Aasheesh Shukla

15 papers Journal 9Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Corrections to "Plant Leaf Disease Detection, Classification and Diagnosis Using Computer Vision and Artificial Intelligence: A Review". IEEE Access Anuja Bhargava, Aasheesh Shukla, Om Prakash Goswami, Mohammed H. Alsharif, Peerapong Uthansakul, Monthippa Uthansakul
2024	J	`jnl`	Plant Leaf Disease Detection, Classification, and Diagnosis Using Computer Vision and Artificial Intelligence: A Review. IEEE Access Anuja Bhargava, Aasheesh Shukla, Om Prakash Goswami, Mohammed H. Alsharif, Peerapong Uthansakul, Monthippa Uthansakul
2023	J	`jnl`	A Vehicle-to-Grid System for Controlling Parameters of Microgrid System. Sensors Jigar Sarda, Yashrajsinh Raj, Arpita Patel, Aasheesh Shukla, Satish Kachhatiya, Mangal Sain
2023	—	`conf`	An Insight Through Reviews on Neural Network Based Data Mining. IC3I Aasheesh Shukla, Manish Sharma, A Kakoli Rao, N. Shalini, Navneet Kumar, Sahil Singh, Ajay Rana
2023	J	`jnl`	Computational Analysis of Uplink NOMA and OMA for 5G Applications: An Optimized Network. Informatica (Slovenia) Shelesh Krishna Saraswat, Vinay Kumar Deolia, Aasheesh Shukla
2023	—	`conf`	Data Sharing Enabled Through Internet of Things (IoT) in Wireless Communication Networks. IC3I Aasheesh Shukla, Sumit Pundir, A Kakoli Rao, N. Shalini, Akhil, Rohit Kumar, Ajay Rana
2023	—	`conf`	Design Analysis of Inductor less LNA with Noise Cancellation Technique for Ultra Wide Band Applications. ICCCNT Praveen Kumar, Manish Kumar, Aasheesh Shukla
2023	J	`jnl`	Intelligent Reflecting Surfaces Assisted Full-Duplex IDMA Communication Network. Wirel. Pers. Commun. Aasheesh Shukla, Manish Kumar, Manish Gupta
2023	J	`jnl`	Machine learning & computer vision-based optimum black tea fermentation detection. Multim. Tools Appl. Anuja Bhargava, Atul Bansal, Vishal Goyal, Aasheesh Shukla
2023	—	`conf`	Predicting Rainfall Using an Artificial Neural Network-Based Model. IC3I Aasheesh Shukla, Manish Sharma, Kripanshu Tiwari, V. Divya Vani, Naveen Kumar, Pooja
2022	J	`jnl`	Buffer-aided cooperative NOMA with partial relay selection. Telecommun. Syst. Pattima Bachan, Aasheesh Shukla, Atul Bansal
2021	J	`jnl`	A comprehensive review on soil classification using deep learning and computer vision techniques. Multim. Tools Appl. Pallavi Srivastava, Aasheesh Shukla, Atul Bansal
2018	J	`jnl`	Analysis and design of tent map interleaver for interleave division multiple access scheme. Int. J. Wirel. Mob. Comput. Aasheesh Shukla, Vinay Kumar Deolia
2014	—	`conf`	Performance analysis of S-Random interleaver for IDMA system using MRRC diversity scheme. IC3 Sonam Sharma, Paresh Chandra Sau, Aasheesh Shukla
2014	—	`conf`	Performance boosting approach of S-Random interleaver for IDMA system using Walsh code. ICACCI Sonam Sharma, Paresh Chandra Sau, Aasheesh Shukla

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.