S. Joseph Jawhar

13 papers Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive MPC Tuning for Torque Ripple Reduction in BLDC Motors using Bayesian Annealing Optimizer. J. Circuits Syst. Comput. S. V. Kayalvizhi, V. Suresh, S. Joseph Jawhar
2026	J	`jnl`	Optimization of PID and FIS Controller via ASMO to Enhance the Performance of Brushless DC Motor. J. Circuits Syst. Comput. V. Suresh, S. V. Kayalvizhi, S. Joseph Jawhar
2025	J	`jnl`	Detecting complex copy-move forgery using KeyPoint-Siamese Capsule Network against adversarial attacks. Int. J. Mach. Learn. Cybern. S. B. Aiswerya, S. Joseph Jawhar
2024	J	`jnl`	FOD-YOLO NET: Fasteners fault and object detection in railway tracks using deep yolo network1. J. Intell. Fuzzy Syst. K. Brintha, S. Joseph Jawhar
2023	J	`jnl`	Dropout AlexNet-extreme learning optimized with fast gradient descent optimization algorithm for brain tumor classification. Concurr. Comput. Pract. Exp. Michael Mary Adline Priya, S. Joseph Jawhar
2021	J	`jnl`	Diagnosis of Brain Tumor Using Nano Segmentation and Advanced-Convolutional Neural Networks Classification. J. Medical Imaging Health Informatics P. V. Deepa, S. Joseph Jawhar, J. Merry Geisa
2021	J	`jnl`	Nanoscale imaging technique for accurate identification of brain tumor contour using NBDS method. J. Ambient Intell. Humaniz. Comput. K. Vijila Rani, S. Joseph Jawhar, S. Palanikumar
2021	J	`jnl`	Optimal Deep Belief Network with Opposition based Pity Beetle Algorithm for Lung Cancer Classification: A DBNOPBA Approach. Comput. Methods Programs Biomed. Michael Mary Adline Priya, S. Joseph Jawhar, J. Merry Geisa
2020	J	`jnl`	Advanced lung cancer classification approach adopting modified graph clustering and whale optimisation-based feature selection technique accompanied by a hybrid ensemble classifier. IET Image Process. Michael Mary Adline Priya, S. Joseph Jawhar
2020	J	`jnl`	Automatic segmentation and classification of lung tumour using advance sequential minimal optimisation techniques. IET Image Process. K. Vijila Rani, S. Joseph Jawhar
2020	J	`jnl`	Superpixel with nanoscale imaging and boosted deep convolutional neural network concept for lung tumor classification. Int. J. Imaging Syst. Technol. K. Vijila Rani, S. Joseph Jawhar
2019	J	`jnl`	Cluster computing based optimization techniques for control of electrical drives. Clust. Comput. S. Subiramoniyan, S. Joseph Jawhar
2018	J	`jnl`	Novel bacterial foraging-based ANFIS for speed control of matrix converter-fed industrial BLDC motors operated under low speed and high torque. Neural Comput. Appl. T. S. Sivarani, S. Joseph Jawhar, C. Agees Kumar, K. Premkumar

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.