Ulligaddala Srinivasarao

11 papers Journal 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An efficient attention encoder decoder-based residual-UNet for the segmentation of liver and lung tumour. Int. J. Data Min. Bioinform. Rakesh Kumar Donthi, Ram Chandra Bhushan, N. Lakshmipathi Anantha, P. Dileep, Ulligaddala Srinivasarao
2026	J	`jnl`	Group-Based Recommendation System Using Bi-Stage Adaptive Deep Learning Model. Int. J. Comput. Intell. Syst. Yojitha Chilukuri, A. Prashanthi, M. V. Kamal, P. Dileep, Rakesh Kumar Donthi, Nemala Jayasri, Ulligaddala Srinivasarao
2025	J	`jnl`	An EfficientNet-B0 Framework for Nitrogen Stress Identification in Sustainable Precision Farming Plants. Cogn. Comput. Surya Babu, Kartikey Thawait, Arepalli Peda Gopi, Ulligaddala Srinivasarao, K. Jairam Naik
2025	J	`jnl`	Biomedical named entity recognition using improved green anaconda-assisted Bi-GRU-based hierarchical ResNet model. BMC Bioinform. Ram Chandra Bhushan, Rakesh Kumar Donthi, Yojitha Chilukuri, Ulligaddala Srinivasarao, Polisetty Swetha
2024	J	`jnl`	Optimized aspect and self-attention aware LSTM for target-based semantic analysis (OAS-LSTM-TSA). Data Technol. Appl. B. Vasavi, P. Dileep, Ulligaddala Srinivasarao
2024	J	`jnl`	Sentiment analysis from email pattern using feature selection algorithm. Expert Syst. J. Knowl. Eng. Ulligaddala Srinivasarao, Aakanksha Sharaff
2023	J	`jnl`	Application of Convolutional Neural Networks for COVID-19 Detection in X-ray Images Using InceptionV3 and U-Net. New Gener. Comput. Aman Gupta, Shashank Mishra, Sourav Chandan Sahu, Ulligaddala Srinivasarao, Jairam Naik Khetavath
2023	J	`jnl`	Machine intelligence based hybrid classifier for spam detection and sentiment analysis of SMS messages. Multim. Tools Appl. Ulligaddala Srinivasarao, Aakanksha Sharaff
2023	J	`jnl`	SMS sentiment classification using an evolutionary optimization based fuzzy recurrent neural network. Multim. Tools Appl. Ulligaddala Srinivasarao, Aakanksha Sharaff
2023	J	`jnl`	Spam email classification and sentiment analysis based on semantic similarity methods. Int. J. Comput. Sci. Eng. Ulligaddala Srinivasarao, Aakanksha Sharaff
2022	J	`jnl`	Email thread sentiment sequence identification using PLSA clustering algorithm. Expert Syst. Appl. Ulligaddala Srinivasarao, Aakanksha Sharaff

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.