural Language Processing-Based Multimodal Deep Learning Approach for News Category Tagging. CVIP (3) Bagesh Kumar, Alankar Singh, Vaidik Sharma, Yuvraj Shivam, Krishna Mohan, Prakhar Shukla, Tanay Falor, Abhishek Kumar
2023	—	`conf`	Enhanced Heart Disease Classification Using Parallelization and Integrated Machine-Learning Techniques. CVIP (3) Subham Panda, Rishik Gupta, Chandan Kumar, Rashi Mishra, Saransh Gupta, Akash Bhardwaj, Pratiksh Kumar, Prakhar Shukla, Bagesh Kumar
2022	—	`conf`	An approach for classifying benign and malignant skin lesions using Optimized Deep Learning and SVM. IC3 Bagesh Kumar, Amritansh Mishra, Subham Raj, Aditya Kumar, Om Suhas Vibhandik, Aayush Talesara, Shubham Kumar, O. P. Vyas
2022	—	`conf`	Generating Textual Description Using Modified Beam Search. ICONIP (5) Divyansh Rai, Arpit Agarwal, Bagesh Kumar, O. P. Vyas, Suhaib Khan, S. Shourya
2022	—	`conf`	Object Detection for Autonomous Vehicle in Hazy Environment using Optimized Deep Learning Techniques. IC3 Bagesh Kumar, Amritansh Mishra, Aayush Talesara, Shubham Kumar, Sourav Dey, O. P. Vyas, Ranjana Vyas
2022	—	`conf`	Optimized Forex Trading using Ensemble of Deep Q-Learning Agents. IC3 Bagesh Kumar, Aadharsh Roshan, Ayush Baranwal, Sankalp Rajendran, Sahil Sharma, Amritansh Mishra, O. P. Vyas
2022	—	`conf`	Sample Reduction for Support Vector Data Description (SVDD) by Farthest Boundary Point Estimation (FBPE) using Gradients of Data Density. IC3 Pratyush Pareek, Aaryan Bhardwaj, Sanskar Patro, Anirudh Arora, Muskan Deep Kaur Maini, Bagesh Kumar, O. P. Vyas
2021	J	`jnl`	A fast learning algorithm for One-Class Slab Support Vector Machines. Knowl. Based Syst. Bagesh Kumar, Ayush Sinha, Sourin Chakrabarti, O. P. Vyas
2021	—	`conf`	Classification of Indoor-Outdoor Scene Using Deep Learning Techniques. MIND Bagesh Kumar, Harshit Gupta, Shriyash Pravin Ingale, O. P. Vyas
2020	J	`jnl`	Sequential Minimal Optimization for One-Class Slab Support Vector Machine. CoRR Bagesh Kumar, Ayush Sinha, Sourin Chakrabarti, Aashutosh Khandelwal, Harsh Jain, O. P. Vyas

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.